American Diabetes Association 76th Scientific Sessions

June 10-14, 2016; New Orleans, LA; Full Report – Draft

Executive Highlights

In this final report, we provide our full coverage of the 76th Scientific Sessions of the American Diabetes Association (ADA), held at the New Orleans Ernest N. Morial Convention Center from June 10-14, 2016. This very successfully organized ADA gathering drew over 16,000 attendees, including 13,265 clinicians in attendance. Total attendance was down noticeably from the attendance of over 18,000 last year in Boston, presumably due to location. This year, a striking 58% of registered attendees were from outside the US in 2016, with over 120 countries represented – the international audience is getting broader and broader.

We worked harder than ever for you this year, covering the most compelling updates in the five-day Scientific Sessions, which included 95 symposia sessions, over 50 oral presentation sessions, and 2,026 poster presentations. ADA received over 2,500 abstracts this year.

Major drug highlights included the full LEADER (Novo Nordisk’s GLP-1 Victoza [liraglutide]) results showing a 13% risk reduction for the primary MACE endpoint, renal outcome results from EMPA-REG OUTCOME (Lilly/BI’s Jardiance [empagliflozin]) demonstrating a 39% risk reduction for new-onset or worsening kidney disease, favorable A1c results from SUSTAIN 2 and 3 (Novo Nordisk’s semaglutide), and impressive hypoglycemia reductions for Novo Nordisk’s Tresiba (insulin degludec) in SWITCH 1 and 2. We also heard plenty on the future directions for type 2 drugs, particularly the GLP-1 class, and the use of SGLT-2 inhibitors in type 1 diabetes.

In technology, we were impressed to see positive results from three important studies for the field: Medtronic’s MiniMed 670G pivotal trial, Dexcom’s DIaMonD study testing CGM in MDI, and Abbott’s FreeStyle Libre IMPACT study. We got a very deep dive on automated insulin delivery at this ADA, just as the field is on the cusp of commercialization. It was also great to see much more progress made on making diabetes data actionable, specifically making insulin easier to use.

In this final report, we include 43 themes immediately below, followed by detailed commentary from 304 talks and discussions (orals, symposia, lectures, panels, corporate symposia, and press conferences), 77 posters, and 28 exhibits.

Below, we have organized our writing into 20 specialized reports:

Diabetes Drugs: (1) GLP-1 Agonists; (2) SGLT-2 Inhibitors; (3) Insulin Therapy; (4) DPP-4 Inhibitors; (5) Novel Therapies; (6) Type 1 Diabetes Cure Therapies and Pathophysiology;

Diabetes Technology: (7) Closing the Loop and Insulin Delivery; (8) Glucose Monitoring; (9) Digital Health;

Additional Topics: (10) Obesity and Prediabetes Care; (11) Diabetes Complications; (12) Treatment Algorithms and Strategies; (13) Policy and Reimbursement; (14) Epidemiology, Education, and Additional Topics, (15) Generic Drugs; and (16) Exhibit Hall.

Events: (17) TCOYD/The diaTribe Foundation Forum; (18) Musing Under the Moon

Historical Visits in the New Orleans Area: (19) Whitney Plantation; (20) National WWII Museum

We’ve highlighted in yellow any presentations and commentary that we found particularly notable. Talks that were either not published in our daily highlights reports or have been significantly expanded are highlighted in blue (unless that talk was a notable yellow highlight).

When applicable, certain talks and sessions have been duplicated in multiple chapters (e.g., content on GLP-1/basal insulin products may appear in both the GLP-1 and Insulin Therapy categories).

We send along our most sincere appreciation to all our Closer Look readers for their support and for what they do for diabetes and obesity everyday and a special shout out from Kelly and John to Adam Brown and Sarah Odeh and all the Close Concerns alums and friends of Close Concerns who added so much to this conference – and whom we owe the world to make so much learning happen for us all. Onward!

Table of Contents 

Themes

Diabetes Technology

Automated Insulin Delivery

  • The AID (Automated Insulin Delivery) field is now moving into the commercialization stage. Will the first hybrid closed loop system, Medtronic’s MiniMed 670G/Enlite 3, be on the US market by ADA 2017?! Medtronic reported strong 670G pivotal study results at ADA (see below), and an FDA submission is planned before the end of this month (June 2016). FDA’s Dr. Courtney Lias even expressed hope during ADA that the review will be quick, and the company’s pre-ADA Analyst Meeting maintained the US launch timing by April 2017. Usability will be key – one never knows exactly what the difference will be between using a technology “in the wild” (also known as real life) vs. in a very well managed clinical trial without a parallel control group. Hopes are high … key opinion leaders are also talking about 2017 commercialization for the 670G, meaning next year could be the year it all starts.
    • Meanwhile, commercial systems from 6+ companies are gearing up for pivotal studies in the next ~6-18 months. Six! Animas, Tandem, TypeZero/International Diabetes Closed Loop Consortium (IDCL), Beta Bionics, Bigfoot Biomedical, Insulet, and others have all announced pivotal study plans with commercial devices (roughly in pivotal trial order), which will make the next couple of years very competitive and exciting for this field. (See our competitive landscape here.) It’s been a fast turnaround from ADA 2015, where the 670G pivotal study was only beginning, and a transformative leap from ADA 2014, where the AID discussion focused nearly exclusively on academic systems.
  • Medtronic headlined the AID discussion at ADA, presenting very positive results from the first pivotal study of a commercial system, the MiniMed 670G/Enlite 3 hybrid closed loop. The single-arm, three-month study in 94 adults and 30 adolescents compared a two-week open-loop run-in period to 90 days on the 670G, showing a 0.5% reduction in A1c from a low study baseline of 7.4%; time <70 mg/dl declining 44% (from 6% to 3%); and time <50 mg/dl declining 40% (1% to 0.6%). It was impressive to see the impact on A1c, given the strong reduction in hypoglycemia and the very well-controlled population of pumpers. (We note that the pumpers were spending only 7% of the time below 70 mg/dl – that’s pretty great control to begin with.) Notably, those with a baseline A1c >7.5% actually saw a 1% reduction after three months on the 670G. Time-in-range (71-180 mg/dl) improved from 67% during the baseline run-in to 72% during the study, with time >180 declining moderately (27% to 25%). That improvement does not sound so significant, but it was clear from the glucose profiles that the MiniMed 670G made extreme highs (e.g., 300 mg/dl) more moderate (e.g., ~200 mg/dl) – a highly valuable improvement, but not showing up as a change to time in 70-180 mg/dl. The glucose profiles (see below) show how the 670G really tightened the range of glucose values throughout the entire day in both populations, with particularly strong efficacy overnight and in adolescents. The new Enlite 3 sensor is a definite improvement, with an overall MARD of 10.3% in this study and 10.5% in its separate pivotal accuracy study.
    • Overall, we see the 670G pivotal data as meaningful for the entire field of automated insulin delivery. This single-arm, uncontrolled study was clearly designed for speed and to prove safety to the FDA, so it’s hard to read too much into the efficacy results, where there were not pre-specified endpoints. Still, reducing A1c 0.5% in well-controlled patients at the same time hypoglycemia declining 44% is a huge win – and the results were consistent in adolescents and adults. It’s clear that automated insulin delivery can make a difference even with first-gen hybrid closed loop products, and even in those doing pretty well. Of course, the hope is it can really improve outcomes for those with much higher A1cs as well (for example, over >10%) or at high risk of severe hypoglycemia, groups that were both excluded from this study.
    • Stanford’s Dr. Trang Ly characterized the 670G results as “outstanding,” and said that the biggest challenge will be managing expectations: “This is not going to cure you,” she noted, as the first-gen 670G algorithm is still somewhat conservative, and hybrid systems like the 670G will still require patient effort – to be specific, carb counting, manual corrections, infusion set changes, sensor wear and calibrations, etc. The 670G algorithm itself has ten years of work behind it, but since it only modulates basal insulin delivery, it will be most efficacious overnight, and it will clearly not remove all patient burden during the day. We expect to hear more on the 670G’s usability and user-friendliness as it gets closer to market.
  • Like so many other products, we expect those automating insulin delivery will improve with time, and the key will be in consistently improving the benefit-burden balance to expand the market. What will AID add onto patients’ and providers’ plates, and what will it remove? How will this balance vary based on what patients are already using – e.g., current pump-CGM users vs. MDI-SMBG users – and how will it change as insulins continue to improve, Bluetooth pens emerge, and standalone CGM sees better value with enhanced apps?
    • First-gen AID technology will likely be an upgrade for many current pump-CGM users, though the bar will be high for MDI-SMBG users – going from zero to two devices on the body will increase burden and cost, which means the corresponding improvement in outcomes needs to be big. For how many will that be worth it with gen one, gen two, etc.? What percentage of MDIs will ultimately wear AID systems?
    • What will most differentiate closed loop systems in a few years: outcomes/reimbursement, form factor, user interface, algorithms, other hormones, etc.? What will the adoption curve look like in five or ten years? What feature(s) will be the killer app(s) for AID that drive adoption – Full automation without meal announcement? Factory calibrated CGM? Smaller on-body devices? Integrated CGM/pump infusion sets? Will AID ever become standard of care in type 1? Will this technology appeals to MDIs that are struggling to manage blood glucose?
  • The nuances of pivotal study design, standardizing outcome metrics, the reimbursement landscape, and the psychosocial impact are now top of mind in the field. Though these have always been in the discussion, all emerged as themes at JDRF’s annual Closed-Loop Research Meeting as well as in countless Closed Loop discussions, and all reminded us that the commercial side of closing the loop presents awesome design opportunities and nuanced challenges. Which system(s) and companies will nail these aspects in the coming years?
    • Pivotal Study Design: MGH’s Dr. Steven Russell summarized a soon-to-be-published Diabetes Care paper he co-authored with Dr. Roy Beck, sharing pivotal study design recommendations for AID systems – this will be fantastic to see! Drs. Beck and Russell recommend broad study inclusion criteria (MDIs included, wide age and A1c ranges), use of A1c and time <60 mg/dl as primary endpoints, a parallel group design (faster), 6-12 months in length, and compared to usual care. Pivotal AP studies have several goals besides regulatory approval – advantageous labeling, reimbursement, prescribing by practitioners, and adoption by patients – meaning study design decisions now will be critical down the road.
    • Reimbursement: Avalere Health’s Amanda Bartelme gave a fascinating overview of AID reimbursement, highlighting some of the key challenges: too much payer focus on A1c, hard-to-predict contracting negotiations, data needs that differ from FDA approval requirements, and more. Ms. Bartelme cautioned that “if a payer thinks every type 1 patient wants to go on this tomorrow, that’s huge dollar signs and huge panic.” It served as a reminder that nothing is a given with payers in this environment – even AID devices that reduce A1c, hypoglycemia, and patient burden will have to demonstrate return-on-investment, and ideally, short-term. Q&A sessions throughout the conference also expressed worry about AID reimbursement, as many clinicians are still battling payers to even cover CGM. From what we can tell, Medtronic will pursue the existing reimbursement channels for the MiniMed 670G (i.e., sensor-augmented pump reimbursed via DME), though this field seems ripe for a new business model (e.g., AID for $75 a month).
    • Standardizing Outcomes Metrics: Barbara Davis Center’s Dr. David Maahs (soon to be at Stanford) summarized another upcoming Diabetes Care paper focused on standardizing a short set of basic, easily interpreted outcomes in artificial pancreas studies. The paper has 24 authors, many of whom are considered leading thinkers in the field. The goal is for the entire field to report study outcomes the same way, easing interpretation, enabling basic comparison between studies, and accelerating adoption via regulators, HCPs, payers, and patients. We love this move!
    • Psychosocial impact: Stanford’s Dr. Korey Hood shared that a full set of validated questionnaires will be available by Fall 2016 to assess the psychosocial impact of automated insulin delivery. There are high expectations that AID will help manage glycemia and improve quality of life, but the field is still in need of tools to help regulatory approval bodies, payers, HCPs, and patients assess systems’ full benefit-risk balance. How do we measure better quality of life due to less diabetes-related stress or better sleep? As insulin delivery becomes automated, how do we protect against deskilling and human-machine interaction failures and confusion? What is the stigma associated with carrying extra devices in those not currently using a pump or CGM? Experiences will fall along a spectrum, of course, but these are critical questions as AID systems are on the cusp of commercialization. We hope these new questionnaires can help add context to the non-glycemic benefits of AID systems, and perhaps identify those that are optimal candidates for the technology. Our greatest hope is that AID massively improves outcomes and quality of life in those struggling on current therapies, whether they are using MDI, pump, SMBG, or CGM.
  • Many called for closed-loop devices to include algorithms with customizable glucose targets. A patient panel at Diabetes Mine’s D-Data Exchange was clear that adjusting an algorithm’s aggressiveness is very key – some patients want more control, particularly in early-generation systems that will err on the conservative side. Indeed, Stanford’s Dr. Trang Ly pointed to this as an area for improvement in the Medtronic MiniMed 670G, which targets 120 mg/dl and does not allow the user to lower the target. The Bionic Pancreas team’s work comparing insulin-only to bihormonal control at different glycemic targets echoes the same point – an algorithm’s target does influence mean glucose and hypoglycemia, sometimes significantly so. Of course, there is a tough balance between customizability and simplicity – tweaking every parameter might be ideal for early adopters, but will add too much complexity that could hinder adoption. It’s a very delicate equilibrium, though targets will certainly go down over time as insulins get faster, sensors improve further, and the FDA and companies get more comfortable with these systems. It will be interesting to compare different commercial systems’ algorithms once they are available, as there may be meaningful differences in aggressiveness, meal announcement burden, initialization and training requirements, alarms, level of adaptation, and more.
  • ADA 2016 shed the most light yet on OpenAPS, the DIY automated insulin delivery system created by Ben West, Dana Lewis, and Scott Leibrand. The community now has 80 users and has over 150,000 hours of AID use outside any clinical trial setting. An illuminating late-breaking poster presented fascinating data from 18 out of the first 40 OpenAPS users. Self-reported outcome measures showed median A1c dropped from 7.1% to 6.2%, an impressive 0.9% reduction in a well-controlled and motivated population. Self-reported median percent time-in-range (80-180 mg/dl) increased from 58% to 81%. Fourteen out of 15 respondents reported some improvement in sleep quality, and 56% reported a large improvement. Respondents were “extremely satisfied with the “life changing” improvements associated with using an APS,” even if they “require significant effort to build and maintain” and “cannot be considered a technological cure.” Though such “hacked together” DIY systems are often perceived as unsafe, the OpenAPS design considerations posted here show how it is designed for safety (e.g., only temporary basals, no automatic correction boluses, etc. – much like the 670G hybrid closed loop).
    • The “unapproved” OpenAPS concerned some clinicians at ADA. Overall, the small community left us with positive takeaways for the field: (i) automated insulin delivery can make a huge glycemic and quality of life difference, even for well-controlled patients; (ii) even though this DIY system is burdensome to set up and wear, patients would not do it and use it unless the benefits were worthwhile (hopefully a good sign for fully integrated commercial systems); (iii) lots of learning is occurring in the OpenAPS community that could be leveraged for commercial systems; (iv) OpenAPS could push the FDA and industry to move faster, and that is a good thing; and (v) the relative risks here seem low, given the involved burden of setup, the solid design for safety, and the real-world dangers of insulin therapy. 
  • Some of the most compelling AID data came from the Cambridge team, who tested their system in inpatient type 2 diabetes – the first of this kind of closed-loop study ever done. The study shared striking improvements in efficacy and safety vs. the truly grim standard of care achieved with open-loop in the hospital. The parallel-arm study randomized 24 patients to receive either closed-loop therapy (n=12) or conventional subcutaneous insulin therapy per clinical guidelines with masked CGM (n=12) for a period of 72 hours. The data looked outstanding and terrifying at the same time – closed-loop control significantly improved time-in-target from 38% to 61% for the 100-180 mg/dl range (p<0.001). Mean glucose improved from 182 mg/dl to 161 mg/dl, just shy of statistical significance (p=0.065). The study used the Cambridge algorithm with unannounced meals, which made control much harder in the closed-loop arm. There was absolutely no difference in hypoglycemia (0% in both groups), and no severe hypoglycemia or adverse events were observed. We left the presentation reminded yet again of the very negative state of current inpatient glucose management. Indeed, we were downright disheartened by the standard of care overnight (mean glucose = 202 mg/dl), and the findings served as a striking reminder of: (i) the need for glucose management education in the hospital setting; and (ii) the great potential for inpatient technology to improve diabetes management and resulting outcomes. The tendency to accept hyperglycemia in inpatients is truly wrong, and we look forward to more studies of AID in this population.
  • This ADA featured less insulin-only vs. bihormonal debate than at ATTD 2016 or last year’s Scientific Sessions. The need for a stabilized glucagon with chronic exposure data has pushed the Bionic Pancreas’ bihormonal timing to 2019-2020. Dr. Ed Damiano, CEO of Beta Bionics, revealed that Zealand’s liquid stable glucagon analog will be tested in clinical trials with the fully integrated iLet bionic pancreas in 2H16. The pivotal studies of the insulin-only iLet are still expected to start in 2Q17, with an FDA submission planned for the end of 2017. The bihormonal pivotal trial, which will begin after the start of the insulin-only pivotal trial, will require that a subset of the study cohort use the iLet for 12 months in order to gain chronic glucagon exposure for a new indication for use of glucagon in a bihormonal bionic pancreas. That puts the bihormonal FDA submission timing into ~early 2019, putting potential approval around late 2019 or 2020.
    • Timing aside, glucagon does allow more patients to reach a mean glucose <154 mg/dl without increasing hypoglycemia. The Bionic Pancreas team again shared their fascinating insulin-only vs. bihormonal glycemic target studies, first discussed at ATTD. The randomized, crossover study (n=20) compared usual care to insulin-only and bihormonal versions of the Bionic Pancreas at different glycemic targets (insulin-only: 130 and 145 mg/dl; bihormonal: 100, 115, 130 mg/dl) over three-day experiments. The insulin-only and bihormonal systems were actually very similar with a glycemic target of 130 mg/dl: a mean glucose of 161 vs. 156 mg/dl and time <60 mg/dl of 0.8% vs. 0.5%. As the bihormonal target dropped to 115 and 110 mg/dl, mean glucose improved to 146 and 136 mg/dl without increasing hypoglycemia. The team is now exploring an insulin-only target of 110 mg/dl, as the use of 130 mg/dl was intentionally conservative.

Glucose Monitoring

  • ADA 2016 was a BIG meeting for sensor outcomes data: Dexcom’s DIaMonD study (testing CGM in MDI) and Abbott’s IMPACT study (testing FreeStyle Libre in well-controlled type 1s) both impressed. Both studies represented strong and positive results for Dexcom, Abbott and the entire field, and a signal of how far industry has come and where things are going in the future: proving outcomes.
    • Dexcom’s DIaMonD study randomized MDI users to six months of CGM (n=105) or six months of usual care (n=53). A1c declined a strong 0.9% with CGM at six months vs. -0.4% with usual care (baseline: 8.6%), for an adjusted mean difference of -0.6% in favor of CGM (p<0.001). The advantage for CGM was impressively consistent across age, baseline hypoglycemia, education, and diabetes numeracy – 60+ year-old CGM users saw the same benefit as 25-60 year-old users in this study. At the same time A1c declined, hypoglycemia significantly improved with CGM: a 30% improvement in time <70 mg/dl (-23 mins/day; p=0.006) and a strong 50% improvement in time <50 mg/dl (-11 mins per day; p=0.005), both outperforming 17% and 21% improvements with usual care (-15 mins, -6 mins). While the absolute reductions are not huge here, the high A1c baseline patients were not experiencing an overwhelming amount of hypoglycemia at baseline. On the high end, CGM users were spending 83 fewer minutes per day above range (>180 mg/dl) at 24 weeks, while the usual care group was spending nine more minutes per day above range (p=0.04). That translated to CGM users spending an hour more per day in range (70-180 mg/dl) at 24 weeks, while the usual care group spent 15 fewer minutes per day in range (p=0.006). CGM trended towards less severe hypoglycemia: a 2% rate (two out of 105 patients) vs. a 4% rate in usual care (two out of 53 patients). Glycemic variability also improved a bit with CGM (median CV: 42% to 38%), but did not change in usual care (42% to 42%) (p<0.001). Daily SMBG tests declined as expected in the CGM group (from 5.1/day to 3.6/day), but stayed roughly similar in the usual care group (5.1/day to 4.6/day) (p<0.001). CGM wear >6 days per week was seen in an impressive 89% of patients at six months, a testament to the better technology and the tight adherence criteria (>85% wear) patients had to demonstrate during the blinded CGM phase before randomization.
      • DIaMonD shows that MDI users not at glycemic target can definitely benefit from CGM – getting a meaningful reduction in A1c (-0.9% from baseline), shaving off highs, cutting their time in mild and dangerous hypoglycemia, and improving variability. We hope this large randomized study can help influence more CGM prescribing in MDIs, countering the “pump first” mentality that Dexcom has always battled. More importantly, we hope DIaMonD can influence professional guidelines and further improvement CGM reimbursement. DIaMonD is also a milestone for Dexcom, who has never run an outcomes study, and will need to do more to keep up with Medtronic’s and Abbott’s growing lists. Phase 2 of the study will cross some of the MDI patients over to pumps, so we’ll eventually see if insulin delivery method makes a difference. We want to see tools driving therapeutic change and creating “higher quality” A1cs and this certainly seemed to happen here.
    • Abbott’s IMPACT study compared FreeStyle Libre to SMBG in type 1 patients in very good control (baseline A1c: 6.7 %). The study met its primary endpoint at six months – relative to the control group, patients using FreeStyle Libre spent a striking ~74 minutes fewer per day <70 mg/dl (a 38% reduction; p<0.001). Pre-specified secondary endpoints were particularly compelling – patients using Libre spent ~49 minutes fewer per day <55 mg/dl (a 50% reduction; p<0.0001) and ~33 minutes fewer per day <45 mg/dl (a 60% reduction; p<0.0001). Measures of nocturnal hypoglycemia were also significantly lower with FreeStyle Libre as patients spent ~28 minutes fewer per night (a 40% reduction; p<0.0001) in hypoglycemia. Patients using Libre spent ~22 minutes fewer per day in extreme hyperglycemia > 240 mg/dl (p=0.02) and spent ~60 minutes greater/day between 70-180 mg/dl (p=0.0006). There was not a significant difference in A1c between the groups, and both saw a marginal ~0.15% increase by the end of the study – a positive given that these patients were spending three hours per day in hypoglycemia at baseline! In other words, FreeStyle Libre prompted a higher quality A1c, with one hour less hypoglycemia per day. The factory-calibrated sensor pretty much completely replaced fingerstick testing, suggesting a high level of confidence in its accuracy: SMBG frequency with FreeStyle Libre fell from a mean of ~5.5 tests/day at baseline to 0.5 tests/day (one every two days) at six months, a testament to the real-world accuracy in patients on insulin therapy. This is very good news as it seeks FDA approval, with now two large RCTs (REPLACE at ATTD and now IMPACT) backing up this finding.
      • IMPACT highlights the truly scary amount of hypoglycemia type 1s on insulin therapy are experiencing every day, and the tremendous challenges of dosing insulin as A1c approaches goal – all patients at baseline were spending ~200 minutes per day <70 mg/dl!!! The hypoglycemia data discussed above is very clinically meaningful (-74 minutes per day), and there is still room to improve therapeutic approaches: patients on Libre were still spending two hours <70 mg/dl per day at six months. Was the residual hypoglycemia driven by over-treating hyperglycemia while on FreeStyle Libre (so-called “hyper avoidance” in intensively managed patients)? Could that be managed with better education? Meanwhile, standard of care patients were still spending over three hours <70 mg/dl per day, no big change from baseline. In that sense, the results tell us as much about FreeStyle Libre’s ability to reduce hypoglycemia as they do about the real-world dangers of insulin therapy, especially in “well controlled” patients skating close to the edge; three hours per day in hypoglycemia is downright dangerous, at the same time these patients would be congratulated for getting below 7%. Avoiding lows on insulin therapy is truly difficult as A1c gets below 7%, and we’re not sure that delicate balance is appreciated enough. Libre and other sensors can help quantify that, and we hope clinical decision support software will help HCPs and patients start to titrate insulin in a data-driven way.
  • Where are glucose sensors going? Accuracy and reliability remain absolutely necessary, but they are no longer sufficient in this cost competitive, outcomes-driven, increasingly digital healthcare environment. It was just three years ago that ADA 2013 featured an entire oral session devoted to CGM accuracy and reliability. With multiple companies boasting available or upcoming sensors with MARDs of ~9-12%, the entire field has clearly picked up its game. Now, accuracy and reliability are the minimum criteria for any new sensor, as there is much more to consider: cost; clinical outcomes data to drive reimbursement; fingerstick calibrations; on-body size; prescribing hassle; connectivity, mobile apps, and clinical decision support software; etc. There is still tremendous room to expand the market, but the race is on to offer the most cost-effective and clinically impactful sensor system and to convince payers and patients of the added value. What will payers think of Dexcom’s DiaMond and Abbott’s REPLACE/IMPACT studies? Will they see this technology as very positive return-on-investment and standard-of-care therapy in type 1 diabetes? Will they make it less of a hassle to get on CGM, even in the US (e.g., no more prior authorizations, appeals, documentation)? Will outcomes and healtheconomic studies be the key frontier on which sensor battles are fought?
    • Automated insulin delivery will be a net positive for the CGM field, though with strong standalone sensor outcomes, will payers do a double take? “Wait, do we really need to cover an automated insulin delivery system (pump and CGM) if patients can get good outcomes with a sensor on MDI?” In that sense, do IMPACT and DIaMonD represent a threat to automated insulin delivery reimbursement? It’s hard to know, but these studies put some pressure on AID systems to show an additional, incremental advantage over best-in-class standalone sensors – particularly because improved apps, pattern recognition, and decision support software are going to make standalone sensors much better.
  • Will the FDA approve a non-adjunctive (BGM replacement) claim for CGM? Dexcom gave a persuasive preview of what we might expect at the July 21 FDA meeting. In short, the risk of an insulin overdose with Dexcom CGM was very low (~0-3%) based on the frequency of erroneously reading 20% or more above YSI in its pivotal trials. The retrospective risk analysis analyzed the two accuracy trials of the G4 Platinum + Software 505 (the same algorithm as in G5) in patients 2-17 years old (n=79) and 18+ years (n=51) vs. YSI. Dr. Walker concluded that G5 mobile is safe for diabetes decision-making, the risk for overdosing is likely minimal, and alerts and alarms further reduce the risk associated with non-adjunctive use of CGM. By contrast, patients using BGM for decision making get point in time snapshots, with no reference to direction, rate of change, or alerts and alarms, plus numerous interfering substances (not to mention hand washing and questionable meter accuracy in the post competitive bidding era). We thought it was a persuasive presentation and look forward to the full case Dexcom presents in a few weeks. Insulin dosing isn’t included on any BGM label, and we wonder how the FDA will approach that irony on July 21.

Data and Digital Health

  • The International Diabetes Center signed agreements to license its one-page, standardized Ambulatory Glucose Profile (AGP) report to Roche, Abbott, Diasend, and Glooko. This news marks an important step towards device-agnostic BGM/CGM download report standardization, which should improve clinical efficiency, hopefully drive less overwhelm and greater therapeutic change, and perhaps even expand adoption of CGM. Dr. Rich Bergenstal told us three other device companies and aggregators are expected to sign similar agreements in “the next month” – the big glucose monitoring players that have not signed on yet include Ascensia, Dexcom, J&J/LifeScan, and Medtronic. Ultimately, the vision for AGP is to become the EKG report of glucose data – something every clinician understands how to interpret and use – and we hope this creates momentum and pressure for every device company to sign on. Not every company is going to get what they want with a standardized report, but the field will benefit significantly from consensus, and companies can obviously innovate on top of AGP. This has been a long time in the making, as the IDC/Helmsley Charitable Trust expert panel on this topic convened in 2012, and the follow-up joint publication appeared in DT&T/JDST in 2013. Kudos to IDC, the Helmsley Charitable Trust, and so many advocates for pushing this forward, and we cannot to see how AGP is implemented and what impact it has on the field.
    • The partnerships give the companies the right to use the AGP in all their diabetes devices and existing software; the agreement with Abbott extends the groups’ existing partnership to other devices, since AGP is already used to visualize downloaded FreeStyle Libre glucose data. The Glooko agreement to use AGP will presumably allow Medtronic and Dexcom CGM data to be displayed in the one-page standardized format, though we wonder if both players will formally sign on. Presumably this expansion also means Roche’s CGM may use AGP when it launches.
  • Medtronic was extremely active on the diabetes data front at ADA, announcing summer updates to CareLink to help optimize pump settings, summer launches of the Glooko and IBM Watson partnerships, and a new food app partnership with Nutrino. It’s such a far cry from the siloed, proprietary Medtronic of three years ago, who simply did not partner and share data, and did not have a pipeline of mobile apps.
    • Next-gen CareLink Pro reports to optimize basal and bolus settings: These will launch this summer and identify optimal insulin:carb ratio, insulin sensitivity factor, and basal rate change. CareLink will suggest which time of day and direction pump settings should change (Increase basal rate from 8am – 12pm). These are step short of the exact recommendations DreaMed will provide with Glooko (“change basal rate to 0.75 u/hr from 8am-12 pm”), but a clear improvement over the status quo!
    • Glooko compatibility: Medtronic pump/CGM devices will (finally!) be compatible with Glooko’s web-based software, kiosk, and mobile app in July. This integration has been more than a year in the making (Medtronic invested in Glooko last March) and we give HUGE kudos to Glooko (and particularly Holly McGarraugh) for breaking open the Medtronic CareLink data silo.
    • Medtronic/IBM Watson Health app, SugarWise: The app is officially named “SugarWise (bringing insight to blood sugars) and is still expected to launch this summer. The first generation app will analyze retrospective data and provide insights based on past CGM, insulin, and nutrition data. The retrospective example from the pre-ADA Analyst Meeting said, “In the last 30 days, high glucose pattern found usually after glazed donut for breakfast.” A future-generation version will add the hypoglycemia prediction feature that we first saw at CES in January – unfortunate this won’t be in gen one.
    • Nutrino food app: The beta app launched during ADA for customers who use MiniMed Connect, providing an individualized picture of how daily food intake and other measures impact glucose levels – see the video here and download the app here. The app reads from Apple’s HealthKit, meaning it should work with Dexcom CGM and Bluetooth meters too (we have not fully tested it yet).
  • Abbott also had several key digital health announcements related to FreeStyle Libre at ADA, continuing the entire field’s move into connectivity, apps, and cloud-based software: (i) its LibreLink Android app for scanning FreeStyle Libre sensors has officially launched in Sweden and the Netherlands on Google Play and more countries are coming by end of month; (ii) a new integration agreement with Diasend enables data from the LibreLink app to automatically populate a patient’s diasend account wirelessly and passively ; and (iii) LibreView was unveiled in the exhibit hall, Abbott’s cloud-based data management software. It is excellent to see Abbott, Dexcom (G5), and Medtronic (MiniMed Connect) all offering mobile app data viewing and passive download to the cloud – now, we hope the magic of really driving therapeutic change with smart algorithms can begin! Abbott’s LibreLink is the only one of the three apps to offer direct Android compatibility for the patient, as both MiniMed Connect and G5 only work with a patient’s Apple iOS device. (Both allow followers to use Android, and both plan to launch Android patient apps this year).
  • In addition to the Medtronic progress, IBM Watson announced three more (!) diabetes partnerships with: (i) ADA to create a sophisticated diabetes advisor to help inform treatment decisions; (ii) HelpAround to provide crowd-sourced, on-demand help to people with diabetes who need it; and (iii) a predictive model to predict retinopathy risk with Israeli HMO Maccabi Healthcare. These augment the Medtronic Diabetes work (see above) and the Novo Nordisk partnership signed last December. With all these partnerships, Watson brings tremendous potential to improve prescribing, to personalize therapy, to improve prediction, and to make sense of all the data that already exists.
    • ADA: ADA CEO Mr. Kevin Hagan announced an exciting long-term partnership with IBM Watson to create a sophisticated diabetes advisor to help inform treatment decisions, plus potential apps for patients and researchers. Clinical decision support and more personalized therapy are clear goals – we can imagine a “Dr. Watson Advisor” that tells clinicians at the point-of-care what therapy to prescribe for a given patient at a given time, similar to its compelling work in cancer – leveraging the entire history of diabetes clinical trials, a patient’s entire case history, and perhaps genomic and other data to give evidence-based, confidence-ranked recommendations. What clinician wouldn’t love that? A new Watson-based innovation program, “Challenge Diabetes,” is also pushing developers to propose apps that will improve the lives of people with diabetes or prediabetes; submissions begin this summer and finalists will be announced this fall. We are elated to see this partnership and wonder if something would be ready by ADA 2017!
    • HelpAround: HelpAround is a fascinating “mobile safety net for people with diabetes,” an app that allows patients and caregivers to ask questions and even find supplies from local patients in moments of need. The IBM Watson partnership will “analyze every help request in real-time, assess its sentiment and tone, and identify frustrations, dissatisfaction and expressions of urgency,” helping further optimize the network of assistance. For example, recognizing in real-time that an individual is in distress in regards to their insulin or glucose levels will allow HelpAround to connect the patient with other insulin users, a nearby retailer, or even a chat with the insulin manufacturer.
    • Retinopathy: This Watson partnership with Israeli HMO Maccabi Healthcare will use machine learning to retrospectively sift through 20 years of data on two million patients to identify who is at risk of retinal damage. The information will be used to design personalized eye examination plans. Theoretically, this same paradigm could be applied to any number of diabetes complications in the future, so that they are caught and treated earlier in development. Nice!

Diabetes Drugs

Cardiovascular Outcomes Trials

  • While LEADER was arguably one of the more likely diabetes drug CVOTs to demonstrate cardioprotection, the results were nonetheless surprisingly positive (from a historical sense) and monumental – cardioprotection and renal protection announced simultaneously. There has been speculation about the potential for cardioprotection with GLP-1 agonists for some time due to the class’ positive effects on weight, blood pressure, and lipids and possible direct effects on the heart and vasculature. Novo Nordisk had expressed cautious optimism in several quarterly updates (most recently in 3Q15) that LEADER would be more likely than most CVOTs to reveal any benefit that existed due to its greater individual patient exposure compared to other trials (mandated minimum exposure of 3.5 years per patient and total exposure of over 30,000 patient-years). That said, there were also many reasons to expect a neutral outcome: the trial was only powered to show non-inferiority, it enrolled a high-risk patient population, any effect of GLP-1 agonists on CVD was expected to be subtle and gradual, and the only other GLP-1 agonist CVOT to report (ELIXA for Sanofi’s lixisenatide) had demonstrated neutral results. In that context, these results were certainly a pleasant surprise and a groundbreaking moment for the type 2 diabetes field.
  • The early consensus seems to be that the benefits in LEADER were most likely related to atherosclerosis. This was the main hypothesized mechanism of CV benefit for GLP-1 agonists before the results were released, as the class positively affects a number of endpoints related to atherosclerosis (e.g., glucose, blood pressure, weight) and may have direct effects on reducing arterial plaque. Speakers at the press briefing for LEADER and in the main results presentation agreed that the results appeared consistent with an atherosclerotic mechanism: the effects took some time to appear and increased over the course of the trial, and they were relatively consistent across multiple atherosclerotic endpoints. This is in marked contrast with the EMPA-REG OUTCOME results for Lilly/BI’s Jardiance (empagliflozin), which demonstrated an immediate effect on heart failure and CV mortality and little to no signal of an effect on MI or stroke. While we expect plenty of further speculation and investigation of the exact mechanism of benefit in LEADER (Dr. Laurie Baggio offered a few specific hypotheses in her discussant presentation), the field appears to be closer to a consensus hypothesis in this case compared to EMPA-REG OUTCOME.
  • We have many remaining questions about the clinical implications of the results that could take years to resolve. Dr. John Buse (University of North Carolina, Chapel Hill, NC) emphasized in his concluding presentation that the results should only be applied to the specific patient population enrolled in LEADER – those with longstanding type 2 diabetes and high CV risk. We expect that any updates to the Victoza label and to type 2 diabetes treatment guidelines will only be applied to this population in the absence of what would be a very expensive trial in a lower-risk population. However, we also imagine that many clinicians may incorporate the results into their risk/benefit calculus for Victoza even for lower-risk patients. We are also very curious to see what the implications will be for Saxenda (liraglutide 3.0 mg for obesity), which is unlikely to undergo a CVOT of its own. We would love to see Novo Nordisk conduct a CVOT for the more potent GLP-1 agonist semaglutide in patients with obesity and without type 2 diabetes, though we understand such a trial would also be very expensive. The question of a GLP-1 agonist class effect on CV outcomes is sure to be a hot topic for the next several years as CVOTs for other agents report results. In the near term, we expect the results to bolster the class as a whole but to disproportionately benefit Victoza until additional CVOTs report data. It will be very interesting to see how clinicians weigh the demonstrated CV benefits with Victoza against advantages like once weekly dosing with Lilly’s Trulicity (dulaglutide) or guaranteed adherence with Intarcia’s ITCA 650 (implantable exenatide mini-pump).
  • We are very curious to see how the LEADER and EMPA-REG OUTCOME results will be judged relative to each other. Will GLP-1 agonists and SGLT-2 inhibitors (or the specific agents in each class that have demonstrated CV benefit) both be considered preferred second-line treatments for all patients at high CV risk? Will the recommendations be different depending on the specific type of CV risk (i.e., empagliflozin for heart failure and liraglutide for atherosclerosis)? The prospect of combination therapy with two drugs that reduce CV risk by different mechanisms is also an intriguing one, though one attendee during a Tuesday session on EMPA-REG OUTCOME raised the possibility that the two mechanisms could actually work against each other if liraglutide reduces ketone body production that is contributing to the benefit with empagliflozin.
  • Large-scale changes to the FDA’s 2008 CV Guidance appear increasingly unlikely now that two CVOTs have reported positive results. The consensus opinion has certainly changed from a year ago, when the streak of four completely neutral trials (SAVOR, EXAMINE, TECOS, and ELIXA) had raised questions about whether the value of these trials was worth the massive investment. Now that two trials have revealed important benefits that might otherwise have remained unknown, we have heard several speakers (including Dr. Darren McGuire and Dr. Steve Nissen at AACE) argue strongly that the field is getting its money’s worth from these studies. Even some previous opponents of the FDA Guidance have changed their opinions over the past year – for example, Dr. Silvio Inzucchi (Yale University, New Haven, CT) stated at EASD that he was prepared to completely revise his previous assessment of the requirements in light of the EMPA-REG OUTCOME results. At the same time, the FDA officially eliminated the Risk Evaluation and Mitigation Strategy for rosiglitazone last December, effectively declaring the main rationale for the 2008 Guidance to be invalid. We also continue to question whether an across-the-board CVOT requirement with the same guidelines for all diabetes drugs is the most effective tool to assess the risks and benefits of new products. We believe that a more nuanced approach, in which drugs with a signal for CV risk would be required to conduct a safety trial and those with potential for benefit would be required or incentivized to conduct a superiority trial, would offer the most value to the field.
  • An intriguing new “fuel energetics” hypothesis for the mechanism of benefit in EMPA-REG OUTCOME generated plenty of discussion at this year’s ADA. The thrust of this hypothesis, outlined in a paper published in Diabetes and a presentation by Dr. Ele Ferrannini (University of Pisa, Italy), is that the shift toward ketone body production with SGLT-2 inhibitors (which has been discussed primarily in the context of increased risk of ketoacidosis) might have cardioprotective effects. In his model, the increased availability of lipid substrates with SGLT-2 inhibitors (due to increased glucagon production and decreased insulin and glucose levels) leads the liver to produce more ketone bodies, which are then taken up by the heart and act as very efficient fuel sources. The increased hematocrit (higher ratio of oxygen-carrying red blood cells to total blood volume) seen with SGLT-2 inhibitors could also lead to more oxygen being delivered to the heart. That combination of more oxygen and more efficient energy utilization could improve the heart’s contractile ability and lessen the strain on a failing heart. A separate paper and presentation by Dr. Sunder Mudaliar (UCSD, San Diego, CA) suggested that a similar hypothesis could apply to the renal protective effects seen in the trial. The basic idea is that a shift by the kidneys toward metabolism of ketone bodies rather than oxygen could help ameliorate renal hypoxia and oxidative stress, which are increasingly being recognized as key contributors to the progression of chronic kidney disease. While these hypotheses do not preclude other previously proposed mechanisms of benefit, the level of attention they received throughout the conference suggests that they will be an important part of the discussion moving forward.
    • If this hypothesis is correct, we look for the field to weigh the beneficial long-term effects of increased ketogenesis on cardiovascular/renal outcomes against the short-term increased risk of DKA. The risk/benefit assessment will likely vary depending on the patient population. Based on current evidence, it seems likely that the benefits will clearly outweigh the risks for patients with longstanding type 2 diabetes and high CV risk, as the EMPA-REG OUTCOME results are most directly applicable to this population and demonstrated no increased risk of DKA. The calculus is somewhat less clear for the broader type 2 diabetes population, but it still seems likely that the benefits will outweigh the risks given that the rates of SGLT-2 inhibitor-associated DKA in type 2 diabetes appear to be low and associated with specific precipitating factors – see our coverage of last fall’s AACE/ACE meeting on the subject for more. The situation may be trickiest in type 1 diabetes, where the risk of DKA appears to be more marked and there is unlikely to be a long-term outcomes trial to evaluate potential cardiovascular and renal benefits. Of course, much more study is needed before making any definitive statements about these tradeoffs, but there is certainly potential for clinicians to face a bit of a paradox.
  • A hypothesis-generating mediation analysis of the EMPA-REG OUTCOME results suggested that changes in hematocrit levels (presumably due to a reduction in plasma volume) could partially account for the 38% risk reduction for cardiovascular death. The covariate mediation analysis examined a host of potential factors to see if they could account for the impressive effect on cardiovascular mortality. Potential mediators were related to glycemia (A1c, fasting plasma glucose [FPG]), vascular tone (systolic blood pressure, diastolic blood pressure, heart rate), lipids (HDL cholesterol, LDL cholesterol, triglycerides), renal factors (log urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate [eGFR]), adiposity (weight, BMI, waist circumference), volume status (hematocrit), or other (uric acid). A “change from baseline” analysis meant to determine a potential acute effect suggested that hematocrit levels and a decrease in plasma volume could explain nearly 52% of the overall effect of empagliflozin on cardiovascular death. An “updated mean” analysis meant to tease out chronic effects similarly found that hematocrit levels could account for 52% of the effect, while other volume-related factors such as hemoglobin and albumin levels could explain nearly 46% and 32% of the effect, respectively. While this interesting post-hoc analysis suggests a role for plasma volume in the cardioprotective benefit of empagliflozin, presenter Dr. Silvio Inzucchi (Yale University, New Haven, CT) emphasized that the analysis suggests that the plasma volume is only a partial mediator of the effect and other potential drivers (like ketone bodies) may not have been included in the analysis because they were not adequately measured at baseline and throughout the study
  • Additionally, we heard speakers use the growing pool of CVOT data in discussions on various safety signals, including heart failure and bone health. Specifically, Dr. Steven Marso (UT Southwestern, Dallas, TX) presented on the anti-glycemic therapies on heart failure risk, pulling from the CVOTs of DPP-4 and SGLT-2 inhibitors in efforts to draw conclusions on each drug class’s risk. Dr. John Buse (University of North Carolina, Chapel Hill, NC) also examined the effects of diabetes drugs on bone health, as he turned to CVOTs in GLP-1 agonists, DPP-4 inhibitors, and SGLT-2 inhibitors to identify the levels of risk. Notably, Dr. Buse supported the use of CVOT data over the meta-analysis of smaller studies for regulatory or clinical decisions. While the field’s conclusions on these safety signals remain limited, we would agree that the growing evidence base from CVOTs and their hard endpoints have helped contribute important insights on our available diabetes drugs, outside of only cardiovascular disease.
  • The fact that there are now two diabetes drugs with demonstrated renal protective effects is one of our most exciting and surprising conclusions from ADA 2016. Full renal outcomes results from EMPA-REG OUTCOME presented by Dr. Christoph Wanner and published in the NEJM demonstrated a significant 39% risk reduction for incident or worsening nephropathy with Lilly/BI’s Jardiance (empagliflozin) (HR = 0.61; 95% CI: 0.53-0.70; p<0.001). In addition, one of the most positive surprises from the LEADER results was the significant 22% improvement in renal outcomes (HR = 0.78; 95% CI: 0.67-0.92; p=0.003) with Novo Nordisk’s Victoza (liraglutide). These findings are truly profound given the current enormous unmet need for new therapies to treat chronic disease. We hope they might prompt both sponsors to consider conducting a dedicated chronic kidney disease trial for their products, comparable to Lilly/BI’s planned heart failure trials for Jardiance. We also wonder what the implications will be for ongoing and future trials of drugs being developed specifically for diabetic nephropathy – will those agents be required to demonstrate a benefit in addition to that provided by Victoza and/or Jardiance?
    • The FDA’s recent Drug Safety Communication about the risk of acute kidney injury with J&J’s Invokana (canagliflozin) and AZ’s Farxiga (dapagliflozin) could potentially complicate the discussion around the renal effects of SGLT-2 inhibitors. The warning was based on a search of the FDA Adverse Event Reporting System that found 101 confirmable cases of acute kidney injury with the two drugs between March 2013 and October 2015. Jardiance was not mentioned in the warning, and there was no signal of increased risk of acute kidney injury with Jardiance in EMPA-REG OUTCOME. This discrepancy suggests that there could be within-class differences in the effect of SGLT-2 inhibitors on the kidneys, which would be surprising given how homogenous the class is typically considered to be. Results from the ongoing outcomes trials for Invokana and Farxiga should help clarify this question; there could potentially be difficult tradeoffs for clinicians if those trials find both an increased risk of acute kidney injury and a reduced risk of long-term cardiovascular and/or renal risk with these drugs. It is too early to reach any definitive conclusions but we will be keeping a close eye on this area.

Updates on New and “New” Insulins

  • New rapid-acting insulin analogs stepped into the spotlight at ADA 2016, following several years in which basal insulins stole the show. Innovation in the rapid-acting insulin analog field has occurred at a somewhat slower pace compared to the basal insulin field that recently saw the US launches of next-generation options from Sanofi (Toujeo [U300 insulin glargine]) and Novo Nordisk (Tresiba [insulin degludec]). Like Toujeo and Tresiba, the next-generation rapid-acting insulin analogs seem to offer meaningful but incremental benefits over existing products but are not expected to be paradigm-shifting innovations. Many of the most notable rapid-acting insulins are variations on existing insulins, rather than entirely new molecules. The data we’ve seen thus far suggest that the new products offer significant but modest improvements in postprandial glucose control, are non-inferior or very modestly superior in terms of A1c reduction, and produce comparable or slightly improved hypoglycemia rates compared to current rapid-acting analogs. Perhaps most excitingly, it appears that the next-generation products may retain their efficacy with mealtime or even post-mealtime dosing, as opposed to the 15 minutes pre-mealtime dosing recommended with the current rapid-acting insulins. This potential for greater dosing flexibility should be very meaningful for patients, as it is more consistent with how many patients dose mealtime insulin in the “real world.” 
    • The most advanced next-generation insulin analog is Novo Nordisk’s faster-acting insulin aspart, which presented full phase 3 Onset 1, Onset 2, and Onset 3 data at ADA 2016. Onset 3 found that intensification to a basal-bolus regimen with faster-acting aspart in patients with type 2 diabetes resulted in a statistically superior mean A1c reduction of 0.94% (baseline A1c=7.9%; p<0.0001) compared to continued treatment with basal insulin alone. In a head-to-head comparison, Onset 2 found that faster-acting insulin aspart administration in patients with type 2 diabetes produced non-inferior A1c reductions and significant improvements in postprandial control compared to Novo Nordisk’s NovoLog (insulin aspart). A1c dropped from 8% to 6.6% with faster aspart and from 7.9% to 6.6% with NovoLog. Faster aspart produced a significant 10.6 mg/dl improvement in one-hour postprandial glucose (p=0.0198) and a numerical but not significant improvement of 6.6 mg/dl in two-hour postprandial glucose. In patients with type 1 diabetes, Onset 1 found a modest but statistically significant improvement in A1c with Faster aspart (~0.2% vs. standard aspart). Notably, in addition to the modest A1c benefits, two-hour postprandial blood glucose levels were superior with Faster aspart than regular aspart (by ~12 mg/dl), and, in terms of A1c reduction, post-meal Faster aspart administration was non-inferior compared to standard pre-meal administration of current insulin aspart.
    • Adocia offered a glimpse at phase 1b meal study results for its Lilly-partnered BioChaperone Lispro and its BioChaperone Combo (insulin glargine/insulin lispro). Both demonstrated improvements in one-hour and two-hour postprandial glucose compared to Lilly’s Humalog (insulin lispro). BioChaperone Lispro demonstrated a mean glucose difference of 42 mg/dl one hour post-meal and a mean difference of 27 mg/dl two hours post-meal. BioChaperone Combo reduced postprandial glucose excursions by 24 mg/dl at one hour compared to Humalog. BioChaperone Combo produced numerically fewer hypoglycemic episodes compared to Humalog and was associated with more time in range. Hypoglycemia was comparable between BioChaperone Lispro and Humalog.
    • MannKind’s Afrezza (inhaled insulin) also demonstrated improvements compared to Lilly’s Humalog (insulin lispro) in terms of a faster onset and shorter duration of action. Afrezza is one of the few new rapid-acting insulins that arguably represents a true, groundbreaking innovation, given its unique delivery method. Unfortunately, burdensome prescribing requirements and potential safety concerns related to the novelty of the product have led to sluggish uptake for Afrezza in the year and a half since its launch. The product has been further plagued by Sanofi’s decision to terminate its licensing agreement with MannKind for Afrezza and MannKind’s CEO woes in the early half of this year. That said, many patients on Afrezza extoll its benefits and we believe that the hurdles presented by the prescribing requirements and other concerns can be mitigated. MannKind appears committed to keeping Afrezza available and announced during ADA that it intends to partner with JDRF to investigate Afrezza for a pediatric population.
  • There’s new and then there’s “new” insulins – we saw results from phase 3 trials of Merck/Samsung’s biosimilar insulin glargine MK-1293 and Sanofi’s biosimilar insulin lispro SAR342434 for the first time. In an oral and a poster presentation, MK-1293 demonstrated similar efficacy and safety to Sanofi’s Lantus (insulin glargine) in both patients with type 1 and type 2 diabetes over 24 weeks. Merck recently shared that it has filed MK-1293 in Europe and we presume a US filing will follow soon. MK-1293 will likely be the second biosimilar insulin glargine to market, after Lilly/BI’s Basaglar/Abasaglar that has already launched in multiple ex-US markets and will launch in the US in December 2016. Biocon/Mylan also have a biosimilar insulin glargine in the works that they hope to file in the US and EU in the next few months. On the rapid-acting insulin side, Sanofi’s biosimilar insulin lispro SAR342434 demonstrated similar effects on A1c and postprandial glucose excursions with a similar safety profile as Lilly’s Humalog (insulin lispro) in combination with Sanofi’s Lantus (insulin glargine) in patients with type 1 diabetes.
  • The basal insulin front was comparatively quiet at this year’s ADA. Most notably, in a series of late-breaking posters, we saw full SWITCH 1 and SWITCH 2 results demonstrating a hypoglycemia benefit for Novo Nordisk’s Tresiba (insulin degludec) over Sanofi’s Lantus (insulin glargine). Novo Nordisk plans to submit this data to the FDA soon, in the hopes that it will support some sort of language surrounding reduced risk of hypoglycemia in Tresiba’s label.

GLP-1 Agonists

  • Data presented at this year’s ADA illustrated a number of exciting potential future directions for the GLP-1 agonist class – the question is whether there will be a market for all of them. We expect that the demonstration of a cardioprotective effect for Novo Nordisk’s Victoza (liraglutide) in LEADER will likely spur growth of the entire class and provide some disproportionate benefit for Victoza. Over the long term, it is possible that some clinicians will use CVOT results as a key differentiating factor when choosing among different agents in the class, at least for their higher-risk patients. This will likely depend in large part on the consistency of results from future GLP-1 agonist CVOTs. Combinations with basal insulin represent another exciting advance for the GLP-1 agonist class; at this year’s ADA, we saw full phase 3 results for Sanofi’s iGlarLixi (lixisenatide/insulin glargine) combination, which is expected to receive US and EU regulatory decisions this year. Novo Nordisk’s Xultophy (insulin degludec/liraglutide) is also on track for a US decision this year and is already available in Europe. Impressive new data for Novo Nordisk’s semaglutide (in type 2 diabetes and obesity) reinforced its potential as a versatile, possibly best-in-class molecule, while results from the FREEDOM-2 trial of Intarcia’s ITCA 650 (implantable exenatide mini-pump) underscored the advantages of an agent that offers guaranteed adherence. We are excited about the potential for all of these products to help expand usage of the GLP-1 agonist class in both type 2 diabetes and obesity, which we have long felt is underutilized. It is not clear at this point whether all the options can find their own niche within the class or whether one or two will emerge as the clear preferred options.

SGLT-2 Inhibitors in Type 1 Diabetes

  • A session on novel therapeutics for type 1 diabetes underscored the continued interest in the use of SGLT-2 inhibitors in type 1 diabetes. In particular, we saw glycemic variability data from J&J’s phase 2 trial of Invokana (canagliflozin) in patients with type 1 diabetes. In the CGM substudy, MAGE (a measure of glucose variability) was 17 mg/dl improved over placebo with canagliflozin 100 mg and 38 mg/dl improved over placebo with canagliflozin 300 mg. As assessed by CGM, time in range (70-180 mg/dl) improved by roughly 14% placebo-adjusted, driven entirely by a reduction in hyperglycemia, with no major increase in hypoglycemia. This was some of the most compelling data we’ve seen on SGLT-2 inhibitors’ benefits on time-in-range and glycemic variability to date. Similarly, another presentation demonstrated markedly less chaotic CGM tracings with the addition of dapagliflozin (AZ’s Farxiga) to a regimen of GLP-1 agonist liraglutide and insulin in patients with type 1 diabetes.
  • A major theme at the annual TCOYD/The diaTribe Foundation forum was the need for better therapies for type 1 diabetes. In particular, Dr. Jeremy Pettus (UCSD, CA) spoke movingly about his own challenges managing his blood sugars while at ADA, despite the fact that he is well-educated, has health insurance, and has access to all of the best diabetes management tools. Regarding SGLT-2 inhibitors specifically, Dr. Pettus stated, “When I have a patient with type 1 diabetes who takes the drug, they say, ‘My life is better. Maybe I should’ve bolused four units and only bolused for three, and the SGLT-2 inhibitor picks up the slack. It takes away some of the chaos.’ That’s the real value of some of these medications.”

The Future of Type 2 Diabetes Drugs

  • It is becoming increasingly clear that future type 2 diabetes drugs will need to offer additional benefits beyond glucose lowering to be successful. We can even imagine a future in which new type 2 diabetes drugs will have to demonstrate a positive effect on cardiovascular and/or renal outcomes in order to succeed now that two agents in different classes have already done so. We are also encouraged to see interest in evaluating such benefits with older generic drugs like pioglitazone in the IRIS trial and metformin in the planned GLINT trial. Demonstrating benefit in additional indications like obesity, type 1 diabetes, and NASH is potentially another way for type 2 diabetes drug manufacturers to differentiate their products. We saw results of several such efforts at this year’s ADA, including data on semaglutide, exenatide/dapagliflozin, and canagliflozin/phentermine in obesity and data on canagliflozin and dapagliflozin in type 1 diabetes. New drug classes like the GLP-1/glucagon dual agonist class promise benefits on weight and other cardiovascular risk factors in addition to reductions in glucose. The bottom line is that we see little room in the current landscape for new drugs that offer nothing more than incremental glucose-lowering benefits, or those (other than insulin) that carry a risk of weight gain or hypoglycemia.
  • We saw a substantial amount of promising new data on GLP-1/glucagon dual agonists in type 2 diabetes and obesity at ADA 2016. Most notably, we saw expanded phase 1 data for Sanofi’s SAR425899, demonstrating significant reductions in weight, “clear” improvements in A1c and fasting plasma glucose, and a similar safety/tolerability profile as GLP-1 single agonists. A phase 1, randomized, blinded study of AstraZeneca’s MEDI0382 GLP-1/glucagon receptor dual agonist found that the candidate was well tolerated overall, with reduced postprandial glucose levels and daily food intake at doses of 5, 10, 30, 100, 150, and 300 micrograms. Further, a preclinical study demonstrated that a single subcutaneous dose of MEDI0382 reduced fasting glucose levels by 42%, glucose AUC by 53%, and food intake by 18% in wild type but not GLP-1 receptor KO mice. We were also interested in a poster presentation of new data on the cholesterol-lowering effect of Janssen/Hanmi’s phase 1 dual agonist HM12525A. As a class, GLP-1/glucagon dual agonists have generated some of the most buzz and industry investment out of any classes in the early-stage diabetes drug pipeline. Much of the recent Keystone Symposia on Novel Therapeutics for Diabetes and Obesity focused on this class and other polyagonists involving GLP-1 agonists. The promise of a winning combination of glucose-lowering, weight reduction, and even potentially cardioprotection has led several pharmaceutical companies to add these candidates to their early-stage pipelines – see our competitive landscape for more.
  • We heard several key diabetes clinical care experts speak to the importance of treating the right patients with the right medications at the right time. During the 10th annual TCOYD/The diaTribe Foundation Diabetes Forum, Drs. Steve Edelman (UCSD, San Diego, CA), Rury Holman (University of Oxford, UK), Anne Peters (USC, Los Angeles, CA), Jeremy Pettus (UCSD, San Diego, CA), and John Anderson (The Frist Clinic, Nashville, TN) spoke eloquently on the need to improve access and adherence to maximize the efficacy of currently available diabetes drugs. As Dr. Edelman put it, “One of the biggest challenges is getting the right drug to the right person. The second big part is getting people to be adherent and persistent and make diabetes higher on their priority list.” Dr. Holman suggested that part of the problem is that clinicians don’t have all of the information they need to offer truly personalized, tailored therapeutic options to their patients. He suggested enriching the clinical trial process so that trials yield more information useful for personalized therapeutic recommendations. During the ADA meeting itself, the highly respected Dr. Judith Fradkin offered an update on the NIH’s plans for rolling out its Precision Medicine Initiative (PMI) Cohort Program and noted that diabetes will be one of the most highly represented conditions in the cohort, with an estimated 135,658 cases at baseline.

Additional Topics

Obesity

  • There was no major new obesity data this year and we saw very little representation from branded obesity pharmacotherapies this year. Aside from Novo Nordisk’s relatively minimalist booth on Saxenda (liraglutide 3.0 mg), no other obesity companies were represented on the exhibit hall floor. In addition, there was only one obesity-focused corporate symposium (supported by Novo Nordisk) on the agenda. The level of engagement from obesity drug companies has been on a sharp decline over recent ADA meetings, as 2014 featured large, bustling booths from Belviq (lorcaserin) and Qsymia (phentermine/topiramate extended-release) and 2015 had Saxenda, but only a small pop-up booth for Belviq. We are not surprised by this drop-off in marketing, given the recent challenges in the obesity drug market, although we remain hopeful that Novo Nordisk’s wealth of expertise and resources will push for greater awareness and education around obesity to gradually boost the market.
  • Notably, we saw a significant amount of promising new data on type 2 diabetes drugs in obesity management. Combination therapies, SGLT-2 inhibitors, and GLP-1 agonists were the stars of this show, headlined by phase 2 results of combination therapy with AZ’s Farxiga (dapagliflozin) and Bydureon (exenatide once weekly), which demonstrated significant ~4 kg weight loss vs. placebo in patients with obesity but not diabetes. In addition, co-administration of J&J’s Invokana (canagliflozin) and phentermine showed significantly greater weight loss vs. placebo in adults with overweight and obesity. On the GLP-1 agonist front, we saw positive results on reductions in energy intake and appetite with once-weekly GLP-1 agonist semaglutide in obesity as well as significant weight benefits from the FREEDOM-2 study of Intarcia’s ITCA 650 (implantable exenatide mini-pump) compared to Merck’s Januvia (sitagliptin) in people with type 2 diabetes. While data from currently available obesity drugs and new targets remained on the quieter side at this meeting, we were glad to see many diabetes drugs turn to this area and given the complexity of obesity, we are also pleased to see more focus on combination therapies. With the diabetes drug space having comparatively greater resources, a larger evidence pool, and established efficacy and safety, we hope to see greater movement from this market into obesity, as the disease remains a significant unmet need.
  • On the basic science front, the brain and microbiome seemed to be the main focuses within obesity research. The agenda featured several intriguing oral presentations on deep transcranial magnetic stimulation, AgRP neuronal activation, and a leptin-responsive brainstem circuit within weight management. As we’ve seen recently, GLP-1 agonists have been heavily studied in this area, as highlighted by an oral presentation examining the regulation of energy balance and glucose homeostasis via the ventromedial hypothalamic GLP-1 receptor. See our recent coverage from the European Obesity Summit for greater discussion on how the brain plays a significant role within energy balance and weight management. Additionally, we heard a decent number of presentations on how the microbiome ties into obesity, with discussions on the interaction between “diabesity” genes and the gut as well as a full symposium on how the microbiome is involved in metabolic risk from pregnancy through the life cycle. While these presentations highlight promising movement, we are increasingly aware of the complexity of both obesity and the corresponding therapies. Of the brain and microbiome, we see the brain and its neural circuitry as a more near-term target area for obesity, although we ultimately hope to see multi-targeted therapies combining these many different approaches.
  • In addition, the role of adipose tissue and its link to obesity and type 2 diabetes risk was in the spotlight at this year’s prestigious Banting lecture, delivered by Dr. Barbara Kahn (Harvard Medical School, Boston, MA). This area of research has certainly been growing rapidly within recent years, as Dr. Kahn noted our evolving understanding of adipocyte tissue as a storage depot to its role in secreting molecules. Dr. Kahn illustrated the complexity and potential of studying adipose tissue, as she touched on how the molecules, lipid levels, and biochemical changes involved in adipose tissue can guide our search for novel drug targets in obesity and type 2 diabetes. We especially enjoyed hearing how these approaches can be used to identify our most at-risk patients and help personalize prevention and treatment efforts. For more on our growing understanding of adipose tissue, also check out the prestigious Minkowski award lecture delivered by Dr. Matthias Bluher (University of Leipzig, Germany) at this past EASD.

The Limitations of A1c

  • ADA 2016 underscored the limitations of using A1c alone to titrate therapy: a mean glucose can range 80 mg/dl for a given A1c (8.0% =120 mg/dl or 200 mg/dl)! This was not groundbreaking by any means – we’ve long argued that A1c in isolation is not the best metric for glycemic control – but this meeting’s commentary went further, stressing that A1c is not simply inadequate, but can be dangerously misleading and clinically ignorant. Dr. Rich Bergenstal drove this point home during his presentation on racial differences in the relationship between mean glucose and A1c, sharing striking data that mean glucose can range 80 mg/dl for a given A1c – e.g., an estimated A1c of 8.0% could correspond to a mean glucose of 120 mg/dl or 200 mg/dl. That’s some serious dispersion between different individuals! Noted UW’s Dr. Irl Hirsch, “the paradigm by which we treat type 2 diabetes is wrong and we’ve been doing it wrong for the past 30 years” [e.g., treating a patient with mean glucose of 120 mg/dl and 200 mg/dl the same because the A1c reads 8.0%]. He and Dr. Bergenstal did acknowledge that A1c is an established measure of the risk of developing complications but highlighted that we would be wise to shift the existing paradigm and begin personalizing diabetes and treatment decisions based on glucose values. Especially in this era of pharmacotherapies and technologies that may improve quality of A1c – shaving off highs and lows, but not impacting A1c substantially – the commentary underscored the need for more widespread glucose monitoring and tools that capture “higher quality” A1cs. A big question, of course, is how to validate such a paradigm shift in the eyes of payers and the FDA. Will anyone fund a modern-day DCCT to validate the importance of time-in-range and reducing hypoglycemia and variability?
  • Abbott’s IMPACT study also highlighted just how much A1c completely obscures dangerous hypoglycemia. As a reminder, both groups in the study saw a non-significant, marginal 0.15% increase in A1c (6.7% to 6.9%), though the “quality of A1c” improved markedly in the FreeStyle Libre group – 74 fewer minutes per day <70 mg/dl (a 38% reduction), and 33 fewer minutes per day <45 mg/dl (a 60% reduction in time spent at a highly dangerous level). Meanwhile, the control group was still spending three hours per day in hypoglycemia with an A1c 6.9%! Do payers appreciate the gravity of that change? How could that change impact short and long-term costs? The results underscored that A1c and average glucose is not just an incomplete metric, but that glucose control for most patients is defined in terms of MANY other variables: hypoglycemia, hyperglycemia, time-in-range, variability, quality of life, fear, hospitalizations, etc.

Focus on the Cost of Diabetes and Inequity

  • The rising cost of diabetes care was heavily discussed at this year’s meeting, and we noticed particular attention to inequities among various patient populations. We were reminded throughout the conference that the US spends dramatically more on diabetes than any other country, with costs totaling $245 billion. As outlined by Dr. Neda Laiteerapong (University of Chicago, IL), the principle driver of this trend is rising medical costs, particularly for insulin expenditures. However, she also brought up the bright spot that overall rising diabetes costs may partially reflect the greater longevity and thus greater utilization of healthcare services of people with diabetes. On the same note, a presentation by Dr. Xilin Zhou (CDC, Atlanta, GA) highlighted tremendous growth in spending on anti-diabetes drugs in the US, with alarming statistics of a 12-fold increase in under two decades. Additionally, we heard discussions on the differences in out-of-pocket expenses (OOPEs) among patient populations. Specifically, Dr. Lina Merjaneh (Seattle Children’s Hospital, WA) highlighted that young adults with type 1 diabetes pay approximately six times more than those with type 2 diabetes. On a more hopeful note, Dr. David Howard (University of Nevada, Reno, NV) explained that OOPEs for vulnerable populations are actually on a downward trend, though this decreased spending may merely reflect the necessity of opting for cheaper, generic drugs. We were glad to see this more nuanced examination of costs at this year’s ADA, as this can help develop a more targeted strategy to tackle the unsustainable trends we’re seeing.
  • In addition, we were pleased to witness greater dialogue on how to treat diabetes in different populations. Drs. Richard Bergenstal (International Diabetes Center, St. Louis Park, MN) and Roy Beck (Jaeb Center for Health Research, Tampa, FL) discussed new findings to support racial differences in the relationship between mean glucose and A1c – an important topic, given how much we depend on A1c in our treatment approaches (see below). In addition, health equity researcher Dr. Nadia Islam (New York University, New York, NY) criticized the fact that the >30 Asian-American ethnic groups in the US are grouped uniformly as “Asian” in analyses of diabetes prevalence and management, despite the fact that these groups can be highly heterogeneous. Dr. Yvette Roubideaux (Washington State University, Spokane, WA) described a similar phenomenon in the American Indian and Alaska native communities, highlighting that the 566 federally-recognized tribes in the US requires a comparably diverse range of approaches to diabetes education and treatment. We also heard the first full results of the COSMID (Comparison of Surgery vs. Medicines for Indian Diabetes) trial, which was the first-ever RCT of surgical vs. non-surgical care for type 2 diabetes in South Asian patients. We hope that these findings can serve as an impetus for policymakers and diabetes researchers to be more attentive to the heterogeneity of the US patient population, with the development of more evidence-based guidelines on how to personalize treatment by this dimension.

What Is ADA’s Role?

  • During a compelling presidential address, ADA President Dr. Desmond Schatz (University of Florida, Gainesville, FL) issued a call to urgency, emphasizing the ADA’s focus on prevention through raising awareness of the scope and cost of diabetes. He underscored the need to bring diabetes to 212 degrees – “the boiling point of water where it erupts with urgency” – to transform the “invisible disease” to a highly visible crisis. Dr. Schatz detailed the many ways in which diabetes is invisible, hidden, and ignored: people hide the reality of living with diabetes from their friends and families, healthcare providers are largely absent in the daily management of the disease, and patients with type 2 diabetes often choose to be invisible due to stigma and feelings of failure. In addition, Dr. Schatz emphasized that although diabetes is far more prevalent, NIH funding for the disease pales in comparison to that for HIV/AIDS and cancer – an incredible $35 per patient for diabetes vs. $2,500 for HIV/AIDS and $372 for cancer, another byproduct of its invisibility. To that end, he advocated for taking a page out of the book of successful movements such as those for HIV/AIDS and even the recent Zika epidemic (which recently received a $1.1 billion compromise bill), where people have rallied around a strategic vision and inspired a “fiery sense of urgency”. We found Dr. Schatz’s presentation incredibly compelling, and are pleased to see the ADA call for immediacy and action in the diabetes world; perhaps through mimicking successful health advocacy movements, we can collectively “turn up the heat” and inspire the sense of urgency required to confront the diabetes epidemic. 
  • The ADA drew significant attention to its Pathway to Stop Diabetes program this year with a dedicated symposium, poster session, and oral presentation session. The closed Pathway symposium on the first day of the conference featured presentations from the latest round of grant recipients, while the oral presentation and poster sessions featured presentations from the 2014 and 2015 awardees. We have been impressed with the Pathway initiative since its inception in 2014; the program awards grants of up to $1.6 million over five to seven years to young diabetes researchers working on innovative projects focused on everything from neuronal regulation of feeding behavior to impaired wound healing. The program is supported by several heavy hitters in the diabetes industry, including Sanofi, Novo Nordisk, Lilly, and AstraZeneca, and we imagine this could make it easier for the researchers to eventually translate their findings into novel therapies. We think this program can play a major role in shaping the next generation of KOLs in diabetes. We also hope it can promote a more diverse group of leaders compared to the current crop (in a sign of some progress, 35% of the Pathway grant recipients thus far are women compared to 26% of the mentors).
    • Many of the featured presentations focused on the themes of the role of the microbiome, neural regulation of hunger, and the promise of genomic approaches to understand the biochemical signatures and gene regulatory networks underlying diabetes and obesity.

Precision Medicine Initiative

  • We were glad to see the progress on President Obama’s Precision Medicine Initiative (PMI) continue at ADA 2016. Most notably, the highly respected Dr. Judith Fradkin (NIDDK, Bethesda, MD) presented the NIH’s plans for rolling out the PMI Cohort Program, sharing ambitious benchmarks slated for completion by the end of 2016. The NIH aims to have 79,000 participants fully consented and enrolled in the cohort, with biospecimens from at least 25,000 participants; the Institute expects to accomplish its final goal of enrolling one million participants by the end of 2019. Further, the NIH plans to launch a direct volunteer program and partnerships with five to seven major healthcare provider organizations to facilitate participant recruitment, and also expects that eight to ten studies using the cohort data will be underway by December 2016. It is very encouraging to see the government’s commitment to developing a strategic plan for the PMI implementation – we hope to see the momentum continue and ultimately bring more accurate diagnoses, improved disease prevention strategies, and better treatment selection for people with diabetes and other chronic diseases.
  • Meanwhile, Dr. Jose Florez (Massachusetts General Hospital, Boston, MA) expressed concern that the field might not yet be ready to apply PMI findings in diabetes as there is still so little known about the genetic underpinnings of the disease. To that end, he highlighted the Accelerating Medicines Partnership Type 2 Diabetes Knowledge Portal, which will enable scientific advances through improved data collection, sharing, and analytics.

Exhibit Hall

  • The ADA 2016 exhibit hall seemed to have less fanfare, attendance, and excitement than we’ve seen in the past. We took particular note of a couple absentees from the hall – for a start, Roche and obesity drug companies (aside from Novo Nordisk) – which we assume reflect both the challenging SMBG and obesity environments in the US and perhaps a different perception on the return on investment from exhibit hall booths. In the modern era of digital and social media marketing, an argument could be made that the ROI of exhibit hall booths is a bit hard to measure. Our coverage includes the following companies and organizations: Abbott, Alere, Amgen, Ascensia, AstraZeneca, Becton Dickinson, BI/Lilly, Dexcom, Glooko, GSK, InSpark, Insulet, Intarcia, J&J/Animas, J&J/LifeScan, J&J/Janssen, LabStyle, Lilly, Mannkind, Medtronic, Merck, Novo Nordisk, Novo Nordisk (Saxenda), Sanofi, Sanofi-Regeneron, Takeda, Tandem, Valeant, and Valeritas.

Historical Visits in the New Orleans Area

  • In between our diabetes learnings, our team took the time to visit two of the New Orleans area’s most important and informative historical sites: (i) the Whitney Plantation and (ii) the National WWII Museum. 
    • We toured the Whitney Plantation, a former sugarcane plantation and the only museum in Louisiana to take a direct focus on slavery. The Whitney Plantation tour featured powerful storytelling drawn from the narratives of men and women who had been emancipated from slavery as children and young adults. After exploring the unsettling scenery of an old slave jail, restored slave cabins, and a church built by former slaves, our team agreed that the Whitney taught us more about the hateful atrocities of slavery than we had ever collectively learned in school. In connecting the dots back to our work at Close Concerns, we reflected on the racial disparities we continue to see in diseases like diabetes and obesity. This experience has thus pushed us to more deeply consider how slavery and its successor systems have contributed to the massive inequities that we continue to see in healthcare access and quality of care today
    • In addition, our team visited the National WWII Museum, which builds on the individual narratives of the American military in World War II. The museum was built as a testament to the 16 million veterans who served in World War II, of whom only ~850,000 are still alive. Visitors are given dog tag keycards that they can scan at different points during their trip through the museum and learn the real-life stories of Americans throughout the world. Mixed in with the panels on the overall history of the war are pieces dedicated to the wartime experiences of people like Slaughter-House Five author Kurt Vonnegut, plus the many men and women whose names are otherwise lost to history. As we returned to the world of diabetes, we at Close Concerns reflected upon the salient connection between the present diabetes epidemic and the history we learned at the National WWII Museum: the US Department of Veterans Affairs reports that nearly a quarter of all veterans have diabetes. While the reason for this disproportionate incidence of diabetes remains unclear, hypotheses include the veteran population’s overall lower incomes, reduced access to healthy food, and higher rates of obesity and war-related exposure to environmental toxins.

GLP-1 Agonists

Symposium: Results of the Liraglutide Effect and Action in Diabetes – Evaluation of Cardiovascular Outcome Results (LEADER) Trial

Introduction, Study Rationale, and Design

John Buse, MD, PhD (University of North Carolina, Chapel Hill, NC)

Dr. John Buse (UNC, Chapel Hill, NC) kicked off the session with an introduction to the background and design of the LEADER trial. He acknowledged the enormous scope of the study and the people who made it possible with an impressive slide reviewing the key numbers for the trial: LEADER enrolled 9,340 patients in 32 countries across 410 sites over five years. In total, an astounding 11,000 people worked on the trial to collect 27.6 million data points over 13,500+ monitoring visits, resulting in information on almost 30,000 patient-years of exposure to liraglutide. LEADER was a double-blind, randomized, placebo-controlled, time- and event-driven trial: participants were treated for at least 3.5 years and no more than 5 years and the trial was to accumulate at least 611 events included in the primary endpoint (CV death, non-fatal MI, and non-fatal stroke). Key secondary outcomes included an expanded composite endpoint of CV death, non-fatal MI, non-fatal stroke, coronary revascularization, unstable angina pectoris requiring hospitalization, and hospitalization for heart failure. All-cause death and each individual component of the expanded CV composite were considered as secondary endpoints as well. Participants had type 2 diabetes with an A1c ≥7% and fell into one of two high cardiovascular risk categories: (i) at least 50 years old with established CVD or chronic renal failure or (ii) at least 60 years old with risk factors for CVD. Participants could be diabetes drug-naïve, on oral diabetes medications, or on basal or premix insulin. Patients on GLP-1 agonists, DPP-4 inhibitors, pramlintide, or rapid-acting insulin were excluded from the trial, as were those with type 1 diabetes or a familial or personal history of multiple endocrine neoplasia type 2 (MEN-2) or medullary thyroid cancer (MTC). Participants were treated according to standard of care guidelines with target A1c ≤7%, blood pressure 130/80 mmHg, and LDL cholesterol <100 mg/dl (<70 mg/dl in patients with previous CV events). Statins were recommended for all patients and aspirin or clopidogrel were recommended for patients with prior CV events. Events were adjudicated by an external committee made up of subcommittees each focused on cardiovascular, microvascular, pancreatitis-related, or neoplasm-related events.

Study Population

Neil Poulter, FMedSci (Imperial College London, London, UK)

Dr. Neil Poulter reviewed the characteristics of the LEADER study population, emphasizing that this was truly a global effort (32 countries, 30% of participants from North America, 35% from Europe, 8% from Asia, and 27% from the rest of the world). He also highlighted the trial’s very impressive retention rate: 97% of participants in both groups completed the trial and there were only 29 dropouts whose vital status was unknown at the end of the study. The study population was 64-65% male, with an average age of 64 and an average diabetes duration of 13 years, which Dr. Poulter noted is significantly longer than in most diabetes trials. Baseline A1c was fairly high at 8.7%, likely due to the lack of an upper A1c limit in the entry criteria. Baseline BMI was 32.5 kg/m2, baseline weight was 92 kg (~203 lbs), baseline blood pressure was fairly well controlled at 140/77 mmHg, and 18% of participants had heart failure at baseline. The liraglutide and placebo groups were well matched for all baseline characteristics. Over 80% of participants fell into the higher-risk group of patients ≥50 with existing CVD or CKD, and many had more than one qualifying condition. Consistent with this high level of risk, over 90% of patients were on antihypertensive therapy, 40% on diuretics, 75% on lipid-lowering medications (which Dr. Poulter described as suboptimal), and just under 70% on platelet inhibitors. Metformin was by far the most commonly used diabetes medication (used by approximately 75% of participants), followed by sulfonylureas at 50% and insulin at 45%. Dr. Poulter also highlighted the impressive treatment exposure in the trial, with a median exposure time of just over 3.5 years and patients spending an average of 83%-84% of the time on study drug.

Clinical and Metabolic Outcomes

Bernard Zinman, MD (Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada)

Dr. Bernard Zinman (University of Toronto, Canada) presented the key clinical and metabolic outcomes from the study. At three years post-randomization (a pre-specified time point), mean A1c in the liraglutide-treated group was 0.4% lower than in the placebo-treated group (p<0.001), despite the instructions to treat to a target A1c of 7% in both groups.  The gap in A1c diminished throughout the trial, largely due to an intensification of other agents in the placebo group. The proportion of patients on metformin, sulfonylureas, alpha-glucosidase inhibitors, TZDs, glinides, and insulin was fairly evenly matched between the two groups at the start of the trial, but more participants in the placebo group initiated treatment with these classes (particularly insulin and sulfonylureas) throughout the trial. Other clinical and metabolic outcomes of interest include 2.3 kg weight loss with liraglutide compared to placebo at three years (p<0.001), a 1.2 mmHg decrease in systolic blood pressure (p<0.001), a 0.6 mmHg increase in diastolic blood pressure (p=0.004), a 3 beats/min increase in heart rate (p<0.001), a 1.6 mg/dl decrease in LDL cholesterol (p=0.02), and a non-significant 0.3 mg/dl increase in HDL cholesterol (p=0.07). Dr. Zinman generally characterized these outcomes as expected effects associated with liraglutide and suggested that the increase in diastolic blood pressure and decrease in LDL cholesterol were not clinically significant. During the trial, a greater proportion of participants in the placebo group initiated new cardiovascular medications such as antihypertensive therapies, diuretics, lipid-lowering drugs, platelet aggregation inhibitors, or other anti-thrombotic medications. The LEADER study also investigated health-related quality of life measures, as measured by the EQ-5D index score (which assesses mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and the EQ-5D VAS score (a visual scale of health state from 0 to 100 representing worst and best health, respectively). Based on the index score, both liraglutide and placebo reduced participants’ quality of life, but liraglutide offered a 0.018 index score improvement over placebo (p=0.034). Liraglutide also offered a 1.3 point advantage on the VAS score (p=0.03). We were extremely pleased to see quality of life measures included in the study and hope that this kind of patient-centered metric could help encourage greater coverage from payers.

Cardiovascular Outcomes

Steven Marso, MD (UT Southwestern, Dallas, TX)

Interrupted multiple times by applause, Dr. Steven Marso presented the primary results from the LEADER trial. He emphasized the consistency of the effect for all the outcomes measured, noting that every single endpoint had a point estimate <1 that fell within a narrow range from 0.6-0.98. Taken together, these results fit the pattern that most in the field had predicted any positive CVOTs for diabetes drugs would show: risk reduction for multiple CV outcomes that appeared gradually and increased over time. This is in marked contrast with the EMPA-REG OUTCOME results for Lilly/BI’s Jardiance (empagliflozin), which demonstrated an immediate benefit for CV death and hospitalization for heart failure and little to no signal of benefit for other endpoints. As several speakers noted, the LEADER results appear more likely to be mediated through a reduction in atherosclerosis, whether that is due to indirect effects (reductions in A1c, weight, blood pressure, etc.) or direct effects on the heart or blood vessels.

  • Primary outcome: The hazard ratio for the primary outcome of three-point MACE (non-fatal MI, non-fatal stroke, and CV death) was 0.87 (95% CI: 0.78-0.97; p<0.001 for non-inferiority; p=0.01 for superiority), translating to a significant 13% risk reduction. Dr. Marso noted that the event rate (3.7 events/100 patient-years) was two-fold higher than projected, perhaps due to the high percentage of participants with existing CVD. The magnitude of the effect was consistent and robust in a number of sensitivity analyses, with the point estimate ranging from 0.82-0.87 and the upper bound of the 95% confidence interval consistently <1.
  • Individual components: While all three components of the primary endpoint contributed to the benefit, the most robust effect was a 22% risk reduction for CV death (HR = 0.78; 95% CI: 0.66-0.93; p=0.007; 497 events). The Kaplan-Meier curves for the two groups began to separate 12-18 months into the trial and continued to diverge until the end of treatment. The results for non-fatal MI and non-fatal stroke trended in the right direction but were not statistically significant. The hazard ratio for non-fatal MI was 0.88 (95% CI: 0.75-1.03; p=0.11, 598 events) and the hazard ratio for non-fatal stroke was 0.89 (95% CI: 0.71-1.11; p=0.30; 336 events). Dr. Marso pointed out that the shape of the curves for non-fatal MI followed the same pattern as those for CV death and for the primary endpoint – initial separation between 12 and 18 months and continued divergence over the course of the trial – perhaps suggesting that the risk reduction might have become statistically significant over a longer time period.
  • Subgroup analyses: There was no significant heterogeneity of the effect on the primary endpoint in subgroups divided by sex, age, region, race, ethnicity, BMI, A1c, diabetes duration, heart failure status, or anti-diabetic therapy. The two subgroups with a p-value for interaction <0.05 (with the caveat that the analyses did not control for multiplicity of testing) were CVD status and renal function. The point estimate for the group with established CVD was 0.83, while the point estimate for the group with CV risk factors was 1.2. Dr. Marso attributed this to the fact that the vast majority of trial participants fell into the first category, which had a much higher event rate; the lower-risk group most likely did not accumulate enough events to show a benefit. By renal function, the point estimate for patients with an eGFR <60 ml/min/1.73 m2 was 0.69 while the point estimate for patients with an eGFR >60 was 0.94.
  • Key secondary outcome: Results for an expanded MACE endpoint (including coronary revascularization and hospitalization for heart failure or unstable angina in addition to the primary endpoint) demonstrated a significant 12% risk reduction (HR = 0.88; 95% CI: 0.81-0.96; p=0.005).
  • All-cause mortality: The liraglutide group experienced a significant 15% risk reduction in all-cause mortality (HR = 0.85; 95% CI: 0.74-0.97; p=0.02), accounted for by the significant reduction in CV death and comparable rates of death from non-CV causes. Dr. Marso noted that these curves also separated after 12-18 months (much later than in EMPA-REG OUTCOME) and continued to diverge throughout the trial.
  • Heart failure: Results for the much-watched endpoint of hospitalization for heart failure also trended in a positive direction but did not reach statistical significance (HR = 0.87; 95% CI: 0.73-1.05; p=0.14).

Microvascular Outcomes

Johannes Mann, MD (Friedrich Alexander University of Erlangen, Erlangen, Germany)

While microvascular outcomes usually don’t receive as much attention as cardiovascular results at CVOT sessions, the topic turned out to be one of the real positives of the entire LEADER session. We were very surprised to see a 16% statistically improvement in time to first microvascular event  (encompassing renal and ophthalmic adverse outcomes; 95% CI: 0.73-0.97, p=0.02), driven entirely by a 22% statistically significant improvement in renal outcomes (95% CI: 0.67-0.92, p=0.003). There was no statistically significant improvement in eye outcomes – the hazard ratio was 1.15 (95% CI: 0.87-1.52, p=0.33). The Kaplan-Meier curves for renal outcomes separated one year into the study and continued to diverge throughout the study. The renal benefit was driven primarily by a difference in the diagnosis of persistent macroalbuminuria (HR=0.74, 95% CI: 0.60-0.91).

  • The implications of this strong renal benefit are substantial, perhaps even prompting consideration of a dedicated chronic kidney disease trial for liraglutide. While improvements in risk factors like glucose and blood pressure could explain some of the benefit, newer evidence suggests that there might be a direct effect at play, involving GLP-1 receptor-stimulated relaxation of muscles around glomeruli (the functional filtering units of the kidney).
  • The patient population in LEADER had a fairly high level of microvascular disease at baseline: around 2.5% of patients had an eGFR below 30 ml/min/1.73m2, ~20% were between 30 and 59 ml/min/1.73m2, and ~41% were between ml/min/1.73m2.
  • The specific outcomes assessed in the category of microvascular disease were as follows:
    • Renal: (i) New onset of persistent macroalbuminuria – as mentioned above, this was the renal sub-outcome that drove the improvement, (ii) persistent doubling of serum creatinine, (iii) need for continuous renal replacement therapy, and (iv) death due to renal disease.
    • Eye: (i) Need for retinal photocoagulation or treatment with intravitreal agents, (ii) vitreous hemorrhage, and (iii) diabetes-related blindness.

Safety

Michael Nauck, MD, PhD (Diabeteszentrum Bad Lauterberg, Germany)

Dr. Michael Nauck (St. Josef Hospital, Bochum, Germany) presented safety and adverse event data from LEADER. Most notably, treatment with liraglutide was associated with a 20% risk reduction for confirmed hypoglycemia with a blood glucose ≤56 mg/dl (HR=0.80, CI: 0.74-0.88, p<0.001) and a 31% risk reduction for severe hypoglycemia requiring assistance (HR=0.69, CI: 0.51-0.93, p=0.016). We expect that this reduction in hypoglycemia risk is largely or at least somewhat attributable to the smaller number of participants in the liraglutide group initiating insulin or sulfonylurea therapy during the trial. The results demonstrate the real-world, long-term benefits of using GLP-1 agonists as an alternative to therapies that increase hypoglycemia risk, and we imagine they could further strengthen the case for GLP-1 agonists (or even GLP-1 agonist/basal insulin combinations) as a first injectable option ahead of insulin. Interestingly, Dr. Anne Peters suggested at The diaTribe Foundation/TCOYD forum later that evening that the overall cardiovascular benefit in LEADER may be at least partially attributable to the lower use of sulfonylureas/insulin and lower hypoglycemia rates in the active treatment group rather than to specific benefits associated with liraglutide – we wonder whether this opinion will be widely shared and whether it will become a significant part of the debate over the results.

  • Total, serious, and severe adverse event rates were generally similar between the liraglutide and placebo groups. As expected, a higher proportion of patients experienced nausea, vomiting, and diarrhea leading to discontinuation in the liraglutide group (p<0.001 for each). Abdominal pain and discomfort were also significant adverse events resulting in treatment discontinuation (p=0.03 for pain, p=0.002 for discomfort). Decreased appetite was also significantly more prevalent in the liraglutide-treated group (p=0.01). Liraglutide also produced a statistically significant increase in acute gallstone disease (145 events vs. 90 in placebo, p<0.001) and acute cholecystitis (36 vs. 21 in placebo, p=0.046). Injection site reactions were higher in the liraglutide-treated group as well (32 vs. 12 in placebo, p=0.002).
  • There was a signal toward increased risk of any, malignant, and benign neoplasms by 12%, 6% and 16%, respectively, but the increase was not significant for each. Interestingly, by type, liraglutide produced a statistically significantly reduced risk of prostate cancer (HR=0.54, CI:0.34-0.88) and leukemia (HR=0.36, CI:0.13-0.99), though Dr. Nauck acknowledged that the number of events was very small. Pancreatic carcinomas were numerically higher in the liraglutide group (13 vs. 5), but the difference was not statistically significant. There were no cases of medullary thyroid carcinoma in the liraglutide-treated group and one in the placebo group. Acute and chronic pancreatitis rates in the liraglutide group were not significantly different from the placebo group.
  • However, both all-cause serious and severe adverse event rates were lower in the liraglutide group than in the placebo group – in fact, serious adverse events overall were significantly lower in the liraglutide group (p=0.01). We expect at least part of this was driven by the reduced risk of hypoglycemia in the liraglutide-treated group compared to the placebo group.

Conclusion

John Buse, MD, PhD (University of North Carolina, Chapel Hill, NC)

Dr. John Buse contextualized the LEADER results by discussing potential mechanisms of benefit, clinical implications, and comparisons to results from other CVOTs for diabetes drugs. He stressed from the outset that directly comparing results from two separate trials is an “entirely inappropriate activity” due to differences in study population, definition and adjudication of events, secular trends in diabetes management, and the countries where the studies were conducted. With that in mind, Dr. Buse shared that he was “nevertheless going to engage in that activity,” suggesting that the divergent results from LEADER and ELIXA (CVOT for Sanofi’s lixisenatide) could have been due either to differences in study design or intrinsic differences between the molecules. He contrasted the benefits seen in LEADER with those in EMPA-REG OUTCOME, suggesting that the LEADER benefit was more likely mediated through a reduction in atherosclerosis while the EMPA-REG results may have been due to an osmotic effect or an impact on fuel energetics. Dr. Buse offered minimal commentary on the clinical implications of the results but stressed that the conclusions need to be limited to high-risk patients. Like previous speakers, he closed by highlighting the trial’s impressive retention and follow-up, suggesting that the trial conduct should inspire strong confidence in the results.

  • Dr. Buse believes that the “substantial differences” between the results from LEADER and ELIXA could be due either to differences in trial design or intrinsic drug-specific differences. He noted that ELIXA had a different primary endpoint (four-point MACE) and recruited an even higher-risk patient population (patients with a recent acute coronary syndrome event) than LEADER. The nature of the population appeared to have an impact on the pattern of events (the majority of events occurred at the beginning of the trial) and may have impacted the results as well. However, Dr. Buse also stressed that lixisenatide and liraglutide are very different molecules both in terms of structure and pharmacokinetics. Lixisenatide is an analog of the Gila monster-derived exenatide while liraglutide is an analog of human GLP-1, and liraglutide has a much longer half-life and provides 24-hour coverage. We imagine that the PK differences in particular could very likely have contributed to the discrepancy on CV outcomes; future CVOTs for other GLP-1 agonists should provide more insight on this question. 
  • Dr. Buse contrasted the gradual, consistent benefit in LEADER with the more immediate and unexpected benefit in EMPA-REG OUTCOME. He argued that while the hazard ratio for the primary endpoint was “remarkably similar” (13% vs. 14%) in the two trials, the overall picture was very different. EMPA-REG OUTCOME showed a rapid separation between groups followed by maintenance of the difference, whereas the curves in LEADER began to separate within the first 18 months and continued to diverge for the rest of the trial. Similarly, while both studies showed the most profound benefit on CV death, LEADER showed much more consistent results across other outcomes. Dr. Buse suggested that the pattern and timing of responses in LEADER is more consistent with an effect on atherosclerosis, while the main hypotheses at this point for the EMPA-REG OUTCOME results relate to osmotic diuresis and fuel energetics. 

Discussant

Laurie Baggio, PhD (Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada)

Dr. Laurie Baggio’s discussant presentation explored possible mechanistic explanations for the effects observed in LEADER. Regarding the surprisingly large benefit seen on nephropathy, Dr. Baggio suggested that improvements in risk factors like glucose, oxidative stress, weight, blood pressure, and inflammation played an indirect role, but there also exists the tantalizing possibility that liraglutide could be acting directly to reduce filtration pressures in the glomerulus (the functional filtration unit of the kidney), preventing them from burning out. On the observed increase in gallstones, Dr. Baggio speculated on potential mechanisms (weight loss in known to cause an increase in gallstones), but concluded by highlighting the dearth of data in this area, characterizing gallstones as a major area for future investigation on GLP-1 agonists. In her conclusion, Dr. Baggio stated that it is a “huge advantage” for patients to know that liraglutide reduces mortality, cardiovascular death, MI, and kidney disease, though they must balance those benefits against increases in nausea, vomiting, diarrhea, and gallstone disease.

  • Improvements in cardiovascular risk factors likely explain the lion’s share of the MACE reduction seen with liraglutide, but Dr. Baggio did not rule out the possibility of direct GLP-1-receptor-mediated action directly on the heart. Evidence is mixed on whether GLP-1 receptors are present in cardiac ventricles. The evidence is clearer on the improvements in risk factors, including body weight, blood vessel health, diuresis, natriuresis, reducing inflammation, glucose control, postprandial lipids, coagulation, and reduced hypoglycemia. However some of these risk factors that were measured, such as blood pressure, did not change enough to explain much of the overall cardiovascular benefit seen in the trial.
  • Dr. Baggio appeared unconvinced that GLP-1 agonists are the best option for patients with advanced heart failure. She pointed that existing outcomes studies, including LEADER, do not suggest a benefit of GLP-1 agonists on heart failure. In her words, there is no reason to avoid using a GLP-1 agonists in a patient with early-stage heart failure, but that prescribers “may want to think twice” in patients with more advanced heart failure. In any case, SGLT-2 inhibitors (or at least empagliflozin from EMPA-REG OUTCOME data) appear to do better with reducing the incidence of heart failure.
  • Dr. Baggio briefly discussed the increase in heart rate seen with liraglutide, but suggested that LEADER does not provide sufficient information to assess the issue one way or the other.
  • The increases in amylase and lipase are hard to assess, given that their levels are usually variable and often elevated in type 2 diabetes patients who are otherwise asymptomatic. In fact, 23% of LEADER patients had elevated levels of the enzymes at baseline. Amylase and lipase levels are examined because they are diagnostic for pancreatitis, but overall the pancreatitis data were reassuring, as is experimental evidence that GLP-1 agonists do not promote acinar cell inflammation or proliferation.
  • LEADER was not powerful or long enough to provide a definitive answer on liraglutide and cancer. Dr. Baggio sees the GLP-1/cancer question as a valid one, in light of evidence that GLP-1/GLP-1 agonists can reduce apoptosis, increase intestinal mass, and increase beta cell mass. She suggested that it will be helpful to know when in LEADER the cancer cases occurred.

Oral Presentations: Treatment Choices after Orals in Type 2 Diabetes

Efficacy and Safety of Once-Weekly Semaglutide vs. Sitagliptin as Add-on to Metformin and/or Thiazolidinediones After 56 Weeks in Subjects with Type 2 Diabetes

Bo Ahrén, MD, PhD (Lund University, Sweden)

In the double-blinded, double-dummy, active-controlled, parallel-group SUSTAIN 2 trial (n=1231), semaglutide 0.5 mg produced a 0.77% greater A1c reduction (p<0.0001) and semaglutide 1.0 mg produced a 1.06% greater A1c reduction (p<0.0001) than Merck’s Januvia (sitagliptin 100 mg) after 56 weeks of treatment. Participants had type 2 diabetes and were on metformin, TZDs, or both. In total, semaglutide 0.5 mg produced a 1.3% A1c reduction and semaglutide 1.0 mg produced a 1.6% A1c reduction, compared to sitagliptin’s 0.5% A1c reduction (baseline A1c=8.1%, p<0.0001). Participants treated with semaglutide 0.5 mg and 1.0 mg experienced a 17.4 mg/dl and 26.74 mg/dl reduction in fasting plasma glucose (FPG), respectively, compared to participants treated with sitagliptin (baseline FPG=169.4 mg/dl, p<0.0001). Overall, participants experienced FPG reductions of 37.4 mg/dl, 46.7 mg/dl, and 20.8 mg/dl on semaglutide 0.5 mg, semaglutide 1.0 mg, and sitagliptin, respectively. End-of-trial 7-point SMPG profiles were lower at every point for participants treated with semaglutide compared to sitagliptin and compared to baseline. 78% of participants in the semaglutide 1.0 mg group and 69% of participants in the semaglutide 0.5 mg group achieved an end-of-trial A1c of <7.0% at 56 weeks, compared to 36% of the sitagliptin-treated group. 66% of the semaglutide 1.0 mg group and 53% of the semaglutide 0.5 mg group achieved a target A1c of ≤6.5% at 56 weeks, compared to 20% of the sitagliptin-treated group.

  • 62% of participants on semaglutide 1.0 mg and 46% of participants on semaglutide 0.5 mg achieved ≥5% weight loss, compared to 18% of participants in the sitagliptin group. Furthermore, 24% of participants in the semaglutide 1.0 mg group and 13% of participants in the semaglutide 0.5 mg group experienced even more impressive weight loss of ≥10%, compared to just 3% of the sitagliptin-treated group. Semaglutide 0.5 mg and 1.0 mg produced a 2.37 kg (~5.22 lbs) and 4.22 kg (~9.3 lbs) greater weight loss, respectively, than sitagliptin (p<0.0001). In total, participants on semaglutide 0.5 mg lost a mean 4.3 kg (~9.5 lbs) of body weight while participants on semaglutide 1.0 mg lost a mean 6.1 kg (~13.4 lbs), compared to 1.9 kg (~4.2 lbs) with sitagliptin (baseline body weight=89 kg [~196 lbs]). Like the A1c results, Dr. Ahrén highlighted the early and dramatic divergence in weight loss between the semaglutide and the exenatide groups.
  • 74% of participants in the semaglutide 1.0 mg group and 63% of participants in the semaglutide 0.5 mg group achieved a composite endpoint of (i) A1c <7.0%, (ii) no severe or blood-glucose confirmed symptomatic hypoglycemia, and (iii) no weight gain. Only 27% of participants in the sitagliptin-treated group were able to achieve this endpoint. Thus, participants on semaglutide appear 2-3 times more likely to achieve this very clinically relevant composite outcome.
  • Overall, serious, and severe adverse event rates were comparable across all three treatment groups, though adverse events leading to discontinuation were higher in the two semaglutide groups. Not surprisingly, Dr. Ahrén attributed the higher discontinuation rate of the semaglutide groups to increased GI side effects – 18% of participants in both semaglutide groups experienced nausea at least once throughout the study (vs. 7% in the sitagliptin group), 13% experienced diarrhea (vs. 7%), and 8%-10% experienced vomiting (vs. 3%). That said, Dr. Ahrén emphasized that the vast majority of cases of nausea were classified as “mild,” the percentage of patients experiencing nausea at any single time point in the study never exceeded 10%, and the percentage of patients experiencing nausea tapered off as the trial progressed. Hypoglycemia, pancreatitis, and malignant neoplasms were similar across all the groups. Participants in the two semaglutide groups experienced a 2 beats/min increase in heart rate, compared to a 1 beat/min increase in the sitagliptin group.

SUSTAIN 2 Results Summary

Treatment

Semaglutide 0.5 mg

Difference between 0.5 mg and sitagliptin

Semaglutide 1.0 mg

Difference between 1.0 mg and sitagliptin

Sitagliptin 100 mg

A1c

-1.3%

-0.77%, p<0.0001

-1.6%

-1.06%, p<0.0001

-0.5%

Fasting Plasma Glucose (FPG)

-37.4 mg/dl

-17.4 mg/dl, p<0.0001

-46.7 mg/dl

-26.74 mg/dl, p<0.0001

-20.8 mg/dl

% Achieving A1c <7.0%

69%

 

78%

 

36%

% Achieving A1c <6.5%

53%

 

66%

 

20%

Weight

-4.3 kg (~9.5 lbs)

-2.37 kg (~5.22 lbs), p<0.0001

-6.1 kg (~13 lbs)

-4.22 kg (~9.3 lbs), p<0.0001

-1.9 kg (~4.2 lbs)

% Achieving ≥5% Body Weight Loss

62%

 

46%

 

18%

% Achieving ≥10% Body Weight Loss

13%

 

24%

 

3%

% Achieving A1c <7.0% with no severe/symptomatic hypoglycemia and no weight gain

63%

 

74%

 

27%

Efficacy and Safety of Once-Weekly Semaglutide vs. Exenatide ER in Subjects with Type 2 Diabetes (SUSTAIN 3)

Andrew Ahmann, MD (Oregon Health & Science University, Portland, OR)

In the open-label, active-controlled, parallel-group SUSTAIN 3 (n=813) trial, participants treated with semaglutide 1.0 mg experienced a 0.62% greater A1c reduction (p<0.0001) than participants treated with exenatide ER 2.0 mg (AZ’s once-weekly Bydureon). Overall, those in the semaglutide-treated group experienced a mean A1c reduction of 1.5%, compared to a 0.9% reduction in the exenatide-treated group (baseline A1c=8.3%, p<0.0001). Dr. Ahmann emphasized that the A1c curves for the semaglutide and exenatide groups diverged early on and stayed significantly different throughout the trial. End-of-trial 7-point SMBG profiles were lower at every point for participants treated with semaglutide compared to exenatide and compared to baseline, though the difference appeared to be less dramatic than the separation between the semaglutide and sitagliptin SMPG profiles (as expected, given the generally accepted greater glucose-lowering efficacy of GLP-1 agonists compared to DPP-4 inhibitors) – it would have been more helpful from our view to have CGM data than SMBG data. 67% of participants in the semaglutide group achieved an end-of-trial A1c of <7.0% at 56 weeks, compared to 40% of the exenatide-treated group. 47% of the semaglutide group achieved a target A1c of ≤6.5% at 56 weeks, compared to 22% of the exenatide-treated group.

  • 52% of participants treated with semaglutide in SUSTAIN 3 achieved ≥5% weight loss, compared to 17% of those treated with exenatide. 21% of semaglutide-treated patients achieved ≥10% weight loss compared to only 4% of exenatide-treated patients. Participants treated with semaglutide experienced a 3.78 kg (~8.3 lbs) greater weight loss than those treated with exenatide (p<0.0001). In total, the semaglutide-treated group experienced a mean weight loss of 5.6 kg (~12.3 lbs) compared to a mean weight loss of 1.9 kg (~4.2 lbs) with exenatide (baseline body weight = 95.8 kg [~211 lbs]).
  • With semaglutide treatment, 57% of participants were able to achieve a composite endpoint of A1c <7% with no severe or symptomatic hypoglycemia and no weight gain. This is about twice the proportion of participants in the exenatide-treated group that achieved this composite endpoint (29%).
  • Overall adverse events were similar between the semaglutide and the exenatide groups, but serious AEs, severe AEs, and AEs leading to discontinuation were slightly higher in the semaglutide group (9% vs. 7%). This was likely driven by the increased GI side effects seen with semaglutide. In particular, as was previously reported, participants in the semaglutide group experienced almost twice as much nausea as those in the exenatide group (22% vs. 12%). Participants in the semaglutide group also experienced higher rates of diarrhea (11% vs. 8%), decreased appetite (8% vs. 5%), vomiting (7% vs. 6%), dyspepsia (7% vs. 5%), and constipation (6% vs. 5%). The side effect profile is consistent with what has been reported across the SUSTAIN phase 3 development program. Our sense is that semaglutide is a more potent GLP-1 agonist, offering greater A1c and weight loss efficacy – though some suggest it may have an accompanying higher GI side effects, with most in single digits, we’re not too worried about that – although to what degree “hand holding” in the trial would have reduced those reporting nausea etc we don’t know. Either way, there are obviously a high percentage of patients that would seem to be able to benefit from this therapy and we look forward to seeing the move toward the market for it.
  • The SUSTAIN 2 and SUSTAIN 3 results were some of the most highly anticipated from the phase 3 development program for semaglutide. Novo Nordisk is positioning semaglutide as a next-generation GLP-1 agonist with greater A1c efficacy, greater weight loss, and potential additional benefits (such as cardioprotection and positive effects on NASH). The results drive home semaglutide’s superiority on the A1c and weight loss front compared to other incretins. We’d love to see how semaglutide stacks up against Lilly’s new GLP-1 agonist Trulicity (dulaglutide), which has been garnering rave reviews from patients and providers. We’d also be highly interested in seeing a head-to-head trial of injectable semaglutide vs. an SGLT-2 inhibitor – and it goes without saying that we’d love to see how they work together. The PIONEER phase 3 development program for the oral formulation of semaglutide does includes a trial against Lilly/BI’s Jardiance (empagliflozin).

SUSTAIN 3 Results Summary

Treatment

Semaglutide 1.0 mg

Exenatide ER 2.0 mg

Difference between semaglutide and exenatide

A1c

-1.5%

-0.9%

-0.62%, p<0.0001

% Achieving A1c <7.0%

67%

40%

 

% Achieving A1c <6.5%

47%

22%

 

Weight

-5.6 kg (~12.3 lbs)

-1.9 kg (~4.2 lbs)

-3.78 kg (~8.3 lbs), p<0.0001

% Achieving ≥5% Body Weight Loss

52%

17%

 

% Achieving ≥10% Body Weight Loss

21%

4%

 

% Achieving A1c <7.0% with no severe/symptomatic hypoglycemia and no weight gain

57%

29%

 

Superior Efficacy of ITCA 650 vs. Sitagliptin in Uncontrolled Type 2 Diabetes on Metformin: The FREEDOM-2 Randomized, Double-blind, 1-Year Study

Julio Rosenstock, MD (Dallas Diabetes and Endocrine Center, Dallas, TX)

Dr. Julio Rosenstock presented results from the phase 3 FREEDOM-2 study demonstrating significantly greater A1c reductions (1.5% vs. 0.8%; p<0.001) and weight loss (4 kg vs. 1.3 kg; p<0.001) with Intarcia’s ITCA 650 vs. Merck’s Januvia (sitagliptin). Intarcia announced topline results from the trial in August. The double-blind trial randomized 535 patients with type 2 diabetes on metformin to receive either ITCA 650 + oral placebo or Januvia + implantable placebo for 52 weeks. Patients received the initiation dose of ITCA 650 for 13 weeks and switched to the maintenance dose for the remaining 39 weeks. The A1c difference between the groups was already significant at six weeks and stabilized at week 26; final reductions were 1.5% with ITCA 650 vs. 0.8% with Januvia (baseline = 8.6%-8.7%; p<0.001). ITCA 650 also produced significantly greater reductions in fasting plasma glucose (47 mg/dl vs. 28 mg/dl; p<0.001). Weight loss followed a similar pattern as the A1c reductions, with a fairly early separation that stabilized at around week 26 and remained stable throughout the trial. The final weight reduction was 4 kg (~8.8 lbs) with ITCA 650 vs. 1.3 kg (~2.9 lbs) with Januvia (baseline BMI = 33 kg/m2; p<0.001). ITCA 650 was also superior in terms of the percentage of patients achieving the composite endpoint of A1c reduction >0.5% and weight loss ≥2 kg (61% vs. 28%; p<0.001) and the percentage achieving A1c targets of <7% (61% vs. 42%) and <6.5% (44% vs. 21%). As expected, there were more GI events in the ITCA 650 group, though the discontinuation rates due to these events were low (4.5% for nausea and 2.3% for vomiting). Importantly, the rate of procedure-related adverse events was quite low (<1%) in both groups. Dr. Rosenstock also emphasized that nausea rates peaked when the initial dose was started and when the dose was escalated, but rates were quite low throughout the rest of the trial.

  • We are particularly impressed with the durability of the A1c and weight reductions – the difference between the groups held steady from week 26 through the end of the trial. We also found the results for the composite endpoint especially compelling and expect that payers will as well. Intarcia has reported results from three additional trials for ITCA 650: results from FREEDOM-1 and FREEDOM-HBL demonstrating significant A1c reductions vs. placebo were presented at ADA 2015 and topline results from the FREEDOM-CVO trial demonstrating a neutral effect on CV outcomes were announced in May. The impressive efficacy and guaranteed adherence should make ITCA 650 an appealing option for a wide range of patients and could significantly expand use of the GLP-1 agonist class, although would not be surprised if the product’s commercial performance falls a bit short of the extremely high expectations that some in the field have set for it, particularly less informed investors looking at the first year or two. We have big expectations that the GLP-1 field will continue to grow, and expect Intarcia to be a meaningful part of this. We appreciate very much Intarcia’s focus on helping improve patient adherence and engagement and look very forward to seeing how the launch emerges. Ideally, this therapy will continue the path that a range of companies are trying to take to make various therapies easier to prescribe and take and stay on.

Questions and Answers

Q: Are there any issues around removal in terms of fibrosis?

A: There were no issues of fibrosis. The technique has been highly revised. It’s now done with a delivery device and different tools to ensure the placement is very superficial. Before there was not a tool to really make sure the device was not placed too deep. Now they have a device where you can’t get too deep, so that’s no longer an issue.

Q: Do you have to take the device out to change the dose?

A: Yes. This device could be used for six months, and eventually it will be one year. Taking it out takes less than two minutes.

Efficacy and Durability of Exenatide in Combination with Pioglitazone vs. Basal-Bolus Insulin in Poorly Controlled Type 2 Diabetic Patients: The QATAR Study

Muhammad Abdul-Ghani, MD, PhD (UT Health Science Center, San Antonio, TX)

Dr. Muhammad Abdul-Ghani presented results of the QATAR study, demonstrating that the addition of exenatide in combination with pioglitazone in poorly controlled type 2 diabetes patients (on metformin/SFU) produces greater A1c reductions with less hypoglycemia and weight gain compared to basal-bolus insulin therapy. This study randomized poorly controlled type 2 diabetes patients on maximal dose of metformin/SFU to either once-weekly exenatide plus pioglitazone (n=112) or basal (glargine)-bolus (aspart) insulin (n=114). Follow-up visits were conducted monthly for the first six months and then every two to three months afterwards. At six and 12 months, the exenatide/pioglitazone arm (baseline A1c of ~10%) achieved A1c levels of 6.5% and 6.2%, respectively, compared to the insulin arm’s achievement of 7.5% and 7.3% at 6 and 12 months, respectively – that’s a pretty big difference and excellent results, especially given the high baseline A1c. In addition, more participants in the insulin therapy arm failed to achieve the A1c goal <7% compared to the combination therapy arm (63% vs. 17%). Regarding adverse events, the exenatide/pioglitazone group experienced significantly less hypoglycemia (0.21 vs. 0.67 events/patient year) and gained less weight (0.7 kg vs. 3.1 kg). On the other hand, the combo therapy arm saw greater edema, injection site bumps, nausea, and other GI side effects. But ultimately, these findings are promising and highlight the rising potential and greater enthusiasm for various forms of combination therapies. The TZD element of the combination was great to see, particularly as this is now a generic drug – we’ve heard when it is taken in lower doses, there are often significantly fewer side effects and we’d love to know more on that. These results reinforce our thinking that early and mid-stage in diabetes treatment, prandial insulin is going to be chosen a smaller percentage of the time given other alternatives – we believe the other alternatives will also keep patients alive longer and that more will eventually need prandial insulin as the “lifespan” will continue to expand. We just hope an “elderly well” rather than an “elderly unwell” will start to emerge. Although we hear a lot of negativity about SFUs, we’d also love to see “all” patients get “the best one.”

Questions and Answers

Q: What did you do with the SFUs? Did you continue it or what?

A: Yes, the treatments were added on top of SFUs and metformin. Participants were also allowed to adjust meds throughout the study.

Q: You noted there was more edema in the combo therapy – was that related to CHF?

A: It was peripheral edema. Only three patients discontinued due to the edema.

Q: One third of your patients had nausea in the combo therapy. Most of these patients also had severe insulin resistance. Did you check the food intake with nausea in relation to the weight changes?

A: No, we didn’t but it’s an interesting point. [Editor’s note – we’re surprised this wasn’t checked. This was an early question/criticism of Amylin’s Byetta and proved to be unfounded.]

Dr. Julio Rosenstock (Dallas Diabetes and Endocrine Center, Dallas, TX): This is very interesting data. These patients have more than ten years of diabetes and A1cs of 10% on metformin and SFUs. The A1c reductions are so impressive. I’ve never seen anything like this. I wish my patients were in the QATAR study.

Clinical Impact of Titratable Fixed-Ratio Combination of Insulin Glargine/Lixisenatide vs. Each Component Alone in Type 2 Diabetes Inadequately Controlled on Oral Agents: LixiLan-O Trial

Julio Rosenstock, MD (Dallas Diabetes and Endocrine Center, Dallas, TX)

Dr. Julio Rosenstock presented results from the phase 3 LixiLan-O trial demonstrating significantly greater A1c reductions with Sanofi’s iGlarLixi (formerly LixiLan) vs. either of its components in patients with type 2 diabetes on oral agents. Sanofi announced topline results from the trial in July 2015 and the dataset was included in the company’s briefing documents for the recent FDA Advisory Committee meeting for iGlarLixi. The open-label trial randomized 1,170 patients with type 2 diabetes not at goal on metformin and another oral agent to receive either iGlarLixi (n=469), Lantus (insulin glargine; n=467), or lixisenatide (n=234) for 30 weeks. A1c reductions were significantly greater with iGlarLixi (1.6%) vs. both Lantus (1.3%) and lixisenatide (0.9%) (baseline = 8.1%; p<0.0001). A significantly higher percentage of patients achieved an A1c <7% with the combination (74%) compared to Lantus (59%) and lixisenatide alone (33%). Fasting plasma glucose reductions were comparable with iGlarLixi (62 mg/dl) and Lantus (59 mg/dl) and less impressive with lixisenatide (27 mg/dl) (baseline = 176-178 mg/dl; p<0.0001). As expected, lixisenatide’s greatest contribution was on postprandial glucose. iGlarLixi was superior to both Lantus (by 43 mg/dl) and lixisenatide (by 20 mg/dl) on two-hour postprandial glucose; the combination was superior to Lantus (by 38 mg/dl) but inferior to lixisenatide (by 16 mg/dl) on postprandial glucose excursions. Seven-point glucose profiles showed lower overall glucose throughout the day with iGlarLixi and lower peaks compared to Lantus, especially at breakfast (we’d love in the future CGM use). The combination also demonstrated a 1.4 kg weight benefit compared to Lantus and allowed a significantly higher percentage of patients to achieve the composite endpoint of A1c <7% with no weight gain (43% vs. 25% with Lantus and 28% with lixisenatide).

  • Especially relevant in light of the recent IGlarLira AdComm discussion, Dr. Rosenstock highlighted the potential for dosing flexibility with the two iGlarLixi pens. Sanofi plans to market iGlarLixi in two pens, one (pen A) with a 2:1 insulin glargine/lixisenatide ratio and insulin doses ranging from 10-40 U/day and another (pen B) with a 3:1 insulin glargine/lixisenatide ratio and insulin doses ranging from 40-60 U/day. Dr. Rosenstock emphasized that this allows insulin titration up to 60 U without going above the maximum dose of 20 mcg lixisenatide. Data on the final dose distribution in LixiLan-O showed that 56% of patients achieved good control with pen A, 44% required intensification to pen B, and only 8% reached the maximum dose of 60 U without achieving target. A number of panelists at the AdComm meeting expressed concerns about distinguishing between the two pens and about the nomenclature of “units” used to dose the combination. These concerns were fairly unexpected to us, and we hope Sanofi and the FDA can work together to resolve them in short order.
  • Adverse events were generally similar between groups in the trial. Nausea rates were substantially lower with iGlarLixi (9.6%) compared to lixisenatide (24%), confirming one of the main expected with these combinations compared to GLP-1 agonists alone. Dr. Rosenstock highlighted the fact that only 0.4% of the iGlarLixi group discontinued treatment due to nausea (compared to 2.6% in the lixisenatide group). The rate of documented symptomatic hypoglycemia was low and comparable between the iGlarLixi and Lantus groups (1.4 vs. 1.2 events/patient-year).

Questions and Answers

Q: Given the short duration of action of lixisenatide, might it make more sense to use it twice a day?

A: That sounds like common sense but you don’t need to. With the results you get, why would you need to? You get an effect on postprandial glucose mainly in the morning, you do have some carry over for lunch, and by dinner there’s not much, but you get down to 6.5%. We shouldn’t use it twice a day because it’s not approved. (Editor’s note – we think this question is interesting – as we continue to emphasize, the over-emphasis on A1c is troubling. We are curious if twice-daily dosing might get more of the 26% of patients who did not reach 7% A1c to 7% or lower.)

Q: Would you use it twice a day if A1c deteriorates over time?

A: I don’t know. We need longer-term studies.

Q: I’d like to see a study where you challenge the fixed-ratio combination not only to glargine + lixisenatide but to degludec + liraglutide, comparing the fixed ratio with split injections. I think it would highlight the convenience of the fixed ratio and on the other side the ability to individualize the combination because we know patients have different characteristics.

A: There’s no question that what you suggest would be a nice study. The question is whether simultaneous therapy is better than sequential. All these years we’ve done sequential. We have a bit of indirect evidence on this from GetGoal Duo 1, where patients were on basal insulin for 12 weeks and then added lixisenatide. That got people down to 7% and here we got down to 6.5%. The important bottom line is that we get down to 6.5%. The same was true with IDegLira. Both combinations get people down to levels we were never able to get before with any of the components alone.

Q: What concentration of insulin glargine was used?

A: U100.  

Oral Presentations: Beyond Basal Insulin in Type 2 Diabetes – Treatment Intensification Options

Efficacy and Safety of the Insulin Glargine/Lixisenatide Fixed-Ratio Combination vs. Insulin Glargine in Patients with T2DM: The LixiLan-L Trial

Vanita Aroda, MD (MedStar Health Research Institute, Hyattsville, MD)

The highly respected Dr. Vanita Aroda presented results from the phase 3 LixiLan-L trial demonstrating significantly greater A1c reductions with Sanofi’s iGlarLixi (formerly LixiLan) vs. Lantus (insulin glargine) in patients with type 2 diabetes on basal insulin, driven by improvements in postprandial glucose. Sanofi announced topline results from the trial in September 2015 and the dataset was included in the company’s briefing documents for the FDA Advisory Committee meeting for iGlarLixi. The open-label trial randomized 736 patients not at goal on basal insulin and oral drugs to treatment with iGlarLixi (n=367) or Lantus (n=369) for 30 weeks. The insulin glargine dose in both groups was titrated to a fasting glucose target of 80-100 mg/dl and the dose was capped at 60 U/day (to match the maximum dose in the combination). A1c reductions were significantly greater with iGlarLixi (1.2%) than Lantus (0.6%) (baseline = 8.1%). A significantly higher percentage of patients achieved an A1c <7% with iGlarLixi (55%) than with Lantus (30%; p<0.0001). Fasting plasma glucose reductions were similar in both groups (21 mg/dl vs. 23 mg/dl), as expected given the almost identical average daily doses of insulin glargine at the end of the trial (46 vs. 47 U). The main contribution of lixisenatide to the combination was on postprandial glucose: iGlarLixi produced significantly greater reductions in both two-hour postprandial glucose (85 mg/dl vs. 25 mg/dl) and postprandial excursions (70 mg/dl vs. 8 mg/dl) compared to Lantus. Seven-point glucose profiles illustrated this improvement in postprandial control, particularly after breakfast. iGlarLixi led to a 1.4 kg weight benefit and comparable hypoglycemia rates to Lantus. The combination also allowed a greater percentage of patients to achieve an A1c <7% without weight gain (34% vs. 13%), an A1c <7% without hypoglycemia (32% vs. 19%), and an A1c <7% without weight gain or hypoglycemia (20% vs. 9%) – while the benefit is encouraging, the low absolute percentages in both groups illustrate the remaining need for more effective therapies.

Questions and Answers

Q: Do you think the weight loss is less when lixisenatide is used in combination with insulin vs. separately when added to insulin or without insulin?

A: I would refer you to the LixiLan-O trial, where we saw greater weight loss with lixisenatide alone. Here we have mitigation of the weight gain with insulin glargine.

Q: But the average weight loss seems to be less here than when you add on a GLP-1 agonist without insulin or even separately.

A: Part of it might be the final dose, which was 17 mcg of lixisenatide on average.

Q: I’m guessing the combination was administered before breakfast. Was the administration of glargine alone done at the same time?

A: Glargine could be administered at any time and it was consistent throughout the trial. The combination was injected an hour before breakfast.

Q: From the seven-point profile, it’s obvious that the main effect is on that first meal, yet it was a fixed schedule of dosing before breakfast. Do you think the results would be different if it was administered with the largest meal rather than breakfast? My patients don’t all eat breakfast, and dinner is typically the biggest meal in the US.

A: That’s an intriguing question that can only be answered by a trial. There was a sub-study looking at dosing at the main meal vs. the morning and the main effect seems to be in the morning, but we would need a trial to know.

Q: You didn’t save a single dose of insulin by adding lixisenatide and you had the same rate of hypoglycemia. Is there any information on the PK/PD data? Were the profiles of both components really preserved? It seems like a very weak effect.

A: The PK data were consistent with what was seen in the lixisenatide standalone program. Your point is appreciated that there’s not necessarily an insulin-sparing effect. I would also state here that we had a greater A1c reduction down to 6.9% without increased hypoglycemia. We’re looking at two different end A1cs with comparable hypoglycemia.

Q: Looking at the meal data in the control group, you still have glucose values of 230 mg/dl two hours after a meal – people are clearly not well controlled. Would you anticipate different results if you had a more well-controlled group?

A: The 230 mg/dl was from a mechanistic substudy highlighting the mechanism of action of iGlarLixi on postprandial glucose. The 7-point SMPG, reflective of control in the comparator group, showed the control we typically see with titration with insulin glargine (postprandial glucose of 160s-190s during the day). This, along with detailed review of titration, superimposable fasting glucoses, and insulin doses all support appropriate titration in the control group.

Patients with T2D Treated with Insulin Degludec/Liraglutide (IDegLira) Have a Greater Chance of Reaching Glycemic Targets without Hypoglycemia and Weight Gain than with Insulin Glargine (IG)

Ildiko Lingvay, MD, MPH (University of Texas Southwestern Medical Center, Dallas, TX)

Dr. Ildiko Lingvay (University of Texas Southwestern Medical Center, Dallas, TX) presented a post-hoc analysis of DUAL V trial focusing on patients who were able to achieve fasting plasma glucose (FPG) and A1c targets (FPG <130 mg/dl or A1c <7%) in the trial. DUAL V, which was previously presented at ADA 2015, demonstrated striking A1c and weight benefits with Novo Nordisk’s fixed-ratio GLP-1 agonist/basal insulin combination Xultophy (insulin degludec/liraglutide) over basal insulin Lantus (insulin glargine) intensification in 557 patients with type 2 diabetes who were already on Lantus and metformin (-0.6% and -3 kg [7lbs], p<0.001 for both). In this post-hoc analysis, Dr. Lingvay showed that significantly more participants in the trial who were treated with Xultophy and achieved a FPG <130 mg/dl did so without hypoglycemic episodes (57.9% of those in the Xultophy arm were able to do so, compared to 40.9% of those in the Lantus arm, p<0.0001). More participants achieving the target FPG with Xultophy did so without weight gain as well (54.3% of Xultophy arm vs. 24% of Lantus arm, p<0.0001). Impressively, 41% of participants who achieved a FPG <130 mg/dl in the Xultophy arm did so without either hypoglycemia or weight gain, while only 14% of those in the Lantus arm did so (p<0.0001). Similarly, greater proportions of patients in the Xultophy arm were able to (i) achieve an A1c <7%, (ii) achieve an A1c <7% with no hypoglycemia, and (iii) achieve an A1c <7% with no hypoglycemia or weight gain. This held true for regardless of baseline A1c (≤7.5%, >7.5%-≤8.5%, and >8.5%). Dr. Lingvay also showed that participants on Xultophy were able to achieve the FPG target <130 mg/dl more quickly than participants on Lantus, despite those participants taking lower insulin doses than those in the Lantus arm throughout the trial.

Improved Glycemic Control and Weight Loss with Once-Weekly Dulaglutide vs. Placebo, Both Added to Titrated Daily Insulin Glargine, in Type 2 Diabetes Patients (AWARD-9)

Paolo Pozzilli, MD (University Campus Bio-Medico, Rome, Italy)

In front of a standing-room-only crowd, Dr. Paolo Pozzilli presented the results of AWARD-9, a double-blind, 28-week superiority trial comparing the effects of Lilly’s Trulicity (dulaglutide) vs. placebo on A1c and weight when added to insulin glargine in type 2 diabetes patients. The trial randomized 300 patients with inadequate glycemic control (A1c of 7-10.5%) to dulaglutide 1.5 mg (n=150) or placebo (n=150) on top of once-daily glargine titrated to a FPG target of 71-99 mg/dl (± metformin). Baseline characteristics were similar between both groups (please see below). Data at 28 weeks show that compared to placebo, dulaglutide provided significantly greater reductions in A1c (-0.7% vs. -1.4%, respectively), and in fasting serum glucose (28 vs. 45 mg/dl, respectively; p<0.001 for both comparisons). No difference in the rate of hypoglycemia was observed. Patients on dulaglutide experienced a weight loss (4.2 lbs [1.91 kg]), compared to a weight gain with placebo (1.1 lbs [0.50 kg]; p<0.001). In addition, insulin glargine requirements were statistically significant lower in the dulaglutide group (13U) vs. the placebo group (26U).

  • The rate of retention was similar between the dulaglutide and placebo groups (92% and 89%, respectively). The two groups also had similar baseline characteristics, with an average age of 60 years, percent female of 41%-43%, percent Caucasian of 92%-95%, BMI of 33 kg/m2, diabetes duration of 13 years, A1c of 8.3%-8.4%, fasting serum glucose of 156-157 mg/dl, and percent on metformin of 87%-89%.

Table: 28-week data on the effect of dulaglutide vs. placebo on glucose measurements, weight, and glargine requirements.

Primary Endpoint

Dulaglutide

Placebo

Difference

p value

A1c reduction  (%)

1.44

0.67

0.77

p <0.001

% pt with A1c <7%

69%

35%

--

p <0.001

% pt with A1c <6.5%

51%

17%

--

p <0.001

Reduction in FSG (mg/dl)

45

28

17

p <0.001

Weight change

-1.91 kg (4.2 lbs)

+0.50 kg (1.1 lbs)

-2.41 kg (5.3 lbs)

p <0.001

Change in glargine dose

13U

26U

-13U

p <0.001

  • Hypoglycemia rates between the two groups were similar. The dulaglutide and placebo groups had similar rates of overall hypoglycemia (82% vs. 76%, respectively), documented symptomatic hypoglycemia (53% vs. 45%, respectively), and nocturnal hypoglycemia (42% vs. 43%, respectively). The dulaglutide group had one episode of severe hypoglycemia, compared to zero in the placebo group.
  • Regarding adverse events, more gastrointestinal symptoms were observed in the dulaglutide groups. Dr.  Pozzilli noted that these events only led to discontinuation of therapy in very few patients.

Questions and Answers

Q: Can you give us an idea on how the insulin was adjusted?

A: The basal insulin glargine dose was given according to the classical algorithm used for a patient with basal-only insulin. It was then titrated by two units.

Q: You had a baseline A1c of 8.4%, which came down to about 7%. But you only had a fraction of people achieve an A1c <7%, suggesting that there were non-responders. Did you look at those non-responders?

A: The patients had an excellent response if you look at the standard deviation. You see that there is minimal variation, suggesting that nearly all the patient responded to therapy. The difference between the two groups was highly significant between the two groups.

Dr. Stefano Del Prato (University of Pisa, Italy): There is something that is not completely clear to me. People in the placebo group required 26 more units of glargine compared to 13 units for dulaglutide, yet there was no difference in the rate of hypoglycemia. What is the explanation? Because one of the things that we have been exposed to is that the combination of insulin plus a GLP-1 agonist often comes with a reduction in hypoglycemia. Is it because of the titration?

A: Yes, I think it is the titration.

Semaglutide Reduces Appetite and Energy Intake, Improves Control of Eating, and Provides Weight Loss in Subjects with Obesity

John Blundell, PhD (University of Leeds, UK)

Dr. John Blundell presented positive results on reductions in energy intake and appetite with once-weekly GLP-1 agonist semaglutide in people with obesity. This double-blind, crossover study examined the mechanisms of weight loss of semaglutide (dose-escalated to 1.0 mg) vs. placebo in 30 participants with obesity and without type 2 diabetes (baseline BMI of 34 kg/m2). At 12 weeks, the results found a reduction in body weight, with decreases in energy intake, appetite, and food intake along with overall improved control of eating. Specifically, findings demonstrated that ad libitum energy intake was lower with semaglutide vs. placebo at lunch (5 hours after standardized breakfast), evening meal, and snacks with relative reductions of 35%, 18%, and 22%, respectively. In addition, the semaglutide group achieved weight loss of 5 kg (with greater loss of fat mass compared to lean mass) vs. a small increase of 0.97 kg with placebo. Fasting overall appetite scores also indicated reduced appetite with semaglutide vs. placebo (p=0.0023), while nausea ratings were similar – suggesting that this effect was independent of side effects. Additionally, results from the overall appetite-suppression score and control of eating questionnaire indicated less cravings and greater control of eating. Notably, participants had greater reductions in energy intake of food groups of high fat and traditionally more “appealing” foods, which reflected the results from the Leeds food preference task. Dr. Blundell noted that the semaglutide group experienced a reduction in resting metabolic rate. These findings further confirm to us the impressive versatility of semaglutide, as the product has been suggested to be studied in several indications beyond type 2 diabetes, including NASH, obesity, and a range of macrovascular and microvascular complications – see more on this from our Novo Nordisk 1Q16 report. We have certainly seen significant enthusiasm for the GLP-1 agonist class within obesity – as already pioneered by Novo Nordisk’s Saxenda (liraglutide 3.0 mg) – and the eating behavior-specific findings from this study direct us back to potential mechanisms within the brain and its reward circuitry, which is marking itself as a fast growing area of research for obesity.

Questions and Answers

Q: Do you think the changes in resting metabolic rate are accounted for by the degree of weight loss?

A: Yes, when weight is lost rapidly, the body adjusts. This can drive appetite and make energy expenditure more efficient. When body weight was entered into the analysis as a co-variate, the effect of semaglutide on RMR was no longer significant.

Dapagliflozin + Exenatide QW Reduced Body Weight and Improved Glucose Tolerance in Nondiabetic Obese Adults: A Randomized, Placebo-Controlled, Phase 2 Study

Jan Eriksson, MD, PhD (Uppsala University, Uppsala, Sweden)

Results from a phase 2 proof of concept study (n=50) of combination therapy with AZ’s Farxiga (dapagliflozin) and Bydureon (exenatide once weekly) demonstrated significant ~4 kg weight loss and glycemic improvements vs. placebo in patients with obesity but not diabetes. Participants in the double-blind, single-center study were randomized to receive either active treatment or double placebo for 24 weeks, followed by a 28-week open-label extension study; data from the extension study will be presented at EASD in September. After 24 weeks, the combination led to significant placebo-adjusted weight loss of 4.1 kg (baseline weight = 103-106 kg [227-234 lbs]; baseline BMI = 35-36; p=0.0007) or 4.2% (p=0.0005). As in most obesity drug trials, there was a wide range of responses, but far more patients achieved ≥5% weight loss with the active treatment than with placebo (36% vs. 4%). MRI analysis of body composition showed that almost all of the weight loss was due to loss of adipose tissue, with no significant change in lean tissue. The combination also produced a modest but significant 0.2% placebo-adjusted A1c reduction (baseline = 5.6%, p=0.0004), a significant drop in the proportion of patients with impaired fasting glucose and impaired glucose tolerance, and a significant placebo-adjusted blood pressure reduction of 6.4 mm Hg (p=0.026). Adverse events were fairly balanced, with slightly more GI side effects in the active treatment group.

  • These results are encouraging, though as noted during Q&A, the real test will be how the combination stacks up against each of its components alone. AZ is currently conducting a phase 3 study (n=660) of that comparison in patients with type 2 diabetes that is expected to complete in December 2017 (primary completion May 2016). As presenter Dr. Jan Eriksson noted, GLP-1 agonist/SGLT-2 inhibitor combinations are very appealing for obesity due to their complementary mechanisms of weight loss (calorie loss with the SGLT-2 inhibitor and reduced appetite/caloric intake with the GLP-1 agonist). The same could also be said for glycemic control, as the reduction in glucagon production with GLP-1 agonists could help mitigate the increased glucagon production that blunts some of the efficacy of SGLT-2 inhibitors. We expect AZ to focus primarily on type 2 diabetes with this combination but find the potential in obesity very interesting as well, particularly for a GLP-1 agonist with more potent weight effects like Novo Nordisk’s Saxenda (liraglutide 3.0 mg) or semaglutide.

Questions and Answers

Q: Could you clarify the timing of the last dose vs. the glucose measures?

A: A glucose tolerance test was performed at baseline and at 24 weeks. The dose was taken half an hour before the glucose tolerance test was started.

Q: Although I acknowledge this was a proof of concept trial, why didn’t it include monotherapy + placebo arms? You’re really asking whether there’s a synergistic or additive effect and this study didn’t answer that.

A: It’s a proof of concept for the combination and we showed robust weight loss vs. placebo, but I agree, we want a study against monotherapies as well. That would have increased the study size so we couldn’t have done it at a single center.

Oral Presentations: Hypoglycemia Potpourri

Effects of GLP-1 Infusion on Endothelium and Atherothrombotic Balance During Hypoglycemia in Healthy Individuals

Stephen Davis, MD (University of Maryland, Baltimore, MD)

Dr. Stephen Davis shared results from two randomized, double blind trials (n=22) evaluating the impact of GLP-1 on endothelial health and atherothrombotic balance during hypoglycemia (50 mg/dl) in participants without diabetes. Results showed that atherothrombotic and inflammatory mediators ICAM-1, VCAM-1, PAI-1, E-Selectin, and Endothelin were all reduced during hypoglycemia with GLP-1 infusion as compared to placebo. Further, nitric oxide and other non-nitric oxide mediated vasodilation were also improved with GLP-1 (p<0.05) vs. control. GLP-1 infusion did not significantly impact glucose kinetics, catecholamines, insulin, glucagon, growth hormone, or free fatty acids. According to Dr. Davis, these data indicate that GLP-1 has acute protective effects on endothelial function and reduces pro-atherothrombotic, pro-inflammatory, and pro-coagulant responses during moderate hypoglycemia. We would expect that the protective effects of the GLP-1 infusion would translate to the GLP-1 agonist class and we are especially curious as to how these effects would play out in those with hypoglycemia unawareness and impaired counter-regulatory hormone reactions to hypoglycemia.

Posters

SWITCH 1: REDUCED HYPOGLYCEMIA WITH INSULIN DEGLUDEC (IDEG) VS. INSULIN GLARGINE (IGLAR), BOTH U100, IN PATIENTS WITH T1D AT HIGH RISK OF HYPOGLYCEMIA: A RANDOMIZED, DOUBLE-BLIND, CROSSOVER TRIAL (87-LB)

T Bailey, G Gerety, J Gumprecht, A Philis-Tsimikas, C Hansen, T Nielsen, and M Warren

SWITCH 1 demonstrated significant hypoglycemia reductions with Tresiba vs. Lantus in patients with type 1 diabetes at high risk for hypoglycemia. The double-blind trial randomized 501 patients to receive once-daily doses of Tresiba or Lantus for 32 weeks, followed by crossover to the other treatment for 32 weeks. Each 32-week period consisted of a 16-week titration period and a 16-week maintenance period, and both groups received injections of NovoLog (insulin aspart) at mealtime. Results showed a significant 11% reduction for the primary endpoint of severe or blood glucose-confirmed symptomatic hypoglycemia with Tresiba vs. Lantus during the maintenance period (event rates of 2,220.9 vs. 2,462.7 events/100 patient-years; p<0.0001). Tresiba also produced a significant 36% reduction in severe or blood glucose-confirmed nocturnal symptomatic hypoglycemia (event rates of 277.1 vs. 428.6 events/100 patient-years; p<0.0001) and a significant 35% reduction in severe hypoglycemia (event rates of 69.1 vs. 92.2 events/100 patient-years; p<0.05) in the maintenance period compared to Lantus. Results were similar for the full treatment period with significant reductions of 6%, 25%, and 26% with Tresiba vs. Lantus for the three respective endpoints. The results for other efficacy and safety parameters were comparable between groups; a post-hoc analysis found a 3% significantly lower total daily insulin dose in the Tresiba group.

SWITCH 2: REDUCED HYPOGLYCEMIA WITH INSULIN DEGLUDEC (IDEG) VS. INSULIN GLARGINE (IGLAR), BOTH U100, IN PATIENTS WITH T2D AT HIGH RISK OF HYPOGLYCEMIA: A RANDOMIZED, DOUBLE-BLIND, CROSSOVER TRIAL (90-LB)

A Bhargava, LB Chaykin, R De La Rosa, Y Handelsman, L Troelsen, K Kvist, and P Norwood

SWITCH 2 demonstrated significant hypoglycemia reductions with Tresiba vs. Lantus in patients with type 2 diabetes at high risk for hypoglycemia. The double-blind trial randomized 721 patients to receive once-daily doses of Tresiba or Lantus in addition to oral diabetes drugs (excluding sulfonylureas/meglitinides) for 32 weeks, followed by crossover to the other treatment for 32 weeks, with the same titration/maintenance periods as in SWITCH 1. Results showed a significant 30% reduction in severe or blood glucose-confirmed symptomatic hypoglycemia with Tresiba vs. Lantus during the maintenance period (event rates of 185.6 vs. 265.4 events/100 patient-years; p<0.0001). Tresiba also produced a significant 42% reduction in severe or blood glucose-confirmed nocturnal symptomatic hypoglycemia (event rates of 55.2 vs. 93.6 events/100 patient-years; p<0.0001). Rates of severe hypoglycemia were low in both groups and numerically but not significantly lower with Tresiba (event rates of 5.3 vs. 9.1 events/100 patient-years; p-value not given). Results were similar for the full treatment period with significant reductions of 23% and 25%, respectively, for the first two endpoints and a 51% reduction in severe hypoglycemia that just reached statistical significance (p=0.03). The results for other efficacy and safety parameters were comparable between groups; a post-hoc analysis found a 4% significantly lower insulin dose in the Tresiba group.

Effect of Exenatide Once Weekly on Glycemic Fluctuations in Patients with T2D (1014-P)

J Frias, J Ruggles, S Zhuplatov, S Nakhle, E Klein, R Zhou, L Shi, and P Strange

Dr. Frias et al. conducted a randomized, controlled, double blind study investigating the effects of AZ’s Bydureon (exenatide once weekly) on glucose fluctuations in patients with type 2 diabetes. The study recruited 117 adult patients well-controlled on metformin (A1c 7-10%), who were randomized to open-label metformin XR (1500 or 2000mg daily) plus double-blinded Bydureon 2.0 mg (n=61) or placebo (n=56). Glucose concentration was measured via the Dexcom G4 CGM every 5 minutes during the last week before randomization (baseline), as well as during weeks 4 and 10. Compared to placebo, Bydureon provided significantly greater reductions in 24-h mean glucose on day six of week four (5.3 mg/dl vs. 26.0 mg/dl, respectively) and on day six of week 10 (3.0 mg/dl vs. 30.8 mg/dl, respectively).  Similar results were observed for fasting plasma glucose (FPG), postprandial glucose (PPG), and mean amplitude of glycemic excursions (MAGE) (please see table 1 below). Those on Bydureon experienced a significant increase in the time spent in euglycemia (70-180 mg/dl) from baseline to week four and week 10 (p<0.001 for both) – this was secondary to reductions in time spent in hyperglycemia (>180 mg/dl), with no increase in the time spent in hypoglycemia (<70 mg/dl); the finding was not observed in the placebo group. The authors concluded that Bydureon provides robust effects on measures of glycemic fluctuation at week four that persist to week 10.

  • Both groups had eight patients withdraw from the study, leading to a retention rate of 87% in the exenatide group (53 patients analyzed) and of 86% in the placebo group (48 patients).
  • Baseline characteristics were comparable between the two groups, with an average age of 55-56 years, percent male of 55-57%, similar race breakdown, duration of diabetes of 9-10 years, pre-trial metformin dose of 1,875-1,925 mg, body weight of 90-91 kg, BMI of 32, A1c of 8.0-8.2%, fasting plasma glucose of 168-178 mg/dl, 2-h mean post-prandial glucose of 221 mg/dl, 24-h mean glucose of 184-186 mg/dl, and MAGE of 90-91.

Table 1: Effect of Bydureon vs. placebo on measures of glucose control and fluctuation

 

Bydureon group

Placebo group

p value

 

Change in 24-h mean glucose from baseline

Week 4, day 6

-26.0

-5.3

p <0.001

Week 10, day 6

-30.8

-3.0

p <0.001

 

Change in fasting plasma glucose, from baseline

Week 4, day 6

-29.6

-1.9

p <0.001

Week 10, day 6

-41.9

-5.0

p <0.001

 

Change in post-prandial glucose (after standard meal), from baseline

Week 4, day 6

-32.1

-2.0

p <0.001

Week 10, day 6

-44.4

-6.0

p <0.001

 

Change in mean amplitude of glucose excursions

Week 4, day 6

-8.2

-3.8

---

Week 10, day 6

-15.2

+2.9

p <0.001

Table: Effect of Bydureon vs. placebo on time spent in euglycemia and hyperglycemia

 

Time spent in euglycemia (70-180 mg/dl)

 

Baseline

Week 4

Week 10

EQW group

53%

71%*

77%#

Placebo group

55%

60%

58%

 

Time spent in hyperglycemia (>180 mg/dl)

 

Baseline

Week 4

Week 10

EQW group

47%

29%

22%

Placebo group

45%

40%

42%

  Numeric data was not provided for time spent in the hypoglycemia range (<70 mg/dl)

  * p<0.001 for baseline vs. week 4 in the EQW group

  # p<0.001 for baseline vs. week 10 in the EQW group

  • Serious adverse events were observed in four patients in the Bydureon group (one case each of acute pancreatitis, non-cardiac chest pain, chest pain, and nephrolithiasis), as well as in one patient in the placebo group (upper respiratory tract infection). The investigators considered these events to be unrelated to treatment.

Consistent Outcomes Across Dose Ranges with Titratable LixiLan, Insulin Glargine/Lixisenatide Fixed-Ratio Combination, in the LixiLan-O Trial (1017-P)

R Henry, B Ahrén, M Davies, Y Wu, Y Handelsman, E Souhami, E Niemoeller, and J Rosenstock

Sanofi presented data from the LixiLan-O trial showing that iGlarLixi (formerly LixiLan; lixisenatide/insulin glargine) was consistently safe and effective and produced minimal weight gain across all dose ranges. Primary results from the trial presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. either component alone in patients with type 2 diabetes not at goal on oral medications. During the trial, the dose of insulin glargine (Lantus) was titrated weekly in both the iGlarLixi and insulin glargine groups to a fasting plasma glucose target of 80-100 mg/dl, with a cap of 60 U/day (the maximum dose available in the combination). In the iGlarLixi group, two different pens with different insulin glargine/lixisenatide fixed ratios were used depending on the required dose of insulin glargine. Patients requiring 10-40 U/day of insulin glargine were treated with the lower-dose pen (ratio of 2 U insulin glargine/1µg lixisenatide), while those requiring insulin glargine doses of 30-60 U/day were treated with the higher-dose pen (ratio of 3 U insulin glargine/1 µg lixisenatide). In this analysis, patients in the iGlarLixi group were divided into subgroups based on their final doses of insulin glargine (≤10-<20 U, ≥20-30 U, ≥30-≤40 U, and >40-≤60) and lixisenatide (≥5-<10 µg, ≥10-<15 µg, and ≥15-≤20 µg). A1c reductions, the percentage of patients achieving an A1c <7%, and the incidence of hypoglycemia in the iGlarLixi group were consistent across all dose categories, and the weight gain seen with insulin glargine alone was mitigated with all doses of iGlarLixi. The incidence of nausea/vomiting was low, which the authors attributed to the gradual titration of lixisenatide.

Impact of Baseline HbA1c, BMI, and Diabetes Duration on the Efficacy and Safety of LixiLan (Insulin Glargine/Lixisenatide Titratable Fixed-Ratio Combination) vs. Insulin Glargine and Lixisenatide in the LixiLan-O Trial (1028-P)

M Davies, L Leiter, G Grunberger, FJ Ampudia-Basco, B Guerci, C Yu, W Stager, E Niemoeller, E Souhami, and J Rosenstock

This analysis of the LixiLan-O trial demonstrated consistent efficacy and safety with Sanofi’s iGlarLixi (formerly LixiLan; lixisenatide/insulin glargine) across subgroups divided by baseline A1c, diabetes duration, and BMI. Primary results presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. either component alone in patients with type 2 diabetes not at goal on oral medications. In this analysis, participants were separated into groups by baseline A1c (<8% or ≥8%), duration of type 2 diabetes (<7 or ≥7 years) and BMI (<30 or ≥30 kg/m2). After 30 weeks, the results for A1c reductions, the percentage of patients with an A1c <7%, and hypoglycemia were consistent across all subgroups. iGlarLixi consistently led to significantly greater A1c reductions (~0.3% vs. insulin glargine and 0.7%-0.9% vs. lixisenatide) and more patients achieving an A1c <7% compared to both components; hypoglycemia was comparable between the iGlarLixi and insulin glargine groups. See the table below for detailed results.

Subgroup

iGlarLixi

Insulin Glargine

Lixisenatide

 

A1c Reduction

A1c <7%

Hypoglycemia

A1c Reduction

A1c <7%

Hypoglycemia

A1c Reduction

A1c <7%

Hypoglycemia

A1c <8%

1.2%

83.8%

23.0%

0.8%

67.7%

22.4%

0.5%

50.5%

5.5%

A1c ≥8%

1.9%

69.8%

27.9%

1.6%

53.9%

24.6%

1.1%

19.4%

7.3%

Duration <7 years

1.5%

75.2%

21.3%

1.2%

61.9%

19.0%

0.8%

37.5%

7.3%

Duration ≥7 years

1.6%

72.6%

28.8%

1.3%

57.4%

27.2%

0.7%

29.9%

5.8%

BMI <30 kg/m2

1.6%

78.6%

31.6%

1.2%

57.9%

29.1%

0.7%

28.4%

12.0%

BMI ≥30 kg/m2

1.5%

75.2%

22.0%

1.3%

62.2%

20.1%

0.8%

36.5%

3.8%

Efficacy and Safety of LixiLan vs. Insulin Glargine According to Baseline Characteristics in Patients with Type 2 Diabetes from the Lixilan-L Trial (1018-P)

C Wysham, R Bonadonna, V Aroda, MP Domingo, C Kapitza, W Stager, C Yu, E Niemoeller, E Souhami, and R Bergenstal

This analysis from the LixiLan-L trial demonstrated consistent efficacy and safety with Sanofi’s iGlarLixi (formerly LixiLan; insulin glargine/lixisenatide) across subgroups divided by baseline A1c, diabetes duration, and BMI. Primary results from the trial presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. insulin glargine (Lantus) in patients not at goal on basal insulin. In this analysis, participants were divided into groups based on their baseline A1c (<8% or ≥8%), time since diagnosis of type 2 diabetes (<10 or ≥10 years), and BMI (<30 or ≥30kg/m2). After 30 weeks, the results for A1c reduction, percentage of patients with an A1c <7%, and hypoglycemia were consistent across all subgroups. iGlarLixi consistently led to ~0.5% greater A1c reductions and ~20-30% more patients achieving an A1c <7% compared to insulin glargine, and there were no significant differences in hypoglycemia between treatment groups. iGlarLixi also offered a significant weight benefit vs. insulin glargine in subgroups divided by baseline A1c and BMI (results for duration of diabetes subgroups not given. See the table below for detailed results. 

Subgroup

iGlarLixi

Insulin Glargine

A1c Reduction

Percentage with A1c <7%

Hypoglycemia Incidence

A1c Reduction

Percentage with A1c <7%

Hypoglycemia Incidence

A1c <8%

0.8%

67.5%

32.7%

0.3%

45.4%

42.3%

A1c ≥8%

1.4%

44.5%

46.0%

0.8%

16.8%

42.6%

Duration <10 years

1.1%

56.0%

41.0%

0.6%

35.3%

36.7%

Duration ≥10 years

1.1%

54.3%

39.2%

0.6%

25.7%

46.7%

BMI < 30 kg/m2

1.1%

58.3%

47.7%

0.5%

27.6%

50.0%

BMI ≥30 kg/m2

1.1%

52.4%

34.3%

0.6%

31.1%

36.8%

Liraglutide Protects Diet Induced Obesity Through Induction of Brown Adipogensis in Mice (1966-P)

J Zhou, P Chandramani-Shivalingappa, and L Li

This poster presented data showing that liraglutide (Novo Nordisk’s Victoza/Saxenda) reduced weight gain and obesity-related inflammation and upregulated genes related to brown fat tissue synthesis in mice. The experiment was conducted on four groups of C57black/6 mice that were fed either a normal (control) or a high fat sucrose diet (HFHSD) and were injected with either liraglutide or saline for five weeks. The mice were then massed and liver, fat and skeletal muscle tissue samples were taken for protein and RNA extraction. The results showed that liraglutide reduced weight gain and inflammation in mice fed a HFHSD to levels comparable to those of the mice receiving saline injections and eating a normal diet. Liraglutide also decreased paragonadal fat mass in HFHSD mice while inducing the expression of UCP-1 (a protein in brown adipose tissue that increases thermogenesis and metabolic rate) and three other related genes: PPAR-alpha, Cidea, CEBP-alpha and CEBP-beta. Liraglutide did not have any effect on fatty acid oxidation or synthesis. This study provides additional mechanistic explanations for the positive clinical results seen with liraglutide in obesity – in particular, we have not heard as much discussion about the connection to brown fat as we have about neural mechanisms of weight regulation – in fact, we haven’t heard too much about brown fat as of late at all – a big change of late.

IDegLira is Efficacious Across Baseline HbA1c Categories in Subjects with Type 2 Diabetes Uncontrolled on SU, GLP-1RA or Insulin Glargine: Analyses From Completed Phase 3b Trials (925-P)

C Sorli, S Harris, E Jódar, I Lingvay, K Chandarana, J Langer, and E Jaeckel

Novo Nordisk presented a post hoc analysis of the phase 3b DUAL trials for GLP-1 agonist/basal insulin combination IDegLira (Xultophy; insulin degludec/liraglutide), showing that the drug’s efficacy was consistent regardless of baseline A1c. The analysis included populations uncontrolled on a GLP-1 agonist (DUAL III; IDegLira vs. continued GLP-1 agonist therapy), a sulfonylurea (DUAL IV; IDegLira vs. placebo) and insulin glargine (DUAL V; IDegLira vs. continued insulin glargine therapy). Patients in each trial were split into three different baseline A1c categories: ≤7.5%, >7.5-≤8.5% and >8.5%. In all categories, IDegLira led to significantly greater A1c reductions than the comparator therapy; as expected, the greatest reductions occurred in the highest baseline A1c category. See the table below for detailed results. Perhaps most impressively, IDegLira led to a mean final A1c <7% in all categories, underscoring its status as one of the most efficacious and versatile type 2 diabetes drugs available.

Table: A1c Reductions Across Baseline A1c Categories in the DUAL Trials

 

Overall

Baseline A1c ≤7.5%

Baseline A1c >7.5%-≤8.5%

Baseline A1c ≥8.5%

DUAL III

IDegLira (n=292): -1.3%

IDegLira (n=113): -1.0%

IDegLira (n=141): -1.4%

IDegLira (n=38): -1.9%

 

GLP-1 (n=146): -0.3%

GLP-1 (n=66): -0.3%

GLP-1 (n=66): -0.3%

GLP-1 (n=14): -1.0%

DUAL IV

IDegLira (n=289): -1.5%

IDegLira (n=93): -1.0%

IDegLira (n=156): -1.5%

IDegLira (n=40): -2.1%

 

Placebo (n=146): -0.5%

Placebo (n=48): -0.2%

Placebo (n=80): -0.6%

Placebo (n=18): -0.7%

DUAL V

IDegLira (n=278): -1.8%

IDegLira (n=63): -1.0%

IDegLira (n=102): -1.6%

IDegLira (n=113): -2.5%

 

IGlar (n=279): -1.1%

IGlar (n=64): -0.5%

IGlar (n=118): -1.0%

IGlar (n=97): -1.7%

P=0.004 for DUAL III baseline A1c ≥8.5%; p<0.001 for all other categories

ITCA 650: A Novel Therapeutic Approach to Treating Type 2 Diabetes (1027-P)

A Whitson, R Azeem, T Alessi, and M Baron

Intarcia presented a poster sharing the company’s experience with the safety and tolerability of the implantation, replacement, and removal of their ITCA 650 exenatide mini-pump thus far from the FREEDOM phase 3 development program for the product. As of November 2015, physicians, registered nurses, and physician assistants had performed 18,383 placements, replacements, and removals of the product in 5,200 patients with type 2 diabetes across 493 clinical sites in 28 countries. There were no serious AEs observed and the poster characterized overall adverse events related to the procedure as generally mild, transient, and reflective of normal healing. Only 1% of procedures were originally unsuccessful (mostly because they were placed too deep in the skin). 0.19% of procedures resulted in discontinuation of treatment and 0.4% resulted in inadvertent expulsion/extrusion (Intarcia noted that this rate is lower than that seen in clinical trials of other implanted drugs). The experience of the implantation and removal procedure has been one of the biggest questions surrounding the potential uptake of ITCA 650. We will look forward to hearing from patients on what they thought of the procedure. Does it hurt? Is the implantable noticeable or uncomfortable post-placement? How easy is removal? A soon-to-be-published paper on treatment satisfaction outcomes in the phase 2 study for ITCA 650 should shed more light on these questions. All in all, these results demonstrating minor adverse events related to the procedure itself are reassuring and we hope bode well for future patients and physician acceptance of this novel delivery mechanism.

DURATION-1 Extension in Patients with T2D: Efficacy and Tolerability of Exenatide Once Weekly (QW) Over 7 Years (1041-P)

CH Wysham, A Philis-Tsimikas, EJ Klein, P Öhman, N Iqbal, J Han, and RR Henry

Findings of the seven-year extension period of the DURATION-1 study demonstrated that exenatide (QW) therapy for seven years was associated with significant, sustained reductions in A1c and weight, with infrequent insulin initiation and no new long-term safety findings. As background, the DURATION-1 study was a 30-week study that compared exenatide QW and twice daily in 295 patients with type 2 diabetes. During this seven-year extension period, patients received exenatide once weekly and visited every eight weeks during this period; glucose-lowering medication usage was noted and glycemic and weight data were analyzed. While there were 295 initial patients, 122 patients completed the extension period – while some of this was “regular” fall-off due to patients moving away and other typical reasons (see below), we do not have data on approximately 40% and we would be very curious to know how many patients left to go on other therapy like once weekly GLP-1, SGLT-2s, etc. Specifically, withdrawal reasons included withdrawn consent (27%), adverse events (12%), investigator decision (7%), lost to follow-up (7%), and glucose control lost (4%). Of the completers, 57 added a new glucose-lowering medication. Concomitant medications included metformin (84%), SFUs (59%), and TZDs (24%); 2% added long-acting insulin in years 2-5, 9% in year 6, and 12% in year 7. For those who followed through with the 7-year extension period, A1c decreased, FPG was significantly below the baseline after the extension period, and body weight decreased (the greatest decreases in body weight occurred in patients that did not take any new glucose-lowering medications). Specifically, at seven years, 46% of participants had A1c <7.0% and 30% had A1c ≤6.5%. Mean reductions at seven years were 1.5% in A1c (baseline of 8.2%); 24 mg/dl in FPG (baseline of 166 mg/dl); and 3.9 kg in weight (baseline of 101 kg). Even though there was a gradual increase in these three categories over time, the authors believed that this probably resulted from the time period’s progression of diabetes, which makes sense. As for safety, out of all the patients who participated in the study, there were 71 serious adverse events, though mild GI and injection site adverse events primarily occurred in the initial 30 weeks. Ultimately, these findings show that the benefits of exenatide appear to be sustained over years of continued use, with no new long-term safety findings and very impressive duration of effect.

Symposium: Heart Failure and Diabetes

GLP-1 RA and Cardiovascular Physiology – Will the Clinic Ever Confirm the Mechanistic Studies?

Mansoor Husain, MD (University of Toronto, Toronto, Canada)

Dr. Mansoor Husain presented various mouse and human studies demonstrating how incretin-targeted therapies affect the cardiovascular system through glycemic control, lipid control, weight loss, endothelial function, sodium and fluid excretion, blood pressure control, anti-inflammatory effects, plaque composition, a small increase in heart rate, cardioprotection in ischemia, and improved left ventricle function in heart failure. Dr. Husain also noted that although these effects apply to multiple incretin classes, GLP-1 agonists typically have a greater impact than DPP-4 inhibitors, as they lead to pharmacological levels of GLP-1 whereas DPP-4 inhibitors simply protect endogenous GLP-1 from degradation. Throughout the talk, Dr. Hussein kept returning to the idea that people who have diabetes have a slightly different profile of HFpEF and HFrEF (heart failure with preserved ejection fraction vs. heart failure with reduced ejection fraction) than those without diabetes. Dr. Husain also reviewed an analysis of studies examining the relationship between heart failure and intensive glucose lowering, remarking that the increased risk of heart failure with intensive treatment seems to be mostly attributed to TZDs rather than DPP-4 inhibitors (few GLP-1 agonists were evaluated in the review). Dr. Husain also presented results from a resent observational study (Filion et al, N Engl J Med, 2016) demonstrating that hospitalizations for heart failure did not increase with incretins vs. other oral anti-diabetic drugs for those with or without a history of heart failure. Finally, Dr. Husain pointed to the results from the LEADER trial for Novo Nordisk’s Victoza (liraglutide) to highlight the potential impact that cardioprotective drugs could have on patients.

Questions and Answers

Q: How many patients do you see with heart failure, and what do you do when you see them? How do you follow up?

A: I consistently look for symptoms of heart failure, through a simple evaluation. I do this all on routine basis. However, if I see signs or symptoms, I move to image-based evidence to check to see if it is reduced ejection fraction or if the ejection fraction is preserved. Then, I make sure that blood pressure is well controlled.

Corporate Symposium: New Therapeutic Advances and Practical Strategies for Complementary Basal Insulin Plus Incretin System – Targeted Agents in Complex Patients with Diabetes (Supported by Sanofi Diabetes)

Summary

Lawrence Blonde, MD (Ochsner Medical Center, New Orleans, LA); Juan Pablos Frias, MD (National Research Institute, Los Angeles, CA); Lawrence Leiter, MD (St. Michael’s Hospital, Toronto, Canada); Julio Rosenstock, MD (Dallas Diabetes and Endocrine Center, Dallas, TX)

Dr. Julio Rosenstock opened the symposium with a discussion on the physiological basis for combination therapy and complementary pharmacologic approaches and mechanisms. He reviewed the current research on the combination of basal insulin with complementary therapies such as GLP-1 agonists to treat fasting plasma glucose and postprandial glucose in people with type 2 diabetes and addressed several key factors that affect patient adherence to glucose lowering medications, ultimately emphasizing that the GLP-1/basal insulin combination carries a low hypoglycemia risk and balances insulin’s weight gain effects. Dr. Lawrence Leiter followed with a presentation on the role of post-prandial glucose (PPG), as he stressed that it contributes substantially to A1c and elevated PPG is associated with increased cardiovascular risk, especially in those on basal insulin and those older than 65 years. After reviewing evidence, he emphasized that prandial GLP-1 agonists have greater effects on gastric emptying and PPG compared to non-prandial GLP-1s, nicely complementing the effects of basal insulin on fasting glucose. Next, Dr. Lawrence Blonde gave an overview of the ADA/EASD roadmap for the management of type 2 diabetes and the differing roles of FPG and PPG dysregulation in contributing to overall hyperglycemia, as he highlighted the guidelines’ stated role of basal insulin. Lastly, Dr. Juan Pablos Frias closed out with a discussion on the practical and mechanistic role of GLP-1 agonists for managing PPG in basal inuslin-treated patients, highlighting that this patient population typically requires additional PPG control and that currently available fixed-dose combinations may offer significant benefits with regards to side effects.

Panel Discussion

Q:  Why should you take lixisenatide when liraglutide has been shown to reduce cardiovascular events? What are the differences between ELIXA and LEADER?

Dr. Leiter: These trials differ in ways beyond the drugs that were tested. The LEADER trial was done in patients with stable cardiovascular disease where patients had acute coronary symptoms in the ELIXA trial. Eighty percent of patients in LEADER had cardiovascular disease while 20% did not. We don’t yet know the results of LEADER but we know that the starting A1c was higher, about 8.7%. In the absence of head-to-head trials it’s difficult to come to a definite conclusion. It appears that the result from LEADER is positive and that ELIXA is neutral but we don’t know if they were used in different clinical settings. The patients with acute coronary syndrome in ELIXA may be the right population to show safety and the wrong population to show efficacy – but it’s because the FDA asked for safety and not efficacy. Patients with post acute coronary syndrome have a lot of cardiovascular events so it’s an efficient way to do a study for safety.

Q: Is there any evidence or rationale in terms of protective effects of GLP-1 agonists on beta cell function?

Dr. Leiter: If you look at beta cell function as opposed to beta cell mass, there are some studies where, compared to insulin, the GLP-1 agonists do a better job of improving beta cell function. There was a three-year study with exenatide compared to basal insulin and in that time, there was better beta cell function after using exenatide than when the patients were on insulin. This is with exenatide three times a day.

Dr. Rosenstock: It is conceivable that if you give short acting GLP-1 agonists, it reduces gastric emptying and there is less insulin and less exposure of nutrients to beta cells. Theoretically, for people with advanced diabetes, it is more dependent on gastric emptying.

Dr. Blonde: If you look at trials, almost all of them gave agents to people with longer duration of diabetes who are using two or more oral agents, and they got substantially good benefits. It appears beta cell function can be improved. They didn’t use clamps but the idea is that most people with type 2 diabetes can lose beta cells but it may be reversible with appropriate treatments.

SGLT-2 Inhibitors

Symposium: Update from the EMPA-REG OUTCOME Trial

Introduction, Context, and Cardiovascular Outcomes

Bernard Zinman, MD (Mount Sinai Hospital, University of Toronto, Ontario, Canada)

In this presentation, Dr. Bernard Zinman introduced the symposium by reviewing the design and findings of the EMPA-REG trial. Most notably, he presented new sub-analysis data, showing that the heart failure and cardiovascular death outcomes of the EMPA-REG trial for Lilly/BI’s Jardiance (empagliflozin) were consistent across age groups. Also presented in two posters, the analyses stratified the results by three baseline age groups (<65, 65-75, ≥75 years). For cardiovascular death, the hazard ratios were 0.72, 0.54, and 0.55 for the age groups, respectively by increasing age group (p=0.484 for the treatment by age group interaction). Regarding hospitalization for heart failure, hazard ratios were 0.73, 0.66, and 0.45 for the respective increasing age groups (p=0.488 for the treatment by age group interaction). In addition, the analyses calculated the collective hazard ratios for heart failure hospitalization or cardiovascular death: 0.79, 0.59, and 0.52 for the respective increasing age groups (p=0.240 for the treatment by age group interaction). The time to cardiovascular death and heart failure hospitalization appeared to remain mostly consistent across baseline age groups. The analyses also found that reported adverse events were consistent with the known safety profile of Jardiance across age subgroups. The percentage of participants reporting one or more adverse events in the empagliflozin arm was 89.1%, 91.8%, and 90.8% in the <65, 65-75, and ≥75 years age groups, respectively. Specifically, the proportion of participants who reported events consistent with urinary tract infection (15% vs. 20% vs. 26%), volume depletion (4% vs. 7% vs. 7%), and bone fracture (3% vs. 5% vs. 5%) tended to increase with increasing age. These findings support the broad use of Jardiance by age group and hopefully provide further color on how to incorporate the EMPA-REG findings into treatment algorithms, as we look forward to further sub-analyses to provide stronger evidence on the guidance for better personalizing therapy.

Update on Microvascular Outcomes

Christoph Wanner, MD (University of Würzburg, Germany)

Dr. Christoph Wanner presented full renal outcomes results from EMPA-REG OUTCOME demonstrating a significant 39% risk reduction for diabetic nephropathy with Lilly/BI’s Jardiance (empagliflozin). The results were also published in the NEJM this morning. The hazard ratio for the main renal endpoint of incident or worsening nephropathy (progression to macroalbuminuria or doubling of serum creatinine accompanied by eGFR ≤45 ml/min/1.73 m2 or renal replacement therapy or death due to renal disease) was 0.61 (95% CI: 0.53-0.70; p<0.001). As with the cardiovascular outcomes, the effect appeared early and was sustained throughout the trial; there was no difference between the 10 mg and 25 mg doses of empagliflozin. The results were essentially the same for the combined endpoint of incident or worsening nephropathy or CV death (HR = 0.61; 95% CI: 0.55-0.69; p<0.001). Subgroup analyses demonstrated a consistent effect in subgroups divided by CKD stage, age, sex, race, diabetes duration, A1c, BMI, blood pressure, and concomitant medications. New onset macroalbuminuria was the most common event and therefore demonstrated the most robust results (HR = 0.62; 95% CI: 0.54-0.72; p<0.0001). The effect for hard renal outcomes (doubling of serum creatinine, renal replacement therapy, or death due to renal disease) took longer to appear but was also highly significant by the end of the trial (HR = 0.54; 95% CI: 0.40=0.75; p<0.001). There was no significant risk reduction for incident albuminuria in patients with normal urinary albumin levels at baseline, suggesting that the benefit is likely exerted later in the progression of CKD. There was no signal for adverse events including hypoglycemia, urinary tract infections, acute kidney injury, bone fractures, hyperkalemia, or DKA in patients with impaired kidney function, which should help support a label update to remove the current contraindication for patients with renal impairment.

  • Dr. Wanner outlined one potential mechanism for the positive renal effects, centered around a reduction in glomerular hypertension. He explained that diabetes leads to increased reabsorption of sodium and glucose in the proximal tubule and decreased delivery of sodium to the macula densa. Because the macula densa regulates the glomerular filtration rate based on the amount of sodium it senses, the abnormally low delivery of sodium leads to hyperfiltration. With SGLT-2 inhibition, more glucose and sodium reaches the macula densa, leading to an initial drop in glomerular pressure and glomerular filtration rate. While this short-term decline in GFR initially led to concerns that SGLT-2 inhibitors might be harmful to the kidneys, over the long term the restoration of tubulo-glomerular feedback and reduced glomerular hypertension appears to be quite beneficial. This model is the closest thing to a consensus hypothesis we have heard for the mechanism of renal protection with SGLT-2 inhibitors, though we also heard an intriguing alternative hypothesis related to fuel energetics earlier this week.

Further Insight into the Findings – Mediation Analysis (Results)

Silvio Inzucchi, MD (Yale School of Medicine, New Haven, CT)

Dr. Silvio Inzucchi (Yale School of Medicine, New Haven, CT) presented a covariate mediation analysis of the EMPA-REG OUTCOME results, suggesting that increased hematocrit (presumably as a reflection of plasma volume) was a significant (but still just a partial) contributor to the impressive 38% risk reduction for cardiac death with Lilly/BI’s Jardiance (empagliflozin). The analysis looked at several potential mediators of the effect related to glycemia (A1c, fasting plasma glucose [FPG]), vascular tone (systolic blood pressure, diastolic blood pressure, heart rate), lipids (HDL cholesterol, LDL cholesterol, triglycerides), renal factors (log urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate [eGFR]), adiposity (weight, BMI, waist circumference), volume status (hematocrit), and other (uric acid). The analyses involved a “change from baseline” analysis to determine if a covariate may have an acute effect on the outcome and a “updated mean” analysis to determine if it may have a chronic effect on the outcome. The change from baseline analysis found that adjustment for hematocrit levels produced a hazard ratio of 0.791 for cardiovascular death, suggesting that decrease in plasma volume could potentially explain nearly 52% of the overall effect of empagliflozin on cardiovascular death. Adjustment for uric acid levels yielded the second largest change in effect (24%), suggesting it may also have some role, though Dr. Inzucchi noted, however, that any percent change in effect under 30%-40% is unlikely to indicate a significant major mediator of the cardiovascular death effect.

  • In the updated mean analysis of potential chronic factors, hematocrit levels once again emerged as a significant potential mediator of the effect. Adjustment for hematocrit produced a hazard ratio again of 0.791 for cardiovascular death, also a 52% change in the overall effect. Analysis for other volume-related factors such as hemoglobin and albumin also suggested a potential effect: hemoglobin levels accounted for 45.7% of the overall effect and albumin levels for 31.6% of the overall effect. In this analysis, A1c and FPG appeared to affect the outcome more than in the “change from baseline” analysis, with adjustment resulting in a 23% and 29% change in effect, respectively. Overall, however, Dr. Inzucchi concluded that hematocrit appeared to by the most likely potential mediator for the effect, warranting further study to investigate this hypothesis. He did, however, acknowledge that there could be other factors not measured in the EMPA-REG OUTCOME trial that could have mediated some of the effect on cardiovascular death.  Others have proposed that a slight increase in ketone bodies produced by SGLT-2 inhibitors may provide a more efficient fuel source for the heart and that this may be an important mediator as well.

Discussant

William Herman, MD (University of Michigan, Ann Arbor, MI)

Discussing both the cardiovascular and renal outcomes results, Dr. William Herman argued that EMPA-REG OUTCOME is a game-changer but one with important caveats. He stressed that the very impressive results need to be interpreted strictly in the context of the eligibility criteria for the trial, meaning they should be applied only to older patients with established CVD. He also noted that the results could reflect the reduced use of potentially harmful medications like insulin and sulfonylureas rather than a specific beneficial effect of empagliflozin. Dr. Anne Peters (USC, Los Angeles, CA) offered a similar theory yesterday with regard to the LEADER results for Novo Nordisk’s Victoza (liraglutide). It is an interesting theory in both cases, though it seems unlikely that it would explain the entire benefit in EMPA-REG OUTCOME given the lack of a hypoglycemia difference between the groups and the dramatic and specific benefits on heart failure and CV death with empagliflozin. For patients with earlier-stage type 2 diabetes, Dr. Herman suggested that selection of SGLT-2 inhibitors as a second-line therapy should still be based on the criteria outlined in the ADA guidelines, including efficacy (moderate), hypoglycemia risk (low), weight effect (beneficial), side effects (genitourinary infections), and cost (expensive). In terms of the mechanism of benefit, Dr. Herman suggested that a sum of small effects (on A1c, weight, blood pressure, etc.), decreased plasma volume, renal effects, or alternative fuel sources are all plausible hypotheses. Several of these issues were discussed in more detail during Q&A – see below for a full transcript.

Panel Discussion

Q: The known factors like blood pressure are very important here. As Dr. Wanner pointed out, the IDNT and RENAAL studies controlled for blood pressure. The FDA requires control of blood pressure for renal endpoints. Even if the FDA didn’t care to control for blood pressure in this setting, why didn’t the sponsor? We’re left with a choice between the Cox analysis and scratching our heads.

Dr. Bernard Zinman (Lunenfeld-Tanenbaum Research Institute, Toronto, Canada): The vast majority of patients with type 2 diabetes do have hypertension and the vast majority are on two or three blood pressure medications. I think the blood pressure we reported here was very similar to other studies like this. I think this is the reality of the kind of blood pressure we can achieve in a global setting. I’m not sure whether you’re implying we should’ve intensified blood pressure therapy before randomization? When you look at the difference in blood pressure, there was no difference in the outcome.

Q: Why wasn’t it treated to target in both arms?

Dr. Zinman: It was.

Q: Not successfully.

Dr. Zinman: The target A1c is <7% and I’d like to know how many people in this audience have all their patients under 7%. We didn’t actively intervene on blood pressure or lipids; we left it to the local physicians and they did the best they could. It didn’t in any way affect the outcome.

Dr. Matthew Riddle (OHSU, Portland, OR): This was a relatively advanced CV risk population and quite a few with existing nephropathy. Was this a surprising systolic blood pressure for this population?

Dr. Christoph Wanner (University of Würtzburg, Germany): I’m quite happy with the blood pressure we achieved. Remember in the IDNT and RENAAL trials they had higher blood pressure and the committee hammered on the investigators to bring the blood pressure down. Here we are in a range where we have quite sophisticated blood pressure-lowering agents. A meta-analysis in CKD did not indicate that further lowering would have a benefit. It’s not proven in type 2 diabetes but at least in CKD that’s true.

Q: I understand the mechanism is unclear, but Dr. McGuire suggested that the mechanisms were different for LEADER and EMPA-REG OUTCOME so the combination might be beneficial. If the alternative fuel hypothesis is true, liraglutide shuts down beta-hydroxybutyrate production, so you might lose at least this part of the effect. You shouldn’t just combine them. If you think we should, we need a combined study.

Dr. Zinman: I can’t agree more. You don’t know until you actually do it. A good example is combining ACE inhibitors and ARBs. I already asked how many people in the room are using GLP-1 agonists and SGLT-2 inhibitors and 60% of hands went up. It’s being done, but you’re correct that we need to study it more. It will take awhile, but we need to look at surrogates, hemodynamic responses, and metabolic responses. Several companies are initiating combination studies. We can’t just assume it will be additive.

Q: One thing you mentioned in your slide was oxidative stress, but it wasn’t further discussed, probably because it’s hard to measure. There are ways to measure the end products of oxidative stress if samples are available, and we had two posters here showing that it was correlated with cardiovascular endpoints in the VADT. If samples are available, some investigation could be telling.

Dr. Silvio Inzucchi (Yale University, New Haven, CT): I agree. These trials teach you that you should have saved more samples. We’re somewhat restricted to what we measured at baseline. We don’t have blood left over. It’s led to a lot of speculation.

Q: It’s interesting that the renal effects of empagliflozin were maintained in patients with a GFR under 45. That’s the level at which we’re not meant to be using the drug according to the label. Was there an analysis of cardiovascular outcomes in that subgroup?

Dr. Inzucchi: There was no heterogeneity of effect based on sub-category of GFR. There was a consistent effect for heart failure hospitalization and CV death in those patients.

Q: You showed that for an eGFR <60. What about under 45?

Dr. Wanner: If you look at stage 3 CKD, the reduction in CV outcomes was similar in the two sub-categories and very consistent. CV outcomes were reduced in even stage 3b, which is eGFR <45. But the n was small.

Q: Do you think the hematocrit increase or plasma volume decrease could also explain the imbalance in stroke?

Dr. Inzucchi: One caution is that when we looked at the stroke outcomes, most of the imbalance occurred in patients who had stopped the study drug. We’re still analyzing it but it is a bit of a curious finding. A reduction in circulating plasma volume and the potential for sludging from increased hematocrit is something we’ve considered. A change in hematocrit from a mean of about 41 to about 44 shouldn’t really change plasma viscosity, but there certainly could be outliers. We are now looking at that specific question – were hematocrit or volume-related adverse events associated with stroke – so far, the answer is no.

Q: As a clinician I’m being persuaded to use this drug. Do you have advice on how to treat mycotic infections? Do you stop the drug if they occur?

Dr. Zinman: In the trial there were not a lot of recurrent infections. Patients tend to treat themselves with over the counter drugs. My own practice is that if a patient had recurrent infections as part of their history of diabetes, I wouldn’t use this class. Similarly, if they have a history of pancreatitis I tend not to use DPP-4 inhibitors. You need to individualize, but in my experience it’s not a big problem. The one patient I had with recurrent infections was a male who got balanitis and although it was treated he got a recurrence and stopped the drug. It’s generally not a problem.

Dr. Inzucchi: I agree that if there are recurrent adverse events from any medication, you need to avoid them. I treat the infections with topical antifungals.

Q: What is your explanation for the increase in creatinine at the onset of treatment?

Dr. Wanner: The increase in creatinine and drop in GFR is because of the reduction in intraglomerular pressure and hyperfiltration. It varies; it can be neutral but it can be quite substantial initially. We know from the ACE inhibitors, where we have a longer history of looking into this, that the more intraglomerular pressure or GFR drops at the beginning, the more the patient benefits long term in terms of RAS blockade. We have to look into it in terms of the SGLT-2 inhibitors, but for the moment I would assume it’s the same.

Q: Hepatic injury was statistically reduced. What was the definition and absolute numbers?

Dr. Zinman: We didn’t specifically measure hepatic injury. I really can’t give greater detail on that. I think it’s worth looking into. Weight-reducing agents can improve hepatic fat and liver enzymes, and it’s definitely going to the left, but I don’t have more details to provide.

Q: Taking your point that this may be a cardiac drug, and you can argue whether it’s really a renal drug, you may or may not need diabetes to have a benefit. Do you have any data on individual patients who had virtually no A1c response vs. a greater response? Was there any difference in outcomes? As clinicians, if we’re using this for diabetes and there’s no A1c improvement, should we withdraw or keep going because glucose is not what we’re actually treating?

Dr. Darren McGuire (UT Southwestern, Dallas, TX): That comment was a bit tongue in cheek, but I believe gauging efficacy by A1c is cutting it well short. There are many plausible beneficial effects and I don’t personally think A1c has anything to do with it.

Dr. Inzucchi: I agree. What you’re proposing is looking at data split by change in A1c. We know baseline A1c doesn’t predict the effect on CV mortality. It would be interesting to look at the impact of the delta in A1c.

Dr. Riddle: This was an interesting and thought-provoking mediation analysis. Will you do a similar analysis for the renal outcomes? Do you have a feeling whether it would show the same or different patterns?

Dr. John Lachin (George Washington University, Washington, DC): The first phase of the analysis is not complete and it will include looking at heart failure and renal outcomes.  

Oral Presentations: Novel Therapeutics in Type 1 Diabetes

Canagliflozin (CANA) Improves Glycemic Control and Reduces Glycemic Variability in Patients with Type 1 Diabetes Mellitus (T1DM) Inadequately Controlled with Insulin

Maria Alba, MD (Janssen R&D, Raritan, NJ)

Dr. Maria Alba presented a full data set from a phase 2 study investigating J&J’s SGLT-2 inhibitor Invokana (canagliflozin) in type 1 diabetes – the primary presentation of the study’s results was at last year’s EASD, but Dr. Alba’s talk included some new data demonstrating markedly reduced glycemic variability with canagliflozin. The original data presentation demonstrated a 0.3% placebo-adjusted reduction in A1c with both the 300 mg and 100 mg canagliflozin doses from a baseline of ~8%, along with weight loss and reduced insulin dose. New data in this presentation demonstrated striking across-the-board improvements in multiple measures of glycemic variability, headlined by a ~15% improvement of time-in-range driven by reduced hyperglycemia. These were some of the best data we have seen on SGLT-2 inhibitors’ benefits on time-in-range and glycemic variability in type 1 diabetes. Taken as a whole, these data make a compelling case for keeping most type 1 patients on the lower 100 mg canagliflozin dose, as the 300 mg dose appeared to have diminishing returns on efficacy but many more adverse events like mycotic infections, DKA, and severe hypo. 

  • The improvements in glycemic variability were striking, even at the lower canagliflozin dose. CGM assessments were performed in a subgroup of 89 patients. Based on these data, it may make sense for the vast majority of type 1 diabetes patients to stick with the lower dose, as the higher dose may result in more of an increase in euglycemic DKA than efficacy. 

Table: Changes in Measures of Glycemic Variability and Glucose Control

 

Cana 100 mg vs. placebo

Cana 300 mg vs. placebo

Daily mean glucose (mg/dl)

25.4 ± 28.7

22.4 ± 32.2

Daily glucose standard deviation by SMBG (mg/dl)

14.5 ± 15.9

16.2 ± 20.4

Glucose standard deviation in CGM substudy (mg/dl)

6.8 ± 16.8

13.8 ± 13.9

MAGE in CGM substudy

16.5 ± 36.5

37.8 ± 37.0

Change in % time spent in range (70-180 mg/dl)

+15.1%

+13.6%

  • Adverse event data reminded us that while canagliflozin has a lot of upside in type 1, there are some important potential risks to consider and manage.  
    • Hypoglycemia: There appeared to be a slight reduction in the event rate of any documented symptomatic hypoglycemia with both canagliflozin doses, although the magnitude of the effect was small. The event rate was 56.1% per patient-year in the placebo group, 50.6% in the canagliflozin 100 mg group, and 47.3% in the canagliflozin 300 mg group, with the treatment differences achieving statistical significance. However, the number of patients with severe hypoglycemia, though small, was unbalanced not in favor of canagliflozin: two patients on placebo, three patients on canagliflozin 100 mg, and eight patients on canagliflozin 300 mg. In our view, this represents yet another reason why there may be little reason to push type 1 patients onto the high dose.
    • DKA: There was a clear dose-dependent increase in the incidence of both serious and non-serious ketone-related adverse events with canagliflozin. Compared to no cases in the placebo group, five patients on canagliflozin 100 mg and seven on canagliflozin 300 mg required hospitalization for DKA, the latter representing 6% of that study group. We still believe that this potentially very serious side effect can be managed, especially now that we are learning more about it.
    • Others: Unsurprisingly, there was an increase in overall adverse events with canagliflozin driven largely by genital mycotic infections, which affected a full 21% of women in the canagliflozin 300 mg group.
  • Study design: This 18-week study aimed to assess canagliflozin’s effect (at both 100 mg and 300 mg doses) in 351 type 1 diabetes patients inadequately controlled on insulin. In a two-week pre-randomization phase, it was recommended that patients’ insulin dosages be reduced by 10%-20%; once canagliflozin or placebo therapy was initiated, insulin doses were titrated to a target. At baseline, average patient age was around 42 years, average BMI was around 28 kg/m2, mean A1c was 7.9%, and mean diabetes duration was 22 years. A little more than half of the study population used insulin pumps, and 11%-12% had prior DKA.

Questions and Answers

Q: The rates of severe hypo were relatively small. It’s dangerous to over-analyze those results. At face value, there was a quadrupling of severe hypos with high dose canagliflozin. What do you think is underpinning this?

A: There was no pattern to what caused the severe hypoglycemic events, though there is a clear numerical increase in cases with the 300 mg group. There was no specific pattern to the cause, and none of the patients lost consciousness.

Dapagliflozin as Additional Treatment to Liraglutide and Insulin in Patients with Type 1 Diabetes: A Randomized Clinical Trial of 12 Weeks

Paresh Dandona, MD, PhD (University of Buffalo, NY)

Dr. Paresh Dandona (University of Buffalo, NY) presented updated results from a single center, prospective, randomized, placebo-controlled trial of SGLT-2 inhibitor dapagliflozin (AZ’s Farxiga) as an add-on to GLP-1 agonist liraglutide (Novo Nordisk’s Victoza) and insulin in patients with type 1 diabetes. Dr. Dandona had previously shared results for the first 10 participants in the trial in a poster at ADA 2015 and results for 16 participants at the AACE/ACE meeting on DKA. The latest presentation at ADA 2016 included updated results for the 30 participants who have now completed the trial. The participants all had type 1 diabetes for at least a year and had been on 1.8 mg liraglutide plus insulin therapy for at least six months prior to study initiation. The participants were randomized to treatment with either 10 mg dapagliflozin or placebo for 12 weeks. At 12 weeks, dapagliflozin treatment produced a mean A1c reduction of 0.6% (baseline A1c=7.8%, p<0.01) and 15 mg/dl reduction in average weekly glucose concentration (p<0.05 vs. baseline, p=0.07 vs. placebo). Furthermore, the dapagliflozin-treated group experienced a mean weight loss of 1.9 kg (p<0.05). Most notably, Dr. Dandona showed CGM tracings in which dapagliflozin treated markedly improved glycemic excursions and time in range – a “taming of the shrew” as he put it. He also demonstrated that the withdrawal of dapagliflozin resulted in greater glycemic variability compared to the triple therapy and the further withdrawal of liraglutide introduced even greater glycemic chaos. The use of CGM tracings in this, admittedly small, trial further add to the bulk of evidence for the beneficial effects of SGLT-2 inhibitors on time in range for patients with type 1 diabetes. Anecdotally, we’ve heard from patients and physicians that SGLT-2 inhibitors are able to take away some of the unpredictability and smooth out glycemic excursions in type 1 diabetes.

  • In terms of safety and adverse events, Dr. Dandona noted that two participants withdrew from the trial due to DKA. In looking at the underlying factors associated with DKA, his team found that dapagliflozin therapy was associated with significant changes in urine volume and glycosuria, increases in free fatty acid, increases in hormone-sensitive lipase, and increases in beta-hydroxybutyrate. These findings are consistent with the DKA results for this trial that Dr. Dandona previously presented at the AACE/ACE meeting on DKA in October. Hypoglycemia event rates were comparable between the dapagliflozin and placebo groups.

Oral Presentations: Beyond Basal Insulin in Type 2 Diabetes—Treatment Intensification Options

Comparison Between SGLT-2 Inhibitors and DPP-4 Inhibitors Added to Insulin Therapy in Type 2 Diabetes: A Systematic Review with Indirect Comparison Meta-Analysis

Se Hee Min, MD (Seoul National University Hospital, South Korea)

Dr. Se Hee Min presented the results of an indirect meta-analysis that compared the effect of SGLT-2 inhibitors plus insulin (SGLT-2i/INS) vs. DDP-4 inhibitors plus insulin (DPP-4i/INS) in type 2 patients. The group performed a systematic review that yielded 14 studies which investigated either SGLT-2i/INSU vs. placebo/INS or DPP-4i/INS vs. placebo/INS (five and nine studies, respectively). Results of the covariate-adjusted indirect comparison using meta-regression analyses showed that SGLT-2i/INS provided greater reductions in A1c (weighted mean difference [WMD] of -0.24%; 95% CI: -0.43 to -0.05%), as well as greater reductions in fasting plasma glucose (WMD -18.0; 95% CI: -28.5 to -7.6 mg/dl) and body weight (WMD -2.38 kg [lbs]; 95% CI: -3.18 kg [7.0 lbs] to -1.58 kg [3.5 lbs]). No difference in hypoglycemia was observed with SGLT-2i/INS compared to DPP-4i/INS (RR 1.19; 95% CI: 0.78-1.82). Dr. Min remarked that in the absence of head-to-head comparisons, these results could serve as the best available evidence for selecting oral agents in patients uncontrolled on insulin. These findings are not surprising to us, as we feel that it is widely understood that the DPP-4 class is slightly inferior in efficacy, but its solid tolerability and safety profiles keep it as a mainstream treatment option.

  • Dr. Min noted that her group focused on SGLT-2 inhibitors and DPP-4 inhibitors because the drugs do not require injections and do not contribute to significant weight gain. Thus, the team views them as preferable add-on agents compared to GLP-1 agonists and TZDs. Furthermore, Dr. Min highlighted that SGLT-2 inhibitors and DPP-4 inhibitors have complementary effects to insulin with regards to hypoglycemia and weight gain.
  • To perform their systematic review, Dr. Min and colleagues searched Medline, Embase, LILACS, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov for randomized controlled trials before June 2015 that compared either SGLT-2i/INSU vs. placebo/INS or DPP-4i/INS vs. placebo/INS. They included only trials that were ≥12 weeks long and that measured A1c as an endpoint. The search yielded 14 trials – five SGLT-2 inhibitor studies and nine DPP-4 inhibitor studies.
  • The indirect analysis involved comparing each drug’s efficacy over placebo. After the initial evaluation yielded no differences between SGLT-2i/INSU and DPP-4i/INS, the authors performed a meta-regression that guided a subsequent covariate adjustment, which yielded the results presented above.

Questions and Answers

Q: The DPP4i/INS studies generally looked at a single dose while the SGLT-2i/INS studies usually had a lower dose and a higher dose. Did you include both doses or the maximum dose?

A: We included the data from the maximum approved dose.                                                           

Q: I’m not sure if you could do this because you would need patient-level data, but would you consider comparing the two drugs by baseline A1c category?

A: Thank you for your question. We did not stratify the patients by A1c.

Efficacy and Safety of Ipragliflozin, an SGLT-2 Inhibitor, Add-on to Insulin in Japanese Patients: Results of a Double-Blind, Placebo-Controlled Study

Hisamitsu Ishihara, MD, PhD (Nihon University School of Medicine, Tokyo, Japan)

Dr. Hisamitsu Ishihara (Nihon University School of Medicine, Tokyo, Japan) presented results from a trial of SGLT-2 inhibitor ipragliflozin (Astellas/Kotobuki’s Suglat) in Japanese patients with type 2 diabetes on basal insulin therapy. The 16-week, randomized, double-blind, placebo-controlled, parallel-group study (n=262) investigated ipragliflozin as an adjunct to basal insulin monotherapy or basal insulin/DPP-4 inhibitor dual therapy. The trial found that iprgraliflozin treatment produced an mean A1c difference of -1.07% compared to placebo (baseline A1c=8.67% in ipragliflozin group, 8.62% in placebo group, p<0.001). Participants treated with a DPP-4 inhibitor at baseline experienced greater A1c reductions than those not on a DPP-4 inhibitor (-1.2% vs. -0.84%, p=0.042 for interaction). Participants in the ipragliflozin-treated group overall also experienced a mean 40.3 mg/dl greater reduction in fasting plasma glucose (p<0.001) and a 1.07 kg (~2.36 lbs) body weight reduction (p<0.001) compared to placebo. Ipragliflozin treatment was also associated with an increase in adiponectin (0.33 µg/ml, p=0.022) and a greater decrease in C-peptide (−0.22 ng/ml, p < 0.001) compared to placebo. In terms of adverse events, more participants in the ipragliflozin-treated group experienced hypoglycemia (29.7% vs. 14.9% in the placebo group), urinary tract infection (2.3% vs. 1.1%), genital infection (4% v. 0%), and fluid/volume depletion (2.3% vs. 1.1%). Dr. Ishihara characterized all hypoglycemia episodes as mild and noted that none of the participants experienced symptoms of ketoacidosis.

Oral Presentations: Treatment and Management of Complications—Can a Dog Really Smell Hypoglycemia?

Canagliflozin (CANA) Slows Progression of Renal Function Decline Independent of Glycemic Effects

Hiddo Heerspink, PhD, PharmD (University Medical Center Groningen, Groningen, Netherlands)

Dr. Hiddo Heerspink presented results from a post-hoc analysis of a randomized, double-blind, two-year study on the effect of canagliflozin (J&J’s Invokana) on renal function in 1,450 patients with type 2 diabetes. The participants were randomized to canagliflozin 100mg daily (n=483) or 300mg daily (n=485), or to glimepiride titrated to 6-8mg daily (n=482). Reduction in A1c was comparable between the glimepiride, canagliflozin 100 mg, and canagliflozin 300 mg groups after one year (0.81%, 0.82%, 0.93%, respectively) and after two years (0.55%, 0.65%, 0.74%, respectively). Decline in annual eGFR was greater with glimepiride (3.3; 95% CI: 2.8-3.8) than with canagliflozin 100 mg (0.5; 95% CI: 0-1.0) or canagliflozin 300 mg (0.9; 95% CI: 0.4-1.4; p<0.01 for each canagliflozin group vs. glimepiride). Both doses of canagliflozin also provided greater reductions in albuminuria (measured via UACR) compared to glimepiride. The positive effects of canagliflozin on eGFR and UACR persisted when controlling for A1c, systolic blood pressure, and body weight. Thus, the authors concluded that canagliflozin may slow the progression of kidney disease independent of its glycemic effects. In closing, Dr. Heerspink noted that the CREDENCE trial is underway to assess the effect of canagliflozin 100mg/day on renal endpoints in patients with diabetic kidney disease. The presentation of positive renal outcomes results from the EMPA-REG OUTCOME trial for Lilly/BI’s Jardiance (empagliflozin) was one of the high points of ADA 2016; those results along with this and other promising analyses of phase 3 trials make an SGLT-2 inhibitor class effect on kidney disease seem more and more plausible.

  • In opening, Dr. Heerspink explained that SGLT-2 inhibition has been shown to lower A1c, body weight, blood pressure, and albuminuria. As noted above, the EMPA-REG OUTCOME trial for Jardiance not only demonstrated reductions in cardiovascular risk, but also suggested a renal protective benefit of the drug. These benefits were observed within weeks of starting therapy, indicating that they may be independent of glycemic control. Dr. Heerspink stated that because the study lacked an active comparator, it was difficult to draw conclusions.
  • This study recruited 1,450 patients with type 2 diabetes with an A1c of 7.0-9.5% who were on metformin (dose of at least 2,000 mg/day, or 1,500 mg/day if intolerant of higher dose). Baseline characteristics were similar between the three groups: average age 55-56 years, percent female 45-50%, average A1c 7.8%, duration of diabetes 6.5-6.7 years, systolic blood pressure 120-30 mmHg, diastolic blood pressure 78-79 mmHg, eGFR 89-91 ml/min/1.73m2, UACR 8.2-9.7 mg/g, and ACE/ARB use 59-62%.
  • Additional outcomes included albuminuria (UACR). A greater decrease in albuminuria was observed with canagliflozin 100 mg vs. glimepiride (difference of -31.7; 95% CI: -48.9 to -8.6) and with canagliflozin 300 mg vs. glimepiride (difference of -49.3; 95% CI: -62.2 to -31.9). This effect persisted when controlling for A1c, systolic blood pressure, and body weight; it was also observed in a subgroup of patients with diagnosed microalbuminuria. Regarding trends, albuminuria increased in the glimepiride group across the two-year study. In the canagliflozin 100mg group, it remained stable in the first year and increased in the second year. In the canagliflozin 300mg group, it decreased in the first year and returned to baseline in year two.
  • The study also measured the percent of patients who experienced a 30% or 40% decline in eGFR. Dr. Heerspink noted that the number of events was small, leading to wide confidence intervals. However, within the microalbuminuria subgroup, the percentage of patients that experienced a 30% declined was statistically significantly lower with canagliflozin 100mg compared to glimepiride (HR 0.37; 95% CI: 0.15-0.90).

Questions and Answers

Q: You have shown an effect on your renal endpoints. Your analysis here suggests that this requires long-term treatment with an SGLT-2 inhibitor to exploit the full potential benefit of the treatment. Obviously, when we talk about long-term treatment, we come to the issue of urogenital infection. Was this more common in patients with renal impairment?

A: To fully understand the effect of canagliflozin and the whole SGLT-2 inhibitor class, you need long-term trials because renal function declines steadily over time. And of course, you have to take into account the safety of the drug. We have seen that people with low eGFR have more adverse effects, but this is also seen in the placebo group. So the relative risk of the drug on adverse effects is similar between people with high eGFR and low eGFR.

Q: How frequently did infection occur in this group?

A: The data have been published already. We know that urinary tract infections occurred in 5% of glimepiride-treated patients and in 6% of canagliflozin-treated patients.

Q: These findings are of intense interest and are somewhat similar to reports of decreased cardiovascular disease risk with these agents, which appears to be independent of their dosing and their A1c-lowering effect. Since there was apparently a change in albuminuria between the groups, can you tell us anything about the mechanism?

A: Of course, this is a very important question. We have done a lot of studies on SGLT-2 inhibitors and their glucose lowering effect without knowing the mechanisms. I wouldn’t say the effect on albuminuria was a small effect; I would say it’s a big effect, especially in patients with already-established microalbuminuria. The mechanism, in my view, relates to the blockage of sodium reabsorption. If you start treatment with an SGLT-2 inhibitor, you block the SGLT-2 transporter and block sodium uptake. This leads to more sodium delivery to the distal tubules, which activates the macula densa and restores tubuloglomerular feedback, which leads to constriction of the afferent arteriole, thereby reducing glomerular pressure. Previous studies have shown that other mechanisms that reduce glomerular pressure lead to renal protection, and now we may have a new mechanism.

Q: Given the data you presented here, and what has already been published for empagliflozin, it seems that SGLT-2 inhibitors may be one of the most effective ways to combat renal impairment in people with type 2 diabetes. What about retinopathy in patients?

A: That’s a very good question. I have to go back to the data to answer that question. I can answer the question for cardiovascular endpoints. This patient population was a low-risk population, so the cardiovascular endpoints were similar between the treatment cohorts. The number of events was very low, so it was hard to draw conclusions.

Q: How does eGFR compare to direct measurement of GFR in this patient population?

A: That’s a very good question. There have been very few studies comparing measured GFR and estimated GFR in people on an SGLT-2 inhibitor. We did a study published in 2013 on dapagliflozin and GFR where we saw an acute fall in measured GFR and in eGFR. So measured GFR tracks with the eGFR endpoint.

Efficacy of Dapagliflozin-Saroglitazar Combination for Treatment of NAFLD in Young Diabetics

Kiran Pal Singh, MD (Fortis Hospital, Mohali, India)

Dr. Kiran Pal Singh’s single center, randomized, open-label study investigated the effects of combining dapagliflozin and saroglitazar (a PPAR alpha/gamma agonist) vs. dapagliflozin alone on A1c and the liver in 56 young patients with diabetes and non-alcoholic fatty liver disease (NAFLD). The patients (ages 20-35 years) had been on dietary and metformin therapy for ≥3 months and received either dapagliflozin 10 mg alone (n=28) or in combination with saroglitazar (4 mg; n=28). Transient elastography (Fibroscan) was used to measure hepatic steatosis (via the controlled attenuation parameter), as well as hepatic fibrosis (via liver stiffness). The 24-week data showed that compared to dapagliflozin alone, the dapagliflozin-saroglitazar combination led to significantly greater reductions in triglycerides and liver fat content, as well as higher rates of transaminase normalization. Dr. Pal Singh thus concluded that this drug combination may have potential benefit in NAFLD.

  • In opening his talk, Dr. Pal Singh highlighted that NAFLD commonly coexists with impaired glucose tolerance and type 2 diabetes, and is believed to be the hepatic component of the metabolic syndrome. He relayed that the major risk factors of NAFLD (dyslipidemia, type 2 diabetes, obesity, metabolic syndrome) overlap with those for diabetes. The pathogenesis of hyperlipidemia and hyperglycemia in NAFLD is multifactorial, and includes insulin resistance and increased production and retention of lipids in hepatocytes due to impaired apolipoprotein secretion or beta oxidation. NAFLD carries several risks, including increased liver-related and cardiovascular mortality, as well as the risk of cirrhosis.
  • Dr. Pal Singh highlighted that despite the risks associated with NAFLD, an optimal treatment has not yet been established. In his view, an ideal drug should aim to improve insulin sensitivity, glucose metabolism, and dyslipidemia. It should also reduce steatosis and transaminitis, and should halt the progression of liver fibrosis. He cited several drugs currently under investigation, including GLP-1 agonists, SGLT-2 inhibitors, PPAR alpha/gamma agonists, Farnesoid X receptor agonists, and leucine-metformin-sildenafil combinations. See our competitive landscape for what this market’s latest looks like.
  • PPAR alpha/gamma agonists are a promising therapy for NAFLD. PPAR alpha activation leads to fatty acid oxidation, which decreases triglycerides and increases HDL, ultimately leading to lipid lowering. PPAR gamma activation acts on adipogenesis and lipogenesis to increase glucose uptake and lower blood glucose levels. Dr. Pal Singh mentioned that while several members of the glitazar class have failed clinical trials for NAFLD due to their poor side effect profile (muraglitazar, tesaglitazar, farglitazar, aleglitazar), saroglitazar’s unique structure makes it less likely to cause weight gain and edema. Previous trials have already shown that it reduces triglycerides and lowers A1c.
  • Patients in both groups had similar demographic, clinical, and biochemical parameters: mean age of 29-30 years, gender breakdown (39-42% female), mean duration of diabetes of 2 years, BMI of 30, baseline A1c of 7.9%-8.2%, triglycerides of 374-399 mg/dl, abnormal transaminases in 61%-64% of each group, and liver fat content of 324-336 dB/m. 

Table 1: 24-week results from the study

 

dapagliflozin-saroglitazar combination

dapagliflozin only

p value

 

baseline

24 wks

change

baseline

24 wks

change

 

A1c

8.2

7.1

-1.2

7.9

7.1

-0.87

0.8

Triglycerides

399

183

-216

373

230

-143

0.002

Liver fat content

336

205

-131

324

250

-74

0.001

Abnormal Transaminases

n=18/28

(64%)

n=5/28

(18%)

72%

n=17/28

(61%)

n=11/28

(39%)

35%

---

Questions and Answers

Q: For your longer term study, have you considered having at least a sample of the patients in both groups undergo evaluation by MRI or liver biopsy?

A: No, we did not do any MRI scanning or biopsies. We just used the fibroscan.

Q: Did the fibroscan give you any measure of fibrosis in addition to liver fat?

A: Yes, we have done that, but we have not analyzed the data. The fibroscan gives both parameters.

Oral Presentations: Treatment Choices after Orals in Type 2 Diabetes

Empagliflozin Compared with Glimepiride as Add-On to Metformin for 4 years in Patients with Type 2 Diabetes

Afshin Salsali, MD (Boehringer Ingelheim, Fremont, CA)

Dr. Afshin Salsali provided an overview of results from a 104-week extension of the EMPA-REG H2H-SU trial in which empagliflozin (25 mg) as an add-on to metformin demonstrated mean A1c, weight, and blood pressure reductions versus the sulfonylurea glimepiride in patients with type 2 diabetes. Specifically, empagliflozin showed a small but significant reduction in A1c from baseline compared to glimepiride at week 208 (-0.18% vs. glimepiride, baseline A1c=7.92%, p=0.02). Notably, though not surprisingly, empagliflozin achieved this A1c with a much lower rate of hypoglycemia adverse events (3% of participants on empagliflozin reported confirmed hypoglycemia, compared to 28% of participants on glimepiride), and the time of onset of first rescue therapy for severe hypoglycemia was much later. Further, empagliflozin provided a 4.6 kg (~10 lbs) weight advantage versus glimepiride, which was sustained for the duration of the study extension period (baseline=83 kg, p<0.001). Empagliflozin also reduced systolic and diastolic blood pressure (-3% and -2% respectively) while glimepiride did not. As expected, on the negative side, empagliflozin was associated with a higher rate of urinary tract infection and genital infection adverse events versus glimepiride (20% and 14% vs. 16% and 4%, respectively). These results further strengthen the argument for the use of empagliflozin as a second-line therapy for type 2 diabetes over sulfonylureas. That said, we recognize that sulfonylureas are often chosen for cost reasons rather than due to their efficacy or safety profile and we hope studies such as this can put pressure on payers to better reimburse newer, safer, more effective medications.

Linagliptin (LINA) as Add-on to Empagliflozin (EMPA) and Metformin in Patients with Type 2 Diabetes (T2DM): Two 24-Week Randomized, Double-Blind, Parallel-Group Trials

Baptist Gallwitz, MD (Eberhard Karls University, Tubingen, Germany)

Dr. Baptist Gallwitz presented positive phase 3 data on the glycemic efficacy of Lilly/BI’s Tradjenta (linagliptin) as add-on to Lilly/BI’s Jardiance (empagliflozin) and metformin compared with placebo. These findings come from two 24-week randomized, double-blind, parallel group studies of Tradjenta vs. placebo, as add-on to Jardiance at either the 10 mg or 25 mg doses and metformin in participants with type 2 diabetes. Participants received metformin and either Jardiance at the 10 mg (study 1; n=352) or 25 mg (study 2; n=354) doses for 16 weeks in an open-label period, which was followed by a randomization to 24 weeks of double-blind, double-dummy treatment with additions of Tradjenta (n=126) or placebo (n=130). The findings demonstrated that at 24 weeks, the Tradjenta group resulted in statistically significant reductions in A1c compared with placebo: from a baseline A1c of ~8%, participants achieved placebo-adjusted A1c reductions of 0.32% and 0.47% in the Jardiance 10 mg and 25 mg dose groups, respectively. In addition, the proportion of participants who reached A1c levels below 7% at week 24 in the Tradjenta add-on groups was more than double that of the placebo groups (26% vs. 11% in study 1; 36% vs. 15% in study 2). There were no significant changes in body weight with either treatment group. Regarding safety and tolerability, no new signals emerged: the placebo group reported more adverse events than the Tradjenta add-on group, with three hypoglycemic events occurring in the placebo arm of study 2 (Jardiance 25 mg + metformin). Ultimately, these findings support an SGLT-2 inhibitor/DPP-4 inhibitor combination as a promising treatment option for patients who are inadequately controlled with metformin and an SGLT-2 inhibitor. Such a combination has certainly received increasing attention, as Merck has recently expressed greater excitement on the potential of a Januvia (sitagliptin)/ertugliflozin combination. We look forward to seeing longer-term data on this approach, as these data could potentially help craft more individualized guidance into treatment algorithms.

Questions and Answers

Q: What was the baseline A1c?

A: Around 8%.

Q: Did you add lina or did you switch the empagliflozin to an empa/lina combination?

A: We did not use the fixed-dose combination. We added the lina on.

Q: Do you have glucagon levels?

A: We do not have these yet.

Q: Did you perform a meal test?

A: No, we did not.

Dapagliflozin + Exenatide QW Reduced Body Weight and Improved Glucose Tolerance in Nondiabetic Obese Adults: A Randomized, Placebo-Controlled, Phase 2 Study

Jan Eriksson, MD, PhD (Uppsala University, Uppsala, Sweden)

Results from a phase 2 proof of concept study (n=50) of combination therapy with AZ’s Farxiga (dapagliflozin) and Bydureon (exenatide once weekly) demonstrated significant ~4 kg weight loss and glycemic improvements vs. placebo in patients with obesity but not diabetes. Participants in the double-blind, single-center study were randomized to receive either active treatment or double placebo for 24 weeks, followed by a 28-week open-label extension study; data from the extension study will be presented at EASD in September. After 24 weeks, the combination led to significant placebo-adjusted weight loss of 4.1 kg (baseline weight = 103-106 kg [227-234 lbs]; baseline BMI = 35-36; p=0.0007) or 4.2% (p=0.0005). As in most obesity drug trials, there was a wide range of responses, but far more patients achieved ≥5% weight loss with the active treatment than with placebo (36% vs. 4%). MRI analysis of body composition showed that almost all of the weight loss was due to loss of adipose tissue, with no significant change in lean tissue. The combination also produced a modest but significant 0.2% placebo-adjusted A1c reduction (baseline = 5.6%, p=0.0004), a significant drop in the proportion of patients with impaired fasting glucose and impaired glucose tolerance, and a significant placebo-adjusted blood pressure reduction of 6.4 mm Hg (p=0.026). Adverse events were fairly balanced, with slightly more GI side effects in the active treatment group.

  • These results are encouraging, though as noted during Q&A, the real test will be how the combination stacks up against each of its components alone. AZ is currently conducting a phase 3 study (n=660) of that comparison in patients with type 2 diabetes that is expected to complete in December 2017 (primary completion May 2016). As presenter Dr. Jan Eriksson noted, GLP-1 agonist/SGLT-2 inhibitor combinations are very appealing for obesity due to their complementary mechanisms of weight loss (calorie loss with the SGLT-2 inhibitor and reduced appetite/caloric intake with the GLP-1 agonist). The same could also be said for glycemic control, as the reduction in glucagon production with GLP-1 agonists could help mitigate the increased glucagon production that blunts some of the efficacy of SGLT-2 inhibitors. We expect AZ to focus primarily on type 2 diabetes with this combination but find the potential in obesity very interesting as well, particularly for a GLP-1 agonist with more potent weight effects like Novo Nordisk’s Saxenda (liraglutide 3.0 mg) or semaglutide.

Questions and Answers

Q: Could you clarify the timing of the last dose vs. the glucose measures?

A: A glucose tolerance test was performed at baseline and at 24 weeks. The dose was taken half an hour before the glucose tolerance test was started.

Q: Although I acknowledge this was a proof of concept trial, why didn’t it include monotherapy + placebo arms? You’re really asking whether there’s a synergistic or additive effect and this study didn’t answer that.

A: It’s a proof of concept for the combination and we showed robust weight loss vs. placebo, but I agree, we want a study against monotherapies as well. That would have increased the study size so we couldn’t have done it at a single center.

Oral Presentations: Modulators of Adipose Tissue Inflammation

SGLT2 Inhibition by Empagliflozin Attenuates Obesity-induced Insulin Resistance and Inflammation by Enhancing Fat Utilization and Macrophage Alternative Activation

Tsuguhito Ota, MD, PhD (Kanazawa University, Japan)

Dr. Tsuguhito Ota presented the results of his animal study that investigated the effects of empagliflozin on insulin resistance in obese mice given either a high-fat diet (HFD) alone or containing either 0.01% or 0.03% empagliflozin. Empagliflozin suppressed HFD-induced weight gain (16% with the 0.03% dose). The drug also increased energy expenditure – more specifically, Dr. Ota noted that the induction of UCP1 expression observed with the drug suggested that it promotes browning of white adipose tissue. In skeletal muscle, empagliflozin increased fat utilization, accompanied by elevated AMPKα and ACC phosphorylation, and increased expression of genes involved in fatty acid oxidation. Empagliflozin was also shown to improve HFD-induced glucose intolerance, hyperinsulinemia, and hepatic steatosis; furthermore, it increased insulin signaling in the mouse liver and white adipose tissue. These tissues also had reduced accumulation of both macrophages and T cells with empagliflozin, along with a change in the macrophage composition from mainly M1 (CD11c+CD206-) cells to predominantly M2 (CD11c-CD206+) cells. As we hear more obesity data on type 2 diabetes drugs, these findings point to the potential of the SGLT-2 inhibitor class in these broader indications.

Questions and Answers

Q: Some of the effects that you saw in terms of fatty acid oxidation and browning are potentially mediated by FGF21. Could that be playing a role?

A: We measured FGF21 in plasma, but it was not changed significantly, so I don’t think so.

Posters

Ertugliflozin Effectively Improves Glycemic Control as Monotherapy in Patients with T2DM (130-LB)

S Dagogo-Jack, M Davies, J Frias, G Derosa, A Darekar, K Focht, G Golm, J Johnson, D Saur, and S Terra

Dr. Dagogo-Jack and colleagues presented interim, 26-week results from the ongoing 52-week, randomized, double-blinded, phase 3 VERTIS MONO trial investigating the safety and efficacy of Merck/Pfizer’s ertugliflozin in patients with type 2 diabetes. The study recruited 461 patients with inadequate glycemic control on diet and exercise (A1c 7-10.5% with no anti-diabetic agents taken within 8 weeks of starting the study), who were randomized to placebo (n=153), ertugliflozin 5mg daily (n=156), or ertugliflozin 15mg daily (n=152). Twenty-six-week data showed that both ertugliflozin doses provided statistically significantly greater A1c reductions vs. placebo (0.99% for the 5mg dose and 1.16% for the 15mg dose); similar results were observed for fasting plasma glucose, body weight, and 2-hour post-prandial glucose. In addition, a greater proportion of patients achieved an A1c <7% in the ertugliflozin groups vs. placebo.

  • Participants who met glycemic rescue criteria received open-label metformin. The FPG thresholds for rescue were >270 mg/dl from day 1 to week 6; >240 mg/dl from week 6 to week 12; and >200 mg/dl from week 12 to 16.  The placebo group had a higher rate of patients receiving glycemic rescue (26%) compared to the ertugliflozin 5mg (2%) and 15mg group (3%).
  • The three groups had comparable baseline characteristics, with an average age of 56-57 years, % male of 54-59%, duration of type 2 diabetes of 5 years, body weight of 91-94 kg [201-207 lbs], BMI of 33 kg/m2, A1c of 8.1-8.4%, FPG of 179-181 mg/dl, baseline 2-hr PPG of 256-263 mg/dl, SBP of 130 mmHg, DBP of 78-79 mmHg, and eGFR of 86-89 mL/min/1.73m2
  • The retention rate through week 26 was 90% across the three groups and 83% for the study drug. 

Table 1: Change in A1c from baseline to 26 weeks 

Treatment

Baseline

Week 26

Change from baseline to wk 26

 

n

Mean

n

Mean

n

Mean

Placebo

153

8.11

89

7.76

153

-0.09

Ertugliflozin 5mg

155

8.16

133

7.31

156

-0.80

Ertugliflozin 15mg

151

8.35

124

7.28

151

-1.04

Table 2: Results of primary and secondary endpoints at 26 weeks. 

Endpoint

Ertugliflozin 5mg vs. placebo

Ertugliflozin 15mg vs. placebo

 

Difference#

p value

Difference#

p value

A1c (%)

-0.99

p<0.001

-1.16

p<0.001

FPG (mg/dl)

-34.5

p<0.001

-44.0

p<0.001

Body Weight

-1.76 kg [3.9 lbs]

p<0.001

-2.16 kg [4.8 lbs]

p<0.001

2-h PPG (mg/dl)

-69.0

p<0.001

-67.3

p<0.001

SBP (mmHg)

-3.31

0.015*

-1.71

0.213

DBP (mmHg)

-1.80

0.039*

-0.37

0.669*

 

Odds Ratio

p value

Odds Ratio

p value

Proportion of pt with A1c <7%

3.6

p<0.001

6.8

p<0.001

* Nominal p value

# Difference in least squares means based on a constrained longitudinal data analysis model

  • Regarding adverse events, genital mycotic infections were more common in female participants receiving ertugliflozin vs. placebo. In male participants, genital mycotic infections were numerically higher with ertugliflozin vs. placebo. The incidence of UTI was numerically highest in the placebo group. Furthermore, the rates of symptomatic hypoglycemia and hypovolemia were similar between the three groups.

Effect of Ertugliflozin plus Sitagliptin on Glycemic Control vs. Either Treatment Alone in Subjects with T2DM Inadequately Controlled with Metformin (125-LB)

R Eldor, R Pratley, G Golm, S Huyck, Y Qiu, S Sunga, J Johnson, S Terra, J Mancuso, S Engel, and B Lauring

Dr. Eldor and colleagues presented interim, 26-week results from an ongoing 52-week randomized, double-blind, phase 3 trial comparing the safety and efficacy of Merck/Pfizer’s ertugliflozin plus sitagliptin (Merck’s Januvia) versus either drug alone in patients with type 2 diabetes. The study recruited 1,233 patients inadequately controlled (A1c 7.5-11%) on stable metformin (≥8 wks at ≥1,500 mg/day), who were randomized to one of five groups: ertugliflozin 5mg or 15mg daily plus sitagliptin 100mg daily, ertugliflozin 5mg or 15mg daily alone, or sitagliptin 100mg daily alone. Data at 26 weeks showed that co-administration of ertugliflozin with sitagliptin led to significantly greater reductions in A1c (1.5% for both groups) compared to either drug alone (1%-1.1% across the three groups; p<0.002). A similar effect was observed with fasting plasma glucose and percentage of patients achieving A1c <7%. Co-administration also led to significantly greater reductions in body weight and systolic blood pressure compared to sitagliptin alone. Static beta-cell responsivity increased across all treatment arms and no difference was observed with the co-administration groups. 

  • The retention rate across all groups at 26 weeks was 92-96%. The authors provided the ranges of baseline characteristics across all five groups: average age of 55 years, % male of 51-62%, mean A1c of 8.50-8.57%, duration of T2DM of 6-7 years, eGFR of 92 mL/min/1.73m2, weight of 88-90 kg [194-198 lbs], and BMI of 32-33 kg/m2

Table 1: Data from 26 weeks showing greater reductions in A1c, FPG, weight, and SBP with combined ertugliflozin + sitagliptin versus either drug alone.

Reduction from baseline:

ERTU 5mg

ERTU 15mg

SITA 100mg

ERTU 5mg + SITA 100mg

ERTU 15mg + SITA 100mg

n

250

248

247

243

244

A1c (%)

1

1.1

1.1

1.5*

1.5*

FPG (mg/dl)

35.5

37.1

25.9

44.4*

48.9*

Body weight

 

2.7 kg  [6.0 lbs]

3.7 kg    [8.2 lbs]

0.7 kg       [1.5 lbs]

2.5kg#                         [5.5 lbs]

2.9kg#                        [6.4 lbs]

SBP

3.9

3.7

0.7

3.4#

3.7#

Pt with A1c <7%

66 (26%)

79 (32%)

83 (34%)

127 (52%)

120 (49%)

* p<0.002 vs. individual treatments

# p<0.005 vs. sitagliptin treatments (comparisons to ertugliflozin alone were not performed)

p<0.001 based on model-estimated odds ratio comparing ERTU+SITA vs. individual treatments

  • The safety profiles were similar between the five groups, with the exception of a higher observed rate of genital mycotic infections in the groups that included ertugliflozin. The authors note that there was no meaningful difference in urinary tract infection incidence between the groups, and that the rate of hypovolemia and symptomatic hypoglycemia were low across treatment groups.

Effect of Empagliflozin (EMPA) on Bone Fractures in Patients with Type 2 Diabetes (T2DM)(126-LB)

S Kohler, S Kaspers, A Salsali, C Zeller, and H Woerle

BI presented a retrospective analysis of pooled clinical trial data demonstrating no increased risk of bone fractures with empagliflozin (Jardiance, partnered with Lilly) in patients with type 2 diabetes. Pooled safety data from 15 phase 1-3 clinical trials and four extension studies was analyzed from patients who were randomly assigned to receive empagliflozin 10mg (n=4,221), empagliflozin 25mg (n=4,196) or placebo (n=4,203). Data from a head-to-head phase 3 study of empagliflozin vs. glimepiride was analyzed separately. The researchers evaluated the rate of bone fracture adverse events (AEs) in the total population and in subgroups divided by gender, baseline age, and baseline eGFR. The pooled analysis found no statistical difference in the number of bone fracture adverse events with empagliflozin vs. placebo but an increased risk in both groups in females, older patients, and those with moderate renal impairment. In the head-to-head study, empagliflozin 25 mg did not increase the risk of bone fracture adverse events compared to glimepiride 1-4mg. In the same study, neither treatment group saw bone mineral density T-scores outside the normal range. This retrospective analysis, along with results from the EMPA-REG OUTCOME trial, provides reassuring evidence that there is no clear link between empagliflozin and bone fractures. Bone fractures have been cited as a potential risk with SGLT-2 inhibitors because the drugs alter renal sodium and glucose reabsorption, resulting in possible changes in renal reabsorption of calcium and phosphate and possible modulation of bone metabolism. The FDA released a Drug Safety Communication last September strengthening the label warning on fracture risk for J&J’s SGLT-2 inhibitor Invokana (canagliflozin); it stated at the time that it would evaluate the risk with Jardiance and AZ’s Farxiga (dapagliflozin) to determine whether updates were warranted. We assume that this data, combined with the lack of any harmful signal in the EMPA-REG OUTCOME trial, makes any additional warnings unlikely.

Effect of Empagliflozin on Diabetic Ketoacidosis in Patients with Type 2 Diabetes: Pooled Clinical Trial Data (127-LB)

S Lund, F Solimando, S Kohler, C Zeller, and S Kaspers

In this poster, BI shared results from a meta-analysis that examined the effects of SGLT-2 inhibitor empagliflozin (Lilly/BI’s Jardiance) on diabetic ketoacidosis (DKA) in patients with type 2 diabetes.  Data from over 15,000 patients with type 2 diabetes from 18 randomized clinical trials (varying from phase 1 to 3 and in duration from 8 days to 4 years) were included in the meta-analysis.  4,558 of these patients received empagliflozin 10 mg, 5,520 patients received empagliflozin 25 mg, and 5,599 patients received a comparator drug.  Baseline characteristics were similar between the two groups.  DKA events were only reported in less than 0.1% of patients, and no difference was seen between patients given comparators or empagliflozin.  However, significantly more patients using empagliflozin had high urinary ketone levels (≥ 1+) than patients on comparators. The low event rate for DKA and comparable rates between empagliflozin and comparators across the 18 trials is reassuring; we believe the link between empagliflozin and high urinary ketone levels should be monitored. The general consensus surrounding the link between SGLT-2 inhibitors and DKA appears to be that the event rate is fairly low in patients with type 2 diabetes but urinary ketone monitoring may be useful, especially for patients on insulin.

Coadministration of Canagliflozin (CANA) and Phentermine (PHEN) for Weight Management in Overweight and Obese Adults (319-LB)

PA Hollander, HE Bays, J Rosenstock, ME Frustaci, A Fung, and N Erondu

In a late-breaking poster, phase 2 results of the co-administration of J&J’s Invokana (canagliflozin) and phentermine showed significantly greater weight loss vs. placebo in adults with overweight and obesity. This study was a four-arm, 26-week study and evaluated the efficacy and safety of Invokana + phentermine, phentermine alone, Invokana alone, and placebo in 334 adults with BMIs of 30-50 kg/m2 and without type 2 diabetes or with hypertension and/or dyslipidemia and BMIs of 27-50 kg/m2. The findings demonstrated that at 26 weeks, from a mean baseline BMI of ~37 kg/m2, the Invokana + phentermine group achieved significantly greater weight loss (7.5%) compared to the other groups (4.1%, 1.9%, and 0.6% for Invokana, phentermine, and placebo, respectively). In addition, the combination therapy group had a significantly higher proportion of participants achieving ≥5% weight loss compared to placebo (67% vs. 18%). Only 18% and 42% of the Invokana and phentermine groups’ participants achieved weight loss of at least 5%. On other secondary endpoints, the combination therapy group also had a significant reduction in systolic blood pressure, with a placebo-subtracted reduction of 4.2 mmHg. Regarding safety and tolerability, no new signals emerged from these data; however, the combination therapy, phentermine, and Invokana groups all experienced increases in heart rate of 3.5 bpm, 4.1 bpm, and 0.7 bpm, respectively – an observation whose potential consequences on cardiovascular events have not yet been determined and will likely warrant further investigation. Ultimately, these findings are powerful in support of using phentermine with SGLT-2 inhibitors in chronic weight management, and we are interested to see whether Janssen will move forward with phase 3 trials, and ultimately pursue an obesity indication. Combination therapies have certainly gained significant attention within obesity management (in addition to diabetes), and we have specifically heard greater enthusiasm for the potential of GLP-1 agonists and SGLT-2 inhibitors in weight management. With so much evidence already accumulated on these various diabetes drugs, we look to see how industry, healthcare providers, and the FDA envision the movement of these products into obesity, given the troubled commercial environment for obesity compounds to date and given the extreme high need for therapy to help patients.

Dapagliflozin Induces Ketosis in Patients with Type 1 Diabetes (949-P)

H Ghanim, N Kuhadiya, S Khan, M Garg, K Green, S Abuaysheh, and P Dandona

This poster presented data showing that the addition of dapagliflozin (AZ’s Farxiga) to liraglutide (Novo Nordisk’s Victoza) and insulin led to glycemic improvements but an increased risk of DKA in patients with type 1 diabetes. This dataset included 30 patients; we saw results for 16 patients at the AACE/ACE meeting on SGLT-2 inhibitors and DKA last October. Participants received once-daily doses of either 10mg dapagliflozin (5mg the first week) or a placebo for 12 weeks. 26 patients completed the study (17 taking dapagliflozin and 9 taking placebo), and two of the four who dropped out developed DKA within a day after increasing the dapagliflozin dose. For those who did complete the study, both A1c and average glucose were decreased in patients taking dapagliflozin compared to placebo (-0.66% vs. 0% and -15 mg/dl vs. +3.1 mg/dl, respectively). In addition, the incidence of hypoglycemia was comparable between the two groups (28% with placebo and 30% with dapagliflozin). As expected, patients on dapagliflozin had increased glycosuria, urine volume, blood glucagon, and free fatty acid concentrations compared to those on placebo. Notably, patients on dapagliflozin also had increased plasma concentrations of acetoacetate and urinary ketone bodies as well as increased concentrations of hormone sensitive lipase (indicating increased lipolysis), suggesting an increased risk of DKA. The authors concluded that caution must be exercised when decreasing insulin doses and increasing dapagliflozin doses in type 1 diabetes. Many in the field have gone further and advised against any off-label use of SGLT-2 inhibitors in type 1 diabetes outside of clinical trials until the risk of DKA is better understood. We agree that this is prudent advice in most cases, though some clinicians like Dr. Anne Peters (USC, Los Angeles, CA) with extensive knowledge of this issue (to say nothing of her patients) have been able to make it work. We advocate for patients understanding risks well and making personalized benefit/risk tradeoffs.

Empagliflozin and Microvascular Outcomes in EMPA-REG OUTCOME (1086-P)

C Wanner, C Lee, HJ Woerle, M Mattheus, SE Inzucchi, B Zinman

This poster presented the microvascular outcomes data of the EMPA-REG OUTCOME trial, finding that empagliflozin used in addition to standard of care reduced the risk of a composite microvascular outcome in people with type 2 diabetes and high CV risk, driven by a reduction in new or worsening nephropathy. The trial included 7,020 patients with a median treatment duration of 2.6 years and median observation time of 3.1 years, with final vital status available for 99% of patients. The trial defined composite microvascular outcome as time to the first incidence of a number of possible events: initiation of laser therapy for retinopathy or of renal replacement therapy, vitreous hemorrhage, diabetes-related blindness, progression of nephropathy, doubling of serum creatine with eGFR of at most 45 mL/min/1.73m2, or death caused by renal disease. The composite microvascular outcome occurred in a significantly lower percentage of patients on empagliflozin (pooled; 14.0%) than placebo (20.5%; HR of 0.62 [95% CI 0.54, 0.70]; p<0.001). Specifically, the hazard ratios for initiation of laser therapy for retinopathy, vitreous hemorrhage, and new or worsening nephropathy were 0.69 (0.43, 1.12) (p=0.134), 0.93 (0.51, 1.71) (p=0.815), and 0.61 (0.53, 0.70) (p<0.001), respectively. The overall reduction was thus primarily driven by the reduced incidence or decreasing severity of nephropathy in the empagliflozin group relative to placebo.

  • Of the participants, 4,687 received empagliflozin and 2,333 received placebo. All participants had type 2 diabetes (A1c 7%-9% for drug-naïve patients and 7.0%-10% for those on stable glucose lowering therapy), established cardiovascular disease, and eGFR of at least 30 mL/min/1.73m2. Participants received either placebo, 10 mg dose of empagliflozin, or 25 mg dose. The study continued until at least 691 participants experienced an event included in the primary outcome: cardiovascular death, non-fatal myocardial infarction, or non-fatal stroke.

Impact of Exposure to SGLT2 Inhibitors on Incidence of Diabetic Ketoacidosis Among Danish Type 2 Diabetes Patients (1098-P)

M Linnemann Jensen, B Carstensen, G Anderson, F Persson, J Nolan, M Ridderstråle, and M Jørgensen

This observational study by the prestigious Steno Diabetes Center aimed to determine the relationship between exposure to insulin, SGLT-2 inhibitors, and other glucose-lowering drugs and the incidence of DKA in a Danish population with type 2 diabetes. The study included 415,670 Danish residents with diabetes who had at least had one filled prescription for a glucose-lowering drug between 1995-2015; drug exposure length was recorded from the first prescription fill. Results demonstrated 4,045 total DKA events over the 20-year period, translating to an incidence of 1.34 events/1,000 patient-years. We were encouraged to see that the DKA incidence rate decreased by 5.6% per year between 1995 and 2015, perhaps suggesting improvements in glucose control or diagnosis/treatment of DKA. The analysis found that exposure to any glucose-lowering drug led to a significant 30% increased risk of DKA relative to no treatment. In terms of specific therapies, patients on insulin had the highest incidence of DKA at 6.0 events/1,000 patient-years; exposure to insulin led to a six-fold increased risk. Most notably, exposure to an SGLT-2 inhibitor on top of insulin and other glucose-lowering drugs carried a hazard ratio of 2.5 (95% CI: 1.1-5.5) based on six events among 4,524 patients. Overall, the authors concluded that although the addition of an SGLT-2 inhibitor may increase the risk of DKA, this increased risk may not be clinically relevant given the low absolute event rate. Their main conclusion was that DKA was and is rare in type 2 diabetes, both with and without SGLT-2 inhibitor therapy. These results are consistent with the consensus from last fall’s AACE/ACE meeting that while SGLT-2 inhibitors may increase the risk of DKA in type 2 diabetes, the absolute event rates are too low to warrant any major changes in prescribing patterns. 

Improved Treatment Satisfaction in People with Type 1 Diabetes Mellitus (T1DM) Treated with Canagliflozin (CANA) (1184-P)

AL Peters, HW Rodbard, A Slee, and S Traina

This poster investigated patient satisfaction among patients with previously uncontrolled type 1 diabetes who were treated with J&J’s SGLT-2 inhibitor Invokana (canagliflozin). The study’s analysis was based on patient-reported outcomes from an 18-week, randomized, double-blind, placebo-controlled study of patients with type 1 diabetes who were on background basal insulin plus bolus therapy. Patients were randomized to either canagliflozin 100 mg, 300 mg, or placebo, with treatment satisfaction assessed at baseline and at week 18 using the two versions of the Diabetes Treatment Satisfaction Questionnaire (DTSQ) – DTSQ status (DTSQs, which measures baseline satisfaction) and DTSQ change (DTSQc, which measures changes in satisfaction). As background, DTSQs scores range from 0 to 36 with higher scores indicating greater satisfaction. DTSQc scores range from -18 to +18, with positive scores indicating increases in satisfaction compared to baseline. The findings demonstrated that the canagliflozin-treated arms showed greater increases in DTSQc compared to placebo, though all participants improved in all six categories of the DTSQc regardless of treatment group. Notably, canagliflozin-treated patients spent much less time in hyperglycemia and hypoglycemia. Product-method mediation analysis indicated that reduction in total insulin dose and reduction in glycemic variability was responsible for between 4% and 9% of the change in satisfaction with canagliflozin. Concluding, the study suggested that decreased doses of insulin, glycemic variability, and body weight may contribute to the increase in satisfaction among canagliflozin-treated patients. However, the levels and factors of contribution to this rise in satisfaction has not been precisely determined. With these findings, the poster’s authors note that not only can such therapies increase satisfaction, but they may also improve adherence.

  • Baseline demographics and diabetes characteristics were similar among the three patient groups. A1c levels were 7.9%, 7.9%, and 8% for the placebo, canagliflozin 100 mg, and 300 mg groups, respectively. Mean ages were 41.8, 42.2, and 42.6 years for the placebo, canagliflozin 100 mg, and 300 mg groups, respectively. BMI measurements were also similar.
  • Canagliflozin 100 and 300 mg reported higher increases in satisfaction after 18 weeks. Baseline DTSQs scores were very similar (29.0, 28.4, and 28.6 with canagliflozin 100 mg, 300 mg, and placebo, respectively). However, at the end of the trial, those patients treated with canagliflozin showed greater improvements in treatment satisfaction compared to those on placebo. In addition, patients in the canagliflozin-treated groups showed DTSQc scores that were 4.8 (1oo mg) and 5.5 (300 mg) points higher than the placebo group.

Symposium: The Good Heart, the Bad Bone, and the Ugly Alpha Cell – What About them SGLT2 Inhibitors?

Potential Benefits of SGLT-2 Antagonists in Prevention and Safety of Use in Patients with Heart Failure

David Aguilar, MD (Baylor College of Medicine, Houston, TX)

Dr. David Aguilar provided a cardiologist’s perspective on the intersection between heart failure and diabetes and suggested that a diuretic effect is the most plausible explanation for the heart failure benefit seen in EMPA-REG OUTCOME. He reviewed evidence demonstrating that diabetes and heart failure often coexist and are a dangerous combination. He noted that cardiologists treating heart failure have historically viewed diabetes drugs in terms of potential increased risk and celebrated the potential for a more positive view in light of the EMPA-REG OUTCOME results. Dr. Aguilar provided a long list of potential mechanisms for the reduced risk of heart failure hospitalization seen in the trial: glucose control, weight loss, adverse effects of other medications in the placebo group, uric acid reduction, blood pressure lowering, reduced preload and afterload, volume/sodium depletion, and renal effects. Of these, he (like many others) believes that a diuretic effect is the most plausible explanation; he suggested that patients with existing diastolic dysfunction could be especially sensitive to the effects of a mild diuretic. He also granted some credence to the ketone body utilization hypothesis put forward by Dr. Ele Ferrannini and Dr. Sunder Mudaliar earlier in the day but stated that much more work needs to be done to validate it. He also noted that positive hemodynamic effects and reductions in arterial stiffness are potential explanations as well; he described the other possibilities as unlikely due to the small effect size and/or lack of a demonstrated connection to cardiovascular outcomes. Dr. Aguilar suggested that the mechanism underlying the CV death reduction is even less clear than that underlying the heart failure benefit and called for further studies to elucidate it.

Questions and Answers

Q: For all the outcomes we’re looking at, there was no dose effect. I don’t know what the explanation is, but we might want to think about that.

A: Perhaps maximal diuresis occurs with the lower dose. If you look at volume depletion it’s not that different.

Q: If the answer is diuresis, I’m frankly puzzled. Most patients with known heart failure are already on diuretics, and they’re often instructed to adjust them to maintain weight. Why would a different form of diuresis perhaps act as a superior mechanism to reduce heart failure risk and potentially death?

A: That’s a super question. The answer is yes, it is different. As for the follow-up question of why, I don’t know. There are other neurohormonal changes with activation of RAS, but we have a body of literature showing that loop diuretics don’t change survival. What’s different? Why doesn’t heart rate increase? We don’t have good explanations. Maybe there’s something different in kidney signaling related to glycosuria.

Comment: I agree it’s not atherosclerosis. Another syndrome people with diabetes also get is microvascular cardiomyopathy and no one’s addressing that. There might be a signal that the brain is affected by SGLT-2 inhibitors. There’s a paper on arterial compliance, but I don’t put a lot of emphasis on that. It probably was a reduction in blood pressure.

A: I agree there might be effects on arterial compliance. That was a small study, so there’s not a lot of data behind it, but it did change a little. I really think we need more data, and there’s a potential role for microvascular function. Maybe if someone has an infarct they’re less susceptible to arrhythmias.

Understanding the Risk of DKA when Hyperglycemia is Treated with SGLT-2 Inhibitors

Simeon Taylor, MD, PhD (University of Maryland, Baltimore, MD)

Dr. Simeon Taylor reviewed the available evidence on the risk of DKA with SGLT-2 inhibitors and offered a set of clinical recommendations. His main hypothesis is that SGLT-2 inhibitors increase susceptibility to other precipitating factors for DKA (e.g., insulin dose reductions, pump failure, infection, surgery) but do not themselves cause overt ketoacidosis. He reviewed mechanistic evidence demonstrating that SGLT-2 inhibitors promote a shift from carbohydrate to lipid metabolism, somewhat comparable to the body’s response to starvation. This leads to significantly higher levels of ketone bodies in the blood, which makes patients more vulnerable to overt DKA under the right circumstances. With the caveat that this dataset is far from perfect, he also reviewed FDA Adverse Event Reporting System (FAERS) data on the rates of SGLT-2 inhibitor-associated DKA, concluding that there appears to be an approximately 14-fold increased risk of ketoacidosis among SGLT-2 inhibitor-treated patients compared to DPP-4 inhibitor-treated patients. However, this may overestimate the risk because at least 30% of the SGLT-2 inhibitor-associated reports of ketoacidosis were observed in type 1 rather than type 2 diabetes. If the type 1 diabetes-associated reports are removed from the database, then Dr. Taylor estimated a five to 10-fold increased risk in type 2 diabetes. As for the clinical implications, Dr. Taylor advised against prescribing the class off-label in type 1 diabetes, as titrating insulin to avoid both DKA and severe hypoglycemia is very challenging. As he put it, “treating people with type 1 diabetes is like trying to thread a needle, and SGLT-2 inhibitors narrow the width of the eye of the needle.” He did stress that he is open to further research on the class in type 1 diabetes, citing the possibility for non-glycemic benefits like amelioration of renal hyperfiltration. In type 2 diabetes, Dr. Taylor suggested that key risk factors for DKA include surgery, low-carb diets, rapid weight loss, and insulin deficiency. He even suggested that clinicians consider avoiding SGLT-2 inhibitors entirely in truly insulin-dependent patients, regardless of diagnosis. He closed by cautioning against relying on urine ketone tests or severe hyperglycemia to diagnose DKA, as there is evidence that SGLT-2 inhibitors can actually reduce ketonuria by promoting reabsorption of ketone bodies and a number of the reported cases of DKA have occurred at blood glucose levels <250 mg/dl.

  • As a sidenote/postscript to Dr. Taylor’s talk, we note that we have been surprised to learn how many patients with both type 1 and type 2 diabetes do not have experience identifying DKA (2/5 of those with type 2 diabetes in a recent dQ&A survey say they are not confident they could recognize the symptoms of DKA), do not have a ketone meter even if they are on an SGLT-2, and may not have insurance coverage for ketone meters and strips. Although we agree the DKA risk can be managed for patients, we do not think patients in the US (and possible elsewhere) have appropriate education in this sphere. For more information on this data, contact Richard Wood (richard.wood@d-qa.com). 

Questions and Answers

Q: The evidence seems to be that the effects of this class in general are not dose-dependent but the risks including DKA and bone fractures are dose-dependent.

A: I think it depends on which benefits you’re talking about. They may have some degree of dose dependence. A1c lowering is slightly more at the higher dose. I think the peak effect is maximized at the lower dose, but the biggest difference is 24 hours later; when you use the higher dose it’s still giving you something but the lower dose is falling off at the end. There could be complex factors relating to whether you need 24-hour coverage.

Q: Can you speculate about the use of SGLT-2 inhibitors in type 1 diabetes?

A: They are not approved in type 1 diabetes and I absolutely do not recommend them. I think it’s a legitimate research question but I don’t think the drug should be used routinely in type 1 diabetes. Clearly some people can take them safely, but the real question is what is the proven benefit of using it? But I don’t want to use my personal opinions. The drugs are simply not approved there.

Q: Based on the presentations at the AACE/ACE consensus conference, quite a few patients developed DKA without antibodies, so I don’t think that’s a helpful way to rule it out. The pharmaceutical companies excluded people with high A1cs from their trials, and it was those people with high A1cs and low insulin secretory ability who got DKA.

A: I agree, I don’t think it’s a full explanation but it’s possible that patients with antibodies have greater risk.

ADA Diabetes Care Symposium: Lagniappe – A Little Something Different

The EMPA-REG Outcome Study Enigma: Are Fuel Energetics the Answer? Cardioprotection in EMPA-REG: A Thrifty Fuel Hypothesis

Ele Ferrannini, MD (University of Pisa, Italy)

Dr. Ele Ferrannini hypothesized that a shift toward ketone body metabolism could have been responsible for the cardioprotective effect in EMPA-REG OUTCOME. This hypothesis was also outlined in a paper just published in Diabetes. Dr. Ferrannini explained that patients with type 2 diabetes have consistently higher lipid oxidation than people without diabetes, and the glucosuria produced by SGLT-2 inhibitors amplifies this effect by decreasing glucose and insulin levels and increasing glucagon levels. This effect has become a common point of discussion over the past year in the context of the potential increased risk of DKA, but Dr. Ferrannini suggested that it could produce positive effects as well. In his model, the increased availability of lipid substrates leads the liver to produce more ketone bodies, which are then taken up by the heart. Ketone bodies are very efficient fuel sources, meaning that at any given level of oxygen they generate more ATP compared to other substrates like glucose. Dr. Ferrannini noted that SGLT-2 inhibitors also lead to increased hematocrit (the ratio of oxygen-carrying red blood cells to total blood volume) and therefore could increase oxygen delivery to the heart. That combination of more oxygen and more efficient energy utilization could improve the heart’s contractile ability and lessen the strain on a failing heart. Dr. Ferrannini emphasized that this is only a hypothesis and that it should not preclude other more “conventional” explanations such as a diuretic effect, but it certainly adds an interesting new dimension to the discussion. At a BI/Lilly-sponsored corporate symposium later that evening, Dr. Lawrence Blonde (Ochsner Health System, Jefferson, LA) and Dr. Carol Wysham (Rockwood Clinic, Spokane, WA) both described this hypothesis as very compelling, and we are sure we have not heard the last of it.  

The EMPA-REG Outcome Study Enigma: Are Fuel Energetics the Answer? Ketone Bodies in Diabetic Heart Failure and Kidney Disease: Friend or Foe?

Sunder Mudaliar, MD (UCSD, San Diego, CA)

Dr. Sunder Mudaliar outlined a similar fuel energetics hypothesis as that presented by Dr. Ele Ferrannini (also published in a paper in Diabetes) to explain the renal protective effects demonstrated in EMPA-REG OUTCOME. He explained that the kidneys have very high energy needs and rely primarily on oxidative metabolism – their level of oxygen consumption is second only to that of the heart. The kidneys’ workload and oxygen requirements are even higher in diabetes due to abnormally high glucose reabsorption, and Dr. Mudaliar noted that the resultant renal hypoxia and oxidative stress are increasingly being recognized as independent pathways involved in the progression of chronic kidney disease. SGLT-2 inhibitors could relieve some of this stress by shifting renal metabolism toward ketone bodies instead of oxygen. Because ketone bodies are a more efficient fuel source, the kidneys do not need to expend as much energy or consume as much oxygen. Dr. Mudaliar acknowledged that these changes are subtle but argued that they could translate to large differences in clinical outcomes over time. That said, he emphasized that this model is only a hypothesis and advocated for more studies measuring oxygen consumption in the kidneys and heart to test it.

Insulin Therapy

Oral Presentations: Treatment Choices after Orals in Type 2 Diabetes

Clinical Impact of Titratable Fixed-Ratio Combination of Insulin Glargine/Lixisenatide vs. Each Component Alone in Type 2 Diabetes Inadequately Controlled on Oral Agents: LixiLan-O Trial

Julio Rosenstock, MD (University of Texas Southwestern Medical Center, Dallas, TX)

Dr. Julio Rosenstock presented results from the phase 3 LixiLan-O trial demonstrating significantly greater A1c reductions with Sanofi’s iGlarLixi (formerly LixiLan) vs. either of its components in patients with type 2 diabetes on oral agents. Sanofi announced topline results from the trial in July 2015 and the dataset was included in the company’s briefing documents for the recent FDA Advisory Committee meeting for iGlarLixi. The open-label trial randomized 1,170 patients with type 2 diabetes not at goal on metformin and another oral agent to receive either iGlarLixi (n=469), Lantus (insulin glargine; n=467), or lixisenatide (n=234) for 30 weeks. A1c reductions were significantly greater with iGlarLixi (1.6%) vs. both Lantus (1.3%) and lixisenatide (0.9%) (baseline = 8.1%; p<0.0001). A significantly higher percentage of patients achieved an A1c <7% with the combination (74%) compared to Lantus (59%) and lixisenatide (33%). Fasting plasma glucose reductions were comparable with iGlarLixi (62 mg/dl) and Lantus (59 mg/dl) and less impressive with lixisenatide (27 mg/dl) (baseline = 176-178 mg/dl; p<0.0001). As expected, lixisenatide’s greatest contribution was on postprandial glucose. iGlarLixi was superior to both Lantus (by 43 mg/dl) and lixisenatide (by 20 mg/dl) on two-hour postprandial glucose; the combination was superior to Lantus (by 38 mg/dl) but inferior to lixisenatide (by 16 mg/dl) on postprandial glucose excursions. Seven-point glucose profiles showed lower overall glucose throughout the day with iGlarLixi and lower peaks compared to Lantus, especially at breakfast. The combination also demonstrated a 1.4 kg weight benefit compared to Lantus and allowed a significantly higher percentage of patients to achieve the composite endpoint of A1c <7% with no weight gain (43% vs. 25% with Lantus and 28% with lixisenatide).

  • Especially relevant in light of the AdComm discussion, Dr. Rosenstock highlighted the potential for dosing flexibility with the two iGlarLixi pens. Sanofi plans to market iGlarLixi in two pens, one (pen A) with a 2:1 insulin glargine/lixisenatide ratio and insulin doses ranging from 10-40 U/day and another (pen B) with a 3:1 insulin glargine/lixisenatide ratio and insulin doses ranging from 40-60 U/day. Dr. Rosenstock emphasized that this allows insulin titration up to 60 U without going above the maximum dose of 20 mcg lixisenatide. Data on the final dose distribution in LixiLan-O showed that 56% of patients achieved good control with pen A, 44% required intensification to pen B, and only 8% reached the maximum dose of 60 U without achieving target. A number of panelists at the AdComm meeting expressed concerns about distinguishing between the two pens and about the nomenclature of “units” used to dose the combination. These concerns were fairly unexpected to us, and we hope Sanofi and the FDA can work together to resolve them in short order.
  • Adverse events were generally similar between groups in the trial. Nausea rates were substantially lower with iGlarLixi (9.6%) compared to lixisenatide (24%), confirming one of the main expected with these combinations compared to GLP-1 agonists alone. Dr. Rosenstock highlighted the fact that only 0.4% of the iGlarLixi group discontinued treatment due to nausea (compared to 2.6% in the lixisenatide group). The rate of documented symptomatic hypoglycemia was low and comparable between the iGlarLixi and Lantus groups (1.4 vs. 1.2 events/patient-year).

Questions and Answers

Q: Given the short duration of action of lixisenatide, might it make more sense to use it twice a day?

A: That sounds like common sense but you don’t need to. With the results you get, why would you need to? You get an effect on postprandial glucose mainly in the morning, you do have some carry over for lunch, and by dinner there’s not much, but you get down to 6.5%. We shouldn’t use it twice a day because it’s not approved.

Q: Would you use it twice a day if A1c deteriorates over time?

A: I don’t know. We need longer-term studies.

Q: I’d like to see a study where you challenge the fixed-ratio combination not only to glargine + lixisenatide but to degludec + liraglutide, comparing the fixed ratio with split injections. I think it would highlight the convenience of the fixed ratio and on the other side the ability to individualize the combination because we know patients have different characteristics.

A: There’s no question that what you suggest would be a nice study. The question is whether simultaneous therapy is better than sequential. All these years we’ve done sequential. We have a bit of indirect evidence on this from GetGoal Duo 1, where patients were on basal insulin for 12 weeks and then added lixisenatide. That got people down to 7% and here we got down to 6.5%. The important bottom line is that we get down to 6.5%. The same was true with IDegLira. Both combinations get people down to levels we were never able to get before with any of the components alone.

Q: What concentration of insulin glargine was used?

A: U100.  

Oral Presentations: Beyond Basal Insulin in Type 2 Diabetes – Treatment Intensification Options

Efficacy and Safety of the Insulin Glargine/Lixisenatide Fixed-Ratio Combination vs. Insulin Glargine in Patients with T2DM: The LixiLan-L Trial

Vanita Aroda, MD (MedStar Health Research Institute, Hyattsville, MD)

Dr. Vanita Aroda presented results from the phase 3 LixiLan-L trial demonstrating significantly greater A1c reductions with Sanofi’s iGlarLixi (formerly LixiLan) vs. Lantus (insulin glargine) in patients with type 2 diabetes on basal insulin, driven by improvements in postprandial glucose. Sanofi announced topline results from the trial in September 2015 and the dataset was included in the company’s briefing documents for the FDA Advisory Committee meeting for iGlarLixi. The open-label trial randomized 736 patients not at goal on basal insulin and oral drugs to treatment with iGlarLixi (n=367) or Lantus (n=369) for 30 weeks. The insulin glargine dose in both groups was titrated to a fasting glucose target of 80-100 mg/dl and the dose was capped at 60 U/day (to match the maximum dose in the combination). A1c reductions were significantly greater with iGlarLixi (1.2%) than Lantus (0.6%) (baseline = 8.1%). A significantly higher percentage of patients achieved an A1c <7% with iGlarLixi (55%) than with Lantus (30%; p<0.0001). Fasting plasma glucose reductions were similar in both groups (21 mg/dl vs. 23 mg/dl), as expected given the almost identical average daily doses of insulin glargine at the end of the trial (46 vs. 47 U). The main contribution of lixisenatide to the combination was on postprandial glucose: iGlarLixi produced significantly greater reductions in both two-hour postprandial glucose (85 mg/dl vs. 25 mg/dl) and postprandial excursions (70 mg/dl vs. 8 mg/dl) compared to Lantus. Seven-point glucose profiles illustrated this improvement in postprandial control, particularly after breakfast. iGlarLixi led to a 1.4 kg weight benefit and comparable hypoglycemia rates to Lantus. The combination also allowed a greater percentage of patients to achieve an A1c <7% without weight gain (34% vs. 13%), an A1c <7% without hypoglycemia (32% vs. 19%), and an A1c <7% without weight gain or hypoglycemia (20% vs. 9%) – while the benefit is encouraging, the low absolute percentages in both groups illustrate the remaining need for more effective therapies.

Questions and Answers

Q: Do you think the weight loss is less when lixisenatide is used in combination with insulin vs. separately when added to insulin or without insulin?

A: I would refer you to the LixiLan-O trial, where we saw greater weight loss with lixisenatide alone. Here we have mitigation of the weight gain with insulin glargine.

Q: But the average weight loss seems to be less here than when you add on a GLP-1 agonist without insulin or even separately.

A: Part of it might be the final dose, which was 17 mcg of lixisenatide on average.

Q: I’m guessing the combination was administered before breakfast. Was the administration of glargine alone done at the same time?

A: Glargine could be administered at any time and it was consistent throughout the trial. The combination was injected an hour before breakfast.

Q: From the seven-point profile, it’s obvious that the main effect is on that first meal, yet it was a fixed schedule of dosing before breakfast. Do you think the results would be different if it was administered with the largest meal rather than breakfast? My patients don’t all eat breakfast, and dinner is typically the biggest meal in the US.

A: That’s an intriguing question that can only be answered by a trial. There was a sub-study looking at dosing at the main meal vs. the morning and the main effect seems to be in the morning, but we would need a trial to know.

Q: You didn’t save a single dose of insulin by adding lixisenatide and you had the same rate of hypoglycemia. Is there any information on the PK/PD data? Were the profiles of both components really preserved? It seems like a very weak effect.

A: The PK data were consistent with what was seen in the lixisenatide standalone program. Your point is appreciated that there’s not necessarily an insulin-sparing effect. I would also state here that we had a greater A1c reduction down to 6.9% without increased hypoglycemia. We’re looking at two different end A1cs with comparable hypoglycemia.

Q: Looking at the meal data in the control group, you still have glucose values of 230 mg/dl two hours after a meal – people are clearly not well controlled. Would you anticipate different results if you had a more well-controlled group?

A: The 230 mg/dl was from a mechanistic substudy highlighting the mechanism of action of iGlarLixi on postprandial glucose. The 7-point SMPG, reflective of control in the comparator group, showed the control we typically see with titration with insulin glargine (postprandial glucose of 160s-190s during the day). This, along with detailed review of titration, superimposable fasting glucoses, and insulin doses all support appropriate titration in the control group.

Faster-Acting Insulin Aspart vs. Insulin Aspart as Part of Basal-Bolus Therapy Improves Postprandial Glycemic Control in Uncontrolled T2D in the Double-Blind onset 2 Trial

Keith Bowering, MD (University of Alberta, Edmonton, Alberta, Canada)

Dr. Keith Bowering presented results from the phase 3 Onset 2 trial demonstrating non-inferior A1c reductions and significant improvements in postprandial control with Novo Nordisk’s faster-acting insulin aspart vs. NovoLog (insulin aspart) in patients with type 2 diabetes. The double-blind study enrolled 689 patients who were randomized to receive either faster aspart or NovoLog for 26 weeks in addition to Sanofi’s Lantus (insulin glargine) and metformin. A1c reductions were comparable in both groups: A1c dropped from 8% to 6.6% with faster aspart and from 7.9% to 6.6% with NovoLog. Faster aspart produced a significant 10.6 mg/dl improvement in one-hour postprandial glucose (p=0.0198) and a numerical but not significant improvement of 6.6 mg/dl in two-hour postprandial glucose. Fasting glucose and three- and four-hour postprandial glucose was comparable in both groups, and both products led to a 2.7 kg weight gain. Adverse event rates and overall hypoglycemia rates were also balanced; there were numerically more severe hypoglycemia events in the faster aspart group (27 vs. 17 events), but Dr. Bowering explained that 18 of the events in the faster aspart group occurred in the same three patients, likely skewing the results. These results are consistent with our sense that faster aspart offers a real but incremental improvement over existing rapid-acting insulins. The improvement in postprandial glucose and the potential for more dosing flexibility should be meaningful for many patients, but we do not expect faster aspart to be a transformational therapy in the same league as other Novo Nordisk products like Xultophy (insulin degludec/liraglutide) and semaglutide.

Questions and Answers

Q: You started by showing area under the curve for the first 30 minutes. You didn’t show more classical endpoints like total area under the curve or Cmax. Do you have any data on that?

A: That is available in a poster here. I believe Cmax was 10 minutes earlier than standard aspart.

Q: What was the time between the injection of insulin and the start of the meal? Could the dosing be more flexible? Based on the Biodel studies, there might be less late hypoglycemia. Did you see anything like that?

A: They were supposed to inject within two minutes of a meal. There was a small number of hypoglycemic events in the first two hours, and in that time frame there was more hypoglycemia seen with faster aspart than standard aspart. Those numbers were small in comparison with the later events.

Adding Faster-Acting Insulin Aspart to Basal Insulin Significantly Improved Glycemic Control: The Onset 3 Trial

Helena Rodbard, MD (Endocrine and Metabolic Consultants, Rockville, MD)

Dr. Helena Rodbard (Endocrine and Metabolic Consultants, Rockville, MD) presented results from the Onset 3 trial of Novo Nordisk’s faster-acting insulin aspart in patients on basal insulin. The 18-week, open-label, parallel group trial (n=236 patients with type 2 diabetes on basal insulin therapy) found that intensification to a basal-bolus regimen with faster-acting aspart resulted in a statistically superior mean A1c reduction of 0.94% (baseline A1c=7.9%; p<0.0001) compared to continued treatment with basal insulin alone. Furthermore, 60% of those in the faster-acting insulin aspart group achieved an A1c <7% at the end of the 18 weeks (compared to 18% in the basal-only group, p<0.0001) and 45% achieved an A1c ≤6.5% (compared to 7% in the basal-only group, p<0.0001). Even more impressively, in the faster-acting insulin aspart group, 59% were able to achieve the target A1c <7% without experiencing severe hypoglycemia (compared to 7% with basal-only, p<0.0001) and 43% were able to achieve the target A1c ≤6.5% without experiencing severe hypoglycemia (compared to 7% with basal-only, p<0.0001). 8-point SMPG profiles indicated improved glycemic control with faster-acting insulin aspart at all points in throughout the day. Regarding postprandial glucose (PPG) specifically, 81% of participants taking faster-acting insulin aspart were able to achieve a PPG ≤140 mg/dl (compared to 22% in comparator arm, p<0.0001) and 80% were able to do so without severe hypoglycemia (compared to 21% in comparator arm, p<0.0001). Fasting plasma glucose (FPG), on the other hand, was not significantly different between the two arms. As expected and consistent with prandial insulin intensification, adverse events included weight gain (mean weight gain=1.66 kg in the faster-acting insulin aspart group) and increased rate of hypoglycemia.

Oral Presentations: Novel Therapeutics in Type 1 Diabetes

Double-Blind Mealtime Faster-Acting Insulin Aspart vs. Insulin Aspart in Basal-Bolus Improves Glycemic Control in T1D: The Onset-1 Trial

David Russell-Jones (Royal Surrey County Hospital, University of Surrey, UK)

Dr. David Russell-Jones gave us our first full look at results from the Onset 1 trial, which examined Novo Nordisk’s faster-acting insulin aspart formulation (Faster aspart) in type 1 diabetes. As a reminder, Novo Nordisk shared topline results from Onset 1 & 2 in early 2015 and submitted Faster aspart to the FDA at the end of last year. Onset 1 found a modest but statistically significant improvement in A1c with Faster aspart (-0.17% vs. standard aspart) with no increase in severe or confirmed hypoglycemia. In our view, among the most important findings among the new data were: (i) in addition to the modest A1c benefits, two-hour postprandial blood glucose levels were superior with Faster aspart than regular aspart (by ~12 mg/dl), and (ii) in terms of A1c reduction, post-meal Faster aspart administration was non-inferior compared to standard pre-meal administration of the current insulin aspart. The latter finding makes for a pretty cool claim and stands to make a difference for patients who find it challenging to consistently take their insulin pre-meal, though it bears remembering that although post-meal Faster aspart was comparable with pre-meal NovoLog, pre-meal Faster aspart was still the winner in this trial.

  • Study design: Onset 1 randomized 1,143 type 1 diabetes patients on basal-bolus therapy with Levemir (insulin detemir) and NovoLog (insulin aspart) to either stay on that treatment regimen, switch the NovoLog for Faster aspart dosed pre-meal, or to switch to Faster aspart dosed post-meal. The main portion of the trial ran for 26 weeks. Average age at baseline was in the mid-40s, with a mean BMI around 26 kg/m2 and mean A1c of 7.6%.

Questions and Answers

Q: Was the total dose at the end of the study similar?

A: Yes, they were similar across groups. Because of continuous bolus titration, there was a slight increase from baseline in bolus dose after titration.

Q: Was the insulin dosed at the time of the meal or 20 minutes before?

A: At the onset of the meal.

Q: I would have expected that the Faster aspart group might have had less delayed hypoglycemia if it is more rapid-on, rapid-off. Was there any CGM data?

A: There was no difference in nine-point profiles.

Q: I’m surprised that insulin doses were adjusted based on premeal glucose, because the main benefit was post-meal. Wouldn’t you expect better results if you targeted post-meal control rather than premeal results?

A: I think in clinical trials, post-meal glucoses are much more variable. It’s safer to do protocol as defined. As you can see, people did see a reduction in A1c.

Q: Did you see any benefits in hypoglycemia immediately post-meal?

A: Overall, the rate of hypoglycemia was similar. If you were going to have a hypoglycemic episode right at the beginning, which is a pretty low proportion of overall cases, you had a slightly higher chance with Faster aspart, which you would expect. But the overall rate was incredibly low.

Q: How should we think about nutrient matching with this insulin? What would happen with a high fat meal, or someone who is a very marked carbohydrate restrictor? Would that potentially lead to a dangerous risk of hypoglycemia early after the meal?

A: The short answer is that those studies have not yet been done. Although Faster aspart is incrementally faster, it’s only by degrees. In practicality, I don't think that would be a problem.

Q: Why didn't you test both insulins with post-meal administration?

A: What I think is important is that this trial shows that if you use Faster aspart after a meal, you still get as much benefit as if you took ordinary aspart before the meal. A lot of patients do this sometimes, so I think this is an important finding.

Q: What about stability in insulin pumps?

A: This insulin is going to be extremely useful for people on pumps. The pump PK data is very impressive. There are a large number of pump studies ongoing, and I suspect that it will be a topic for next year’s ADA.

Efficacy and Safety of MK-1293 Insulin Glargine Compared with Originator Insulin Glargine (Lantus) in Type 1 Diabetes (T1D)

Philip Home, DPhil (Newcastle University, Newcastle Upon Tyne, UK)

Professor Philip Home presented phase 3 data showing that Merck’s Samsung-partnered biosimilar insulin glargine MK-1293 demonstrated similar efficacy and safety to Sanofi’s Lantus in people with type 1 diabetes. Professor Home presented the 24-week data of this phase 3, active-controlled, open-label, 52-week study, in which 506 participants with type 1 diabetes were randomized 1:1 to once-daily MK-1293 or Lantus, guided by a fasting glucose-based dosing algorithm. At week 24, from a baseline A1c of ~8%, the MK-1293 and Lantus groups achieved A1c reductions of 0.65% and 0.68%, respectively, meeting the non-inferiority and equivalence criteria with a difference of only 0.03%. Total insulin dose between the two arms was also similar, with the MK-1293 group on 49.4 U/day vs. the Lantus group’s 50.4 U/day. Basal and prandial insulin doses between the arms differed by 0.8 U/day and 2.3 U/day, respectively. Regarding fasting plasma glucose, MK-1293 and Lantus arms achieved reductions of 16.4 mg/dl and 25.9 mg/dl, respectively. Professor Home noted that this relatively larger difference may be due to the not-so-reliable measure of the clinic samples and pointed to the 7-point average SMPG difference as more consistent (-4.9 mg/dl for MK-1293 vs. -4.6 mg/dl for Lantus), as he called for regulators to consider CGM approaches for these measures in the future. As for the safety profile, the difference of percentage of participants experiencing symptomatic hypoglycemia remained small, with 71% and 76% of the MK-1293 and Lantus groups, respectively. Professor Home pointed out an imbalance in severe hypoglycemia (6.1 events/person-year in MK-1293 vs. 3.2 in Lantus), but highlighted that only two participants on MK-1293 were accounting for 49% of the severe episodes. For other adverse events, there were minimal treatment group differences (241 events in MK-1293 vs. 248 events in Lantus) and the anti-insulin antibody (AIA) response was similar between the two arms, with regards to cumulative incidence, neutralizing antibodies, and immunological insulin resistance. Thus, Professor Home concluded that the overall therapeutic profile of MK-1293 was similar to that of Lantus in type 1 diabetes.

  • As background, Merck recently shared that MK-1293 is filed in Europe; the candidate is one of the first three insulin glargine biosimilars (the other two being from Lilly/BI and Biocon/Mylan) and while we have not explicitly heard plans for a US filing, we would expect one to come soon alongside Europe’s. These data are certainly promising and we continue to express cautious hope that the movement of biosimilars into the market will cut down on the increasing costs of insulin for patients – we also wonder, of course, how much providers will trust these new formulations.

BioChaperone® Combo (BC Combo) Improves Postprandial Glycemia vs. Humalog® Mix 75/25™ (HMx) in People with Type 1 Diabetes Mellitus (T1DM)

Steve Edelman, MD (UCSD, San Diego, CA)

Dr. Steve Edelman presented new phase 1 data of Adocia’s BioChaperone Combo (insulin glargine/insulin lispro), demonstrating superior postprandial glycemic control compared to Lilly’s Humalog (insulin lispro) in people with type 1 diabetes. In this double-blind, randomized, crossover mixed-meal study (ClinicalTrials.gov Identifier: NCT02514954), 28 participants with type 1 diabetes (baseline A1c of 7.3%) received equivalent individualized doses of BioChaperone Combo or Humalog, immediately prior to a standardized meal (508 kcal [68 g], 56% carbs/17% protein/27% fat). Looking at the six-hour post-meal glycemic profiles, Dr. Edelman showed that starting from identical baseline blood glucose levels, BioChaperone Combo reduced post-meal blood glucose over two hours and had a lower blood glucose maximum compared to Humalog (72 mg/dl vs. 95 mg/dl), as well as a reduced PPG excursion at one hour (-24 mg/dl) compared to Humalog. Within the first two hours, BioChaperone Combo also had a comparative 24% reduction in post-prandial glucose excursions (as measured by glucose area under the curve, p=0.008). In addition, the Humalog arm experienced a late post-prandial blood glucose drop below baseline ~3.5 hours post-meal (BioChaperone Combo dropped below baseline at around 5.5 hours) and those on Humalog had a lower blood glucose minimum compared to the BioChaperone Combo group (65 mg/dl vs. 94 mg/dl). Regarding hypoglycemia, the Humalog group experienced numerically more hypoglycemic episodes than the BioChaperone Combo group (15 vs. 9 for ≤70 mg/dl; 8 vs. 4 for ≤50 mg/dl), as the BioChaperone Combo group spent more time in target (80 to 180 mg/dl) with 274 minutes vs. 183 minutes. On safety and tolerability, Dr. Edelman noted that there were no significant differences between treatment groups’ safety profiles with three adverse events reported in each group (mostly consisting of headaches, nausea, and flu-like symptoms) and the treatments proved to be well-tolerated with no injection site reactions. This study is one of several trials that Adocia is conducting on its insulins, as the company has also recently initiated phase 1b studies for its HinsBet (BioChaperone human insulin) and BioChaperone Lispro. These new promising findings for BioChaperone Combo prompt us to continue wondering if the product could potentially be incorporated into the Lilly partnership – please see our Adocia 1Q16 report for more on the company’s latest.

Questions and Answers

Q: How do you anticipate to see this clinical benefit?

A: To me, as someone who sees patients quite a bit, you have a more effective reduction in PPG and you have a reduced rate of delayed hypo. As you know, using current premixes, they do have a rapid acting analog but combined with insulin, they have the same PK/PD profile as NPH. This’ll impact the timing of injections and lead to hypo. And those insulins don’t last as long. Similar to the Novolog product, these types of premixes will be great for type 2 diabetes. I think that’s why a lot of clinicians don’t use these premixes – because of the PK/PD.

Q: Was it a solid or liquid meal test?

A: It was a solid meal. It was prepared in kitchen with 69 grams of carbs, proteins, and fats. It was an Italian meal.

Q: Anything done to impact the timing of the glargine component?

A: As I understand it, these molecules are basically the same. But when you put them in a combo through this technology, the time course may change. The most obvious was the lispro. I do believe that it’s the nature of the bonding of these molecules that allow the PK/PD to be different. The molecules themselves are unchanged. It’s the combo through this technology that’s affecting it.

Ultra-Rapid BioChaperone Lispro Ameliorates Postprandial Blood Glucose (PPG) Control Compared with Humalog in Subjects with Type 1 Diabetes Mellitus

Tim Heise, MD (Profil GmbH, Neuss, Germany)

Dr. Tim Heise (Profil GmbH, Neuss, Germany) presented results from a phase 1b meal study showing greater improvements in postprandial glucose with Lilly/Adocia’s ultra-rapid BioChaperone Lispro compared to Lilly’s Humalog (insulin lispro). The single-center, double-blind, randomized, single-dose, cross-over study in patients with type 1 diabetes (n=38, baseline A1c=7.4%) found that mealtime BioChaperone Lispro administration resulted in a mean one-hour postprandial glucose (PPG) difference of 42 mg/dl compared to mealtime Humalog administration (mean one hour PPG=135 mg/dl with BioChaperone Lispro vs. 177 mg/dl with Humalog, baseline blood glucose=100 mg/dl). Two-hour PPG was also lower with BioChaperone Lispro compared to Humalog, with a mean difference of 27 mg/dl (mean two-hour PPG=126 mg/dl with BioChaperone Lispro vs. 153 mg/dl with Humalog). As was previously reported in the topline results, BioChaperone Lispro administration produced a 61% reduction in two-hour postprandial glucose excursions (as measured by glucose area under the curve, p<0.0001) compared to Humalog. BioChaperone Lispro also reduced 30-minute postprandial excursions by 51% (p=0.0004), one-hour excursions by 58% (p<0.0001), three-hour excursions by 75% (p=0.0002), and eight-hour excursions by 42% (p=0.04). In terms of blood glucose concentration, BioChaperone Lispro led to a 73% reduction in one-hour post-meal blood glucose concentration (p<0.0001) and a 67% reduction in two-hour blood glucose concentration (p=0.0014). Peak blood glucose was reduced by 24% with BioChaperone Lispro administration compared to Humalog (p=0.016). Hypoglycemia rates were comparable between the BioChaperone Lispro and Humalog groups, with 18 events with BioChaperone Lispro and 19 events with Humalog. Adverse events were similar between the two groups as well; infection and headache were the most frequent adverse events and there were no severe adverse events in either group.

  • BioChaperone Lispro uses Adocia’s proprietary carrier technology, resulting in a faster-on, faster-off profile. BioChaperone Lispro reached its half-maximal concentration 37% faster than Humalog (in 18 min, compared to 29 min for Humalog). BioChaperone Lispro also achieved a 168% higher insulin exposure vs. Humalog in the first 30 minutes post-administration (p<0.0001) and a 52% higher insulin exposure in the first hour post-administration. Post-peak, BioChaperone Lispro concentration also declined 15% more rapidly than Humalog: the candidate reached its half-maximal concentration in 135 min post-administration, compared to 160 min for Humalog. Eight-hour insulin exposure, as measured by area under the curve, was 21% lower with BioChaperone Lispro. Overall, BioChaperone Lispro achieved its maximum concentration 25% faster than Humalog (after 47 min vs. 62 min) and its maximum concentration was 13% higher than Humalog (117 mU/l vs. 104 mU/l). Overall exposure was similar between the two insulins, however. These results are consistent with previous studies.
  • In Q&A, Dr. Heise suggested that the faster absorption rate of BioChaperone Lispro could support more flexible dose timing in addition to improved postprandial control. He especially sees potential for the use of BioChaperone Lispro and other ultra-rapid-acting insulins in children or elderly patients. There has been some hope that MannKind’s inhaled insulin Afrezza could serve as a convenient mealtime insulin with a more rapid absorption profile, but uptake as been sluggish due to a combination of complicated prescribing requirements and potential safety concerns - we strongly believe both barriers can and should be mitigated. The “next-generation” rapid-acting insulin analog field has not progressed as rapidly as the basal insulin analog field (where Novo Nordisk’s Tresiba [insulin degludec] has been characterized as a near-perfect basal insulin in terms of PK/PD profile), but we’re energized by the positive data that’s emerging surrounding BioChaperone Lispro and Novo Nordisk’s faster-acting insulin aspart.

Nocturnal Glycemic Control with Glargine Titration Based on Bedtime in Addition to Fasting Plasma Glucose in Type 1 Diabetes

Francesca Porcellati, MD, PhD (University of Perugia, Italy)

Dr. Francesca Porcellati presented study findings showing the benefits of an insulin titration algorithm based on the relationship between nocturnal plasma glucose (PG) and next morning fasting plasma glucose (FPG) levels. In this study, 58 participants with type 1 diabetes on basal-bolus therapy and FPG >130 mg/dl were randomized to algorithm #1 (the usual glargine titration based on FPG of six days) or algorithm #2 (based on the difference between bedtime PG and next morning FPG on days with post-dinner PG at the target 100-130 mg/dl with optimized evening prandial insulin) for three months. At three months, fasting plasma glucose decreased with both algorithms, but more so with algorithm #2 (154±17 mg/dl to 140±16 mg/dl vs. 151±18 mg/dl to 128±8 mg/dl, p<0.05). In addition, both intra-subject variability of FPG (CV 9±1.4% vs. 15±2.7%, p<0.05) and incidence of nocturnal confirmed hypoglycemia (5.4±1.4 vs, 7.6±2.7 events/patient-year) were lower on algorithm #2 compared to algorithm #1. Thus, Dr. Porcellati concluded that using an algorithm that incorporates bedtime PG may bring about several advantages in glycemic control, hypoglycemia risk, and A1c.

Questions and Answers

Q: We’re driven to overbasalize patients, largely because pharma companies have basal insulins. Why not also use this in type 2 diabetes?

A: In type 2, it’s different because if you use basal insulin, you are really following fasting. But I partly agree – for some of our patients with basal insulin, it’s important to check bedtime glucose.

Q: From my experience, I can recommend you to expect differences in type 1 diabetes. That’s why we are free to titrate basal first. The difference between bedtime and morning glucose levels is important. A three-point profile is quite simple.

A: We need to move attention more to postprandial control, which is tough to ask from patients.

Oral Presentations: Treatment and Management of Complications – Can a Dog Really Smell Hypoglycemia?

Glycemic Control and Hypoglycemia Benefits with Insulin Glargine 300 U/mL (Gla-300) Extend to People with Type 2 Diabetes (T2DM) and Mild-to-Moderate Renal Impairment

Javier Escalada MD, PhD (Clinica Universidad de Navarra, Spain)

Dr. Escalada presented a post-hoc meta-analysis of the EDITION 1, 2, and 3 trials that compared the effects of glargine 300U/ml (Gla-300) and glargine 100U/ml (Gla-100) on A1c reduction and hypoglycemia in type 2 diabetes patients with renal impairment. The meta-analysis included patients with moderate (GFR 30 to 60; n=401) or mild renal impairment (GFR 60 to 90; n=1,390), and those with normal renal function (GFR 90; n=685). Those with severe impairment (GFR <30) were excluded due to low numbers, and Dr. Escalada noted that this was a drawback to the meta-analysis. In reviewing the rationale for this analysis, Dr. Escalada stated that renal impairment increases the risk of hypoglycemia in type 2 patients, and thus may limit treatment options. Across all three subgroups, at six months, Gla-300 and Gla-100 provided similar reductions in A1c, and the percentage of patients who achieved an A1c of <7% and <7.5% was similar between the two drug doses. Of note, regardless of renal function, Gla-300 led to a lower rate of confirmed (≤70 mg/dl) or severe nocturnal hypoglycemia (rate ratio of 0.59 [95% CI: 0.39-0.90], 0.72 [0.56-0.93], and 0.69 [0.43-1.10] for the moderate, mild, normal groups, respectively), with comparable or lower rates of any-time hypoglycemic events.

  • In opening, Dr. Escalada cited the results of EDITION 1, 2, and 3 – multicenter, randomized, open-label, phase 3a studies where patients received once daily injections of glargine 300U/ml or glargine 100U/ml titrated to a fasting SMPG of 80-100 mg/dl.  EDITION 1 enrolled patients on basal and prandial insulin with or without metformin; EDITION 2 recruited patients on basal insulin and oral therapy; and EDITION 3 enrolled insulin-naïve patients taking oral therapy. The six-month data from these studies showed that in patients with type 2 diabetes, Gla-300 provided comparable glycemic control with less hypoglycemia compared to Gla-100. Post-hoc analyses have shown that these benefits persisted when controlling for age, BMI, and duration of diabetes.
  • Regarding baseline characteristics, the three groups had comparable gender balance (% male 48-54) and BMI (34-35 kg/m2). Those with moderate renal impairment were older (average age of 65 vs. 59 for mild impairment and 52-53 for normal renal function). These participants also had a longer duration of diabetes (15 years vs. 12 for mild impairment and 10 for normal renal function), as well as a longer duration of basal insulin use (5.7-6.0 vs. 5.4-5.5 for mild impairment and 4.1-4.3 for normal renal function).
  • Glargine 300 U/ml and 100U/ml provided comparable A1c reductions, a finding observed in all three subgroups (Table 1). The percentage of patients that achieved an A1c of <7% and <7.5% was similar between the two drug doses, and this result was also observed across all three subgroups (Table 2).

Table 1: A1c reductions observed with Glargine 300 U/ml vs. Glargine 100U/ml

Group

Gla-300

Gla-100

Overall

1.02

1.01

eGFR ≥90

1.00

1.10

eGFR 60-90

1.06

1.04

eGFR 30-60

0.95

0.92

Table 2: Percentage of patients that achieved an A1c of <7% and <7.5%

 

% patients achieving A1c <7%

% patients achieving A1c <7.5%

Group

Gla-300

Gla-100

Gla-300

Gla-100

eGFR ≥90

27.9

29.4

45.9

46.1

eGFR 60-90

40.1

37.4

57.9

54.6

eGFR 30-60

37.2

39.8

56.3

58.2

Table 3: Participants with at least one event of hypoglycemia

Group

n

Nocturnal (midnight – 6am)

Anytime (24 h)

 

 

Gla-300

Gla-100

Gla-300

Gla-100

Overall

2,468

371 (30%)

490 (40%)

812 (66%)

884 (72%)

eGFR 30-60

399

79 (40%)

102 (51%)

159 (80%)

160 (80%)

eGFR 60-90

1,386

225 (32%)

274 (40%)

470 (67%)

489 (71%)

eGFR ≥90

683

67 (20%)

114 (33%)

183 (55%)

235 (67%)

Questions and Answers

Q: While the relative benefit of glargine 300 is clear, one of the questions was whether there were indeed more hypoglycemic episodes in the group with decreased renal function. It was a little difficult to tell that from the slides.

A: [Dr. Escalada referred to a slide with Table 3 (shown above)]. You can see here that patients with the worse renal function had a higher percentage of patients suffering from severe hypoglycemia. So you are right that in this case, the hypoglycemia burden was higher in patients with lower eGFR.

Oral Presentations: Management of Hyperglycemia in the Hospitalized Patient (with State-of-the-Art Lecture)

Efficacy and Safety of U500 Insulin Use in Hospitalized Patients at VA Pittsburgh Health Care System (VAPHS)

Ha Nguyen, MD (University of Pittsburgh Medical Center, PA)

Dr. Ha Nguyen shared data from a retrospective chart review of 90 hospitalizations of patients on outpatient U500 insulin between 2000-2015. Dr. Nguyen shared that U500 is a concentrated human insulin that is often the best option in markedly insulin resistant diabetes, but noted that it can have deleterious side effects. Accordingly, 44 patients switched to U100 during their hospital stays, while 46 remained on U500. There was no significant difference between the two groups in mean blood glucose level or incidence of hypoglycemia, indicating that U500 insulin therapy is indeed safe in the hospital setting. However, given its inherent risks, Dr. Nguyen emphasized that U500 should be administered under the supervision of an endocrinologist and with prefilled syringes to minimize dosing errors.

Questions and Answers

Q: A recent study found that a group of patients on U500 insulin had more hyperglycemia and hypoglycemia than a group on U100 insulin; why do you think your study found different results?

A: I saw that study, actually. We believe this discrepancy is because, in that study, only 60% of patients had endocrine consult – that could be why U500 had more hyperglycemia and hypoglycemia. In our study, 95% had endocrine consult.

Posters

NOVO NORDISK'S BASAL INSULIN TRESIBA BEATS LANTUS ON HYPOGLYCEMIA IN SWITCH 1 AND 2

Novo Nordisk presented data from the phase 3b SWITCH trials in two late-breaking posters (87-LB and 90-LB) demonstrating significant reductions in overall, nocturnal, and severe hypoglycemia with Tresiba (insulin degludec) vs. Sanofi’s Lantus (insulin glargine).  We saw topline results from both SWITCH 1 (type 1 diabetes) and SWITCH 2 (type 2 diabetes) in February. Novo Nordisk plans to submit the data to regulatory authorities in 3Q16 in the hopes of gaining some sort of label update, though we will keep our expectations in check given the FDA’s historically conservative approach in this area. While we were quite impressed with the data, we were also struck by how high the hypoglycemia rates were in both groups, particularly in the type 1 diabetes trial. To us this underscores the enormous complexity of managing diabetes with current insulin therapy and illustrates the need for as many tools as possible to help patients reduce their risk. We are also starting to see we need a different narrative for patients “in control” – currently, a patient’s “control” reflects their A1c, not their A1c combined with their time spent in hypoglcyemia, which seems like a limited way to assess success.

  • SWITCH 1 demonstrated significant hypoglycemia reductions with Tresiba vs. Lantus in patients with type 1 diabetes at high risk for hypoglycemia. The double-blind trial randomized 501 patients to receive once-daily doses of Tresiba or Lantus for 32 weeks, followed by crossover to the other treatment for 32 weeks. Each 32-week period consisted of a 16-week titration period and a 16-week maintenance period, and both groups received injections of NovoLog (insulin aspart) at mealtime. Results showed a significant 11% reduction for the primary endpoint of severe or blood glucose-confirmed symptomatic hypoglycemia with Tresiba vs. Lantus during the maintenance period (event rates of 2,220.9 vs. 2,462.7 events/100 patient-years; p<0.0001). Tresiba also produced a significant 36% reduction in severe or blood glucose-confirmed nocturnal symptomatic hypoglycemia (event rates of 277.1 vs. 428.6 events/100 patient-years; p<0.0001) and a significant 35% reduction in severe hypoglycemia (event rates of 69.1 vs. 92.2 events/100 patient-years; p<0.05) in the maintenance period compared to Lantus. Results were similar for the full treatment period with significant reductions of 6%, 25%, and 26% with Tresiba vs. Lantus for the three respective endpoints. The results for other efficacy and safety parameters were comparable between groups; a post-hoc analysis found a 3% significantly lower total daily insulin dose in the Tresiba group.
  • SWITCH 2 demonstrated significant hypoglycemia reductions with Tresiba vs. Lantus in patients with type 2 diabetes at high risk for hypoglycemia. The double-blind trial randomized 721 patients to receive once-daily doses of Tresiba or Lantus in addition to oral diabetes drugs (excluding sulfonylureas/meglitinides) for 32 weeks, followed by crossover to the other treatment for 32 weeks, with the same titration/maintenance periods as in SWITCH 1. Results showed a significant 30% reduction in severe or blood glucose-confirmed symptomatic hypoglycemia with Tresiba vs. Lantus during the maintenance period (event rates of 185.6 vs. 265.4 events/100 patient-years; p<0.0001). Tresiba also produced a significant 42% reduction in severe or blood glucose-confirmed nocturnal symptomatic hypoglycemia (event rates of 55.2 vs. 93.6 events/100 patient-years; p<0.0001). Rates of severe hypoglycemia were low in both groups and numerically but not significantly lower with Tresiba (event rates of 5.3 vs. 9.1 events/100 patient-years; p-value not given). Results were similar for the full treatment period with significant reductions of 23% and 25%, respectively, for the first two endpoints and a 51% reduction in severe hypoglycemia that just reached statistical significance (p=0.03). The results for other efficacy and safety parameters were comparable between groups; a post-hoc analysis found a 4% significantly lower insulin dose in the Tresiba group.

Similar Glucose Control, Postprandial Glucose Excursions, and Safety in People with T1DM Using SAR342434 or Insulin Lispro in Combination with Insulin Glargine (Gla-100): SORELLLa 1 Study (94-LB)

SK Garg, K Wernicke-Panten, M Rojeski, S Pierre, and K Jedynasty

This poster featured initial phase 3 data demonstrating the non-inferiority of Sanofi’s SAR342434 to Lilly’s Humalog (U100 insulin lispro), in combination with insulin glargine. Developed as a rapid acting follow-on product to Humalog, SAR has an identical amino acid sequence to that of LIS and a previous clamp study determined that SAR was similar in pharmacokinetic exposure and pharmacodynamics activity to LIS. This phase 3 study – entitled SORELLA 1 – randomized 507 type 1 patients to either a multiple daily injection regimen of SAR or LIS in addition to once-daily GLA-100. At 26 weeks, the SAR and LIS groups achieved A1c reductions of 0.42% and 0.47%, respectively, with a LS mean difference of 0.06%. In addition, both groups showed similar post-prandial glucose excursions and insulin dosages. Almost all patients reported at least one episode of hypoglycemia, and a similar percentage of SAR- and LIS-treated patients reported hypoglycemia or severe hypoglycemia difference. In both SAR- and LIS- treated patients, anti-insulin lispro antibody incidence levels were similar (59.1% vs. 59.5% respectively). Each treatment group had one patient who discontinued treatment due to a treatment-emergent adverse event: 42.9% of SAR-treated and 41.7% of LIS-treated reported any adverse event. One death was reported in the SAR group due to a cardiovascular event not considered to associated with either hypoglycemia or the experimental treatment. In addition, both SAR-treated and LIS-treated patients reported similar weight gains of .69 kg and .67 kg, respectively. Thus, the study’s findings concluded that SAR was just as effective and well-tolerated as insulin lispro in people with type 1 diabetes.

Efficacy and Safety of LixiLan vs. Insulin Glargine According to Baseline Characteristics in Patients with Type 2 Diabetes from the Lixilan-L Trial (1018-P)

C Wysham, R Bonadonna, V Aroda, MP Domingo, C Kapitza, W Stager, C Yu, E Niemoeller, E Souhami, and R Bergenstal

This analysis from the LixiLan-L trial demonstrated consistent efficacy and safety with Sanofi’s iGlarLixi (formerly LixiLan; insulin glargine/lixisenatide) across subgroups divided by baseline A1c, diabetes duration, and BMI. Primary results from the trial presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. insulin glargine (Lantus) in patients not at goal on basal insulin. In this analysis, participants were divided into groups based on their baseline A1c (<8% or ≥8%), time since diagnosis of type 2 diabetes (<10 or ≥10 years), and BMI (<30 or ≥30kg/m2). After 30 weeks, the results for A1c reduction, percentage of patients with an A1c <7%, and hypoglycemia were consistent across all subgroups. iGlarLixi consistently led to ~0.5% greater A1c reductions and ~20-30% more patients achieving an A1c <7% compared to insulin glargine, and there were no significant differences in hypoglycemia between treatment groups. iGlarLixi also offered a significant weight benefit vs. insulin glargine in subgroups divided by baseline A1c and BMI (results for duration of diabetes subgroups not given. See the table below for detailed results. 

Subgroup

iGlarLixi

Insulin Glargine

A1c Reduction

Percentage with A1c <7%

Hypoglycemia Incidence

A1c Reduction

Percentage with A1c <7%

Hypoglycemia Incidence

A1c <8%

0.8%

67.5%

32.7%

0.3%

45.4%

42.3%

A1c ≥8%

1.4%

44.5%

46.0%

0.8%

16.8%

42.6%

Duration <10 years

1.1%

56.0%

41.0%

0.6%

35.3%

36.7%

Duration ≥10 years

1.1%

54.3%

39.2%

0.6%

25.7%

46.7%

BMI < 30 kg/m2

1.1%

58.3%

47.7%

0.5%

27.6%

50.0%

BMI ≥30 kg/m2

1.1%

52.4%

34.3%

0.6%

31.1%

36.8%

Efficacy and Safety of MK-1293 Insulin Glargine Compared with Originator Insulin Glargine (Lantus) in Type 2 Diabetes (T2D) (926-P)

P Hollander, G Golm, W Carofano, R Eldor, M Crutchlow, M Marcos, M Rendell, P Home, B Gallwitz, and J Rosenstock

Merck’s Samsung-partnered biosimilar insulin glargine candidate MK-1293 demonstrated similar efficacy and safety to Sanofi’s Lantus in people with type 2 diabetes over 24 weeks. In this phase 3, active-controlled, open-label trial, people with type 2 diabetes (A1c ≤11%) were randomized 1:1 to once-daily MK-1293 (n=265) or Lantus (n=266), guided by a fasting glucose-based dosing algorithm, and with oral agents and prandial insulin continued. At 24 weeks, from a baseline A1c of ~8.3%, the MK-1293 and Lantus groups achieved A1c reductions of 1.28% and 1.30%, respectively, with a difference of 0.03%, meeting the non-inferiority and equivalence criteria. In addition, the two groups had very similar insulin doses: the MK-1293 and Lantus groups had basal doses of 48.3 U/day and 46.9 U/day, respectively. On safety, both groups also had similar anti-insulin antibody (AIA) responses and the study showed no clinically meaningful between-group differences in the reported adverse events including symptomatic hypoglycemia, injection site reaction, systemic allergic reaction, anaphylactic response, and angioedema. As background, Merck recently shared that MK-1293 is filed in Europe, with expectations of data being released this year (data from the phase 3 trial in type 1 diabetes was presented by Dr. Philip Home at this meeting – see above). MK-1293 is one of the first three insulin glargine biosimilars (the other two being from Lilly/BI and Biocon/Mylan) and while we have not explicitly heard plans for a US filing, we would expect one to come soon alongside Europe’s. For more on these latest developments, please read our coverage of Merck’s 1Q16 update.

IDegLira is Efficacious Across Baseline HbA1c Categories in Subjects With Type 2 Diabetes Uncontrolled on SU, GLP-1RA or Insulin Glargine: Analyses From Completed Phase 3b Trials (925-P)

C Sorli, S Harris, E Jódar, I Lingvay, K Chandarana, J Langer, and E Jaeckel

Novo Nordisk presented a post hoc analysis of the phase 3b DUAL trials for GLP-1 agonist/basal insulin combination IDegLira (Xultophy; insulin degludec/liraglutide), showing that the drug’s efficacy was consistent regardless of baseline A1c. The analysis included populations uncontrolled on a GLP-1 agonist (DUAL III; IDegLira vs. continued GLP-1 agonist therapy), a sulfonylurea (DUAL IV; IDegLira vs. placebo) and insulin glargine (DUAL V; IDegLira vs. continued insulin glargine therapy). Patients in each trial were split into three different baseline A1c categories: ≤7.5%, >7.5-≤8.5% and >8.5%. In all categories, IDegLira led to significantly greater A1c reductions than the comparator therapy; as expected, the greatest reductions occurred in the highest baseline A1c category. See the table below for detailed results. Perhaps most impressively, IDegLira led to a mean final A1c <7% in all categories, underscoring its status as one of the most efficacious and versatile type 2 diabetes drugs available.

Table: A1c Reductions Across Baseline A1c Categories in the DUAL Trials

 

Overall

Baseline A1c ≤7.5%

Baseline A1c >7.5%-≤8.5%

Baseline A1c ≥8.5%

DUAL III

IDegLira (n=292): -1.3%

IDegLira (n=113): -1.0%

IDegLira (n=141): -1.4%

IDegLira (n=38): -1.9%

 

GLP-1 (n=146): -0.3%

GLP-1 (n=66): -0.3%

GLP-1 (n=66): -0.3%

GLP-1 (n=14): -1.0%

DUAL IV

IDegLira (n=289): -1.5%

IDegLira (n=93): -1.0%

IDegLira (n=156): -1.5%

IDegLira (n=40): -2.1%

 

Placebo (n=146): -0.5%

Placebo (n=48): -0.2%

Placebo (n=80): -0.6%

Placebo (n=18): -0.7%

DUAL V

IDegLira (n=278): -1.8%

IDegLira (n=63): -1.0%

IDegLira (n=102): -1.6%

IDegLira (n=113): -2.5%

 

IGlar (n=279): -1.1%

IGlar (n=64): -0.5%

IGlar (n=118): -1.0%

IGlar (n=97): -1.7%

P=0.004 for DUAL III baseline A1c ≥8.5%; p<0.001 for all other categories

Impact of Baseline HbA1c, BMI, and Diabetes Duration on the Efficacy and Safety of LixiLan (Insulin Glargine/Lixisenatide Titratable Fixed-Ratio Combination) vs. Insulin Glargine and Lixisenatide in the LixiLan-O Trial (1028-P)

M Davies, L Leiter, G Grunberger, FJ Ampudia-Basco, B Guerci, C Yu, W Stager, E Niemoeller, E Souhami, and J Rosenstock

This analysis of the LixiLan-O trial demonstrated consistent efficacy and safety with Sanofi’s iGlarLixi (formerly LixiLan; lixisenatide/insulin glargine) across subgroups divided by baseline A1c, diabetes duration, and BMI. Primary results presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. either component alone in patients with type 2 diabetes not at goal on oral medications. In this analysis, participants were separated into groups by baseline A1c (<8% or ≥8%), duration of type 2 diabetes (<7 or ≥7 years) and BMI (<30 or ≥30 kg/m2). After 30 weeks, the results for A1c reductions, the percentage of patients with an A1c <7%, and hypoglycemia were consistent across all subgroups. iGlarLixi consistently led to significantly greater A1c reductions (~0.3% vs. insulin glargine and 0.7%-0.9% vs. lixisenatide) and more patients achieving an A1c <7% compared to both components; hypoglycemia was comparable between the iGlarLixi and insulin glargine groups. See the table below for detailed results.

Subgroup

iGlarLixi

Insulin Glargine

Lixisenatide

 

A1c Reduction

A1c <7%

Hypoglycemia

A1c Reduction

A1c <7%

Hypoglycemia

A1c Reduction

A1c <7%

Hypoglycemia

A1c <8%

1.2%

83.8%

23.0%

0.8%

67.7%

22.4%

0.5%

50.5%

5.5%

A1c ≥8%

1.9%

69.8%

27.9%

1.6%

53.9%

24.6%

1.1%

19.4%

7.3%

Duration <7 years

1.5%

75.2%

21.3%

1.2%

61.9%

19.0%

0.8%

37.5%

7.3%

Duration ≥7 years

1.6%

72.6%

28.8%

1.3%

57.4%

27.2%

0.7%

29.9%

5.8%

BMI <30 kg/m2

1.6%

78.6%

31.6%

1.2%

57.9%

29.1%

0.7%

28.4%

12.0%

BMI ≥30 kg/m2

1.5%

75.2%

22.0%

1.3%

62.2%

20.1%

0.8%

36.5%

3.8%

Consistent Outcomes Across Dose Ranges With Titratable LixiLan, Insulin Glargine/Lixisenatide Fixed-Ratio Combination, in the LixiLan-O Trial (1017-P)

R Henry, B Ahrén, M Davies, Y Wu, Y Handelsman, E Souhami, E Niemoeller, and J Rosenstock

Sanofi presented data from the LixiLan-O trial showing that iGlarLixi (formerly LixiLan; lixisenatide/insulin glargine) was consistently safe and effective and produced minimal weight gain across all dose ranges. Primary results from the trial presented as an oral presentation demonstrated superior glycemic control with iGlarLixi vs. either component alone in patients with type 2 diabetes not at goal on oral medications. During the trial, the dose of insulin glargine (Lantus) was titrated weekly in both the iGlarLixi and insulin glargine groups to a fasting plasma glucose target of 80-100 mg/dl, with a cap of 60 U/day (the maximum dose available in the combination). In the iGlarLixi group, two different pens with different insulin glargine/lixisenatide fixed ratios were used depending on the required dose of insulin glargine. Patients requiring 10-40 U/day of insulin glargine were treated with the lower-dose pen (ratio of 2 U insulin glargine/1µg lixisenatide), while those requiring insulin glargine doses of 30-60 U/day were treated with the higher-dose pen (ratio of 3 U insulin glargine/1 µg lixisenatide). In this analysis, patients in the iGlarLixi group were divided into subgroups based on their final doses of insulin glargine (≤10-<20 U, ≥20-30 U, ≥30-≤40 U, and >40-≤60) and lixisenatide (≥5-<10 µg, ≥10-<15 µg, and ≥15-≤20 µg). A1c reductions, the percentage of patients achieving an A1c <7%, and the incidence of hypoglycemia in the iGlarLixi group were consistent across all dose categories, and the weight gain seen with insulin glargine alone was mitigated with all doses of iGlarLixi. The incidence of nausea/vomiting was low, which the authors attributed to the gradual titration of lixisenatide.

Symposium: The New Face of Injectable Options

Benefits and Limitations of Concentrated Insulin

Wendy Lane, MD (Mountain Diabetes and Endocrine Center, Asheville, NC)

Concentrated insulin guru Dr. Wendy Lane took to the podium to discuss the newly expanded range of concentrated insulins available to clinicians and patients. We appreciated the nuance in how Dr. Lane described the strengths and weaknesses of new concentrated basal analogs Toujeo (insulin glargine U300) and Tresiba (insulin degludec) U200, relative to the reigning heavyweight Humulin U500, Lilly’s concentrated human insulin formulation. Dr. Lane seemed to favor slightly more things about Tresiba U200, namely that: (i) its pen holds more units than the Toujeo pen (also meaning fewer copays); (ii) its duration of action is the “longest of any basal insulin;” (iii) bioequivalence with Tresiba U100 means no need for dose titration with the switch to U200, whereas you need to up-titrate in the switch from insulin glargine U100 (Lantus) to U300 (Toujeo). Despite the differences, she was positive on both new insulins when used appropriately. Later at a corporate symposium on concentrated insulins, Dr. Lane shared that she is using Humulin U500 less often following the introduction of Toujeo and Tresiba U200. For more on this topic, see our coverage of her discussion on this topic at this past year’s ENDO.

  • Dr. Lane is optimistic about the potential for concentrated rapid-acting analogs like Humalog (insulin lispro) U200 in pumps. Even Humulin U500 – an imperfect insulin for use in a pump – has demonstrated efficacy in pumps in patients with very high daily insulin needs. Dr. Lane pragmatically pointed out that part of the advantage of a more concentrated rapid-acting insulin would be fewer cartridge replacements and fewer copays.
  • For those not familiar with the world of concentrated insulin formulations, the benefits are real, and include: (i) improved absorption from smaller-volume insulin depots, leading to more predictable insulin action; (ii) fewer injections and/or lower volume per injection to enhance patient comfort, potentially with a positive effect on compliance; and (iii) in some cases (such as insulin glargine), concentrating insulin can prolong its action profile.

Questions and Answers:

Q: In my view, Humulin U500 is not a bolus insulin anymore, and it’s too slow to put in a pump. The advantage of concentrated insulin is to flatten the PK profile for longer duration.

A: What you’re saying makes sense if you’re looking at the PK profile, but if you put it into a pump, you change its behavior somewhat. I’ve found that it works well in high dose users – it has a good postprandial effect. The problem is that patients need to bolus ahead of meals. Right now, it’s being studied in a clinical trial as MDI monotherapy, because it has both basal and prandial characteristics. In our clinical experience in several hundred patients, if you put U500 into a pump in a high dose insulin user, you get good results.

Q: There is a big risk of dosing errors for insulin in inpatient settings. Should we be saying no to concentrated insulins in-house for safety reasons?

A: For safety reasons, it’s probably best to use a U100 insulin for inpatient use.

Q: Is there strong evidence that concentrated insulins have better absorption?

A: There is not strong evidence – it’s clinical evidence, and to some degree, speculation. When you inject a high dose of U100 insulin, especially glargine, you’re going to see a point of titration that doesn’t give you a better effect. It’s either a decrease in absorption, or some sort of decreased activity either due to high volume or insulin-ase causing some sort of degradation. There is at least one paper published indicating that when you start to titrate above 0.5 U/kg, you start to lose benefit.

Swallowing Your Biologics and Not Your Pride

Chandra Sharma, PhD (Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India)

Dr. Chandra Sharma discussed the theoretical advantages of oral insulin (better compliance, more physiological delivery of insulin to the liver) before discussing his own research group’s work on oral insulin technology. His group’s investigational platform involves a pH-sensitive polymer of layered nanoparticles that can be absorbed across the intestinal mucosa. According to his group’s preclinical studies, 93% of the particles are less than 100nm in size, and a 30-45 U/kg dose in a diabetic rat model yielded maximum glucose level reductions of 50%-70% with bioavailability of 22%-24%. We don’t have much to compare this to as we haven’t seen much equivalent data on other investigational oral insulin delivery systems (much of which, presumably, is proprietary), but it’s exciting to see all the progress being made on the challenging task of oral peptide delivery.

Smart Insulins and Nanotechnology for Diabetes Management – Reality or Myth?

Daniel Anderson, PhD (MIT, Cambridge, MA)

Dr. Daniel Anderson’s fascinating talk covered a range of topics at the forefront of smart insulin. He opened by discussing three approaches to modifying the insulin structure and imparting glucose-responsive behavior: binding of insulin to endogenous targets such as albumin and lectin (which would then be displaced by glucose, freeing the insulin molecule), changing the solubility or aggregation of insulin in a glucose-dependent way, and developing an insulin that relies on glucose to bind to its receptor. Dr. Anderson then highlighted the potential to package insulin molecules into “smart” microspheres. He shared that his lab has constructed a microgel that swells and enlarges its pores in response to glucose, thereby providing a potential glucose-dependent mechanism of insulin release. Notably, Dr. Anderson also considered the possibility of using nanoparticles to alter gene expression and cure rare genetic forms of diabetes. In concluding his presentation, Dr. Anderson turned to a different topic of interest – using new biomaterials to make capsules that can promote and protect transplanted islet cells in their new human host.

  • Dr. Anderson covered three types of covalent modifications to the insulin structure that could impart glucose-responsive behavior. First, experiments dating back to 1979 have investigated the use of insulin bound to endogenous targets such as lectin and albumin. Glucose can disrupt such binding, leading to release of free insulin. The technology led to the foundation of the company SmartCells, which was acquired by Merck in 2010. Dr. Anderson expressed excitement as he remarked that several clinical trials on this technology are currently ongoing – see our Merck 1Q16 report for the latest on the company’s smart insulin candidate MK-2460. Secondly, Dr. Anderson’s lab has focused on conjugating insulin to phenylboronic acid (PBA), a compound that can reversibly bind glucose. Binding of glucose to the PBA-insulin complex can alter the charge on insulin, thus influencing its availability. Dr. Anderson’s team has already developed several forms of a PBA-detemir complex, which has performed better than both native insulin and detemir in mouse studies. Lastly, Dr. Anderson commented that glucose-dependent binding of insulin to its receptor is a third promising mechanism for smart insulin.
  • Dr. Anderson then discussed the potential to package insulin molecules into smart microspheres that respond to glucose – either by breaking down or by swelling up and enlarging their pores. Dr. Anderson highlighted the need for rational design of biomaterials, noting that the sugar polymers found in biodegradable sutures have also been used to make the microcapsules that work in exenatide. A next would be to use such capsules not just for sustained release (as in the case of exenatide), but for glucose-responsive release. Dr. Anderson cited an example from his lab, which has used glucose oxidase to construct microgels that swell in response to glucose, and that are biodegradable.
  • Dr. Anderson remarked that despite current advances in technology, significant challenges lie ahead in order to make a smart insulin that meets the requirements – i.e., rapid on/off, no dose dumping, biocompatibility, antigenicity, and clearance of the encapsulating materials.
  • Dr. Anderson posited whether nanoparticles could be used to correct genetic elements, and thus potentially cure the very rare forms of diabetes that are based on single gene mutations. He noted that nanoparticles have already been used to deliver siRNA into cells (to inhibit gene expression in certain types of liver disease) and to bring mRNA into cells (to promote specific protein production).
  • In concluding his talk, Dr. Anderson turned to islet transplantation, noting that new materials can be used to make the capsules that hold transplanted islet cells in the host body. These capsules must allow for the delivery of nutrients and oxygen to the islet cells, permit transport of insulin out of the capsule, and avoid the host immune system. His lab has used analogs of alginate (a compound derived for seaweed) to create such capsules, which so far have been shown to keep islet cells alive for up to four months.

Questions and Answers

Q: This is fascinating. I have a basic question – is there shared technology between the production of nanoparticles and biosimilar drugs?

A: No; each is customizable for its application.

Q: One of your former post-docs has received a JDRF award looking at smart patches. Can you share some information about those?

A: The vision is that patients could have a painless patch. The microneedles in the patch would provide delivery, but would not hurt because they aren’t deep enough. And you can have a patch that provides not only delivery, but smart delivery.

Inhaled Insulin – Where are we Going From Here?

Stefano Del Prato, MD (University of Pisa, Pisa, Italy)

Dr. Stefano Del Prato offered a fairly negative take on inhaled insulin, arguing that clinical trials have not demonstrated clear advantages in terms of clinical outcomes or patient convenience and that more long-term data is needed to fully understand pulmonary safety. He noted that MannKind’s inhaled insulin Afrezza has demonstrated non-inferiority at best compared to injected insulin in terms of A1c reductions. He acknowledged the potential advantages on postprandial control but noted that there have not been any studies comparing inhaled insulin to other solutions like GLP-1 agonists that could provide the same benefit. For Dr. Del Prato, the biggest clinical advantage of inhaled insulin is that it may facilitate the initiation of insulin therapy among patients who would otherwise be reluctant based on data from the EXPERIENCE trial of Pfizer’s Exubera. Dr. Del Prato was fairly skeptical about the promised convenience advantages of inhaled insulin, noting that clinical trials of Afrezza did not show a significant benefit on patient-reported outcomes. In terms of safety, Dr. Del Prato believes that questions still remain about inhaled insulin’s effects on the lungs and that long-term studies are needed to evaluate the risk of lung cancer and declining pulmonary function. Dr. Del Prato received some pushback during Q&A from clinicians who have had positive experiences with Afrezza (see more below); he responded that he believes the subject is still open for discussion but that the field must rely on hard evidence from clinical trials rather than anecdotal reports.

  • During Q&A, Dr. Nancy Bohannon (California Pacific Medical Center, San Francisco, CA) stated that it has taken her a year of experience to determine how to optimize inhaled insulin therapy for each of her patients. She spoke very positively about her overall experience with Afrezza but suggested that individualization of therapy requires a lot of trial and error. For example, many of her patients needed to take an extra dose of Afrezza a few hours after the first dose, and some needed to increase their basal insulin dose because they had been unknowingly relying on injected rapid-acting insulin for part of their basal coverage. If other clinicians have had similar experiences, that could help explain why Afrezza has struggled with new patient retention while still receiving very positive reviews from a subset of patients.     

Questions and Answers

Q: You said it’s not clinically advantageous, but I’ve had a number of patients who really like using this.

A: I’m not saying it can’t be used. I’m saying if you look at the data and define an advantage as an improvement in the clinical outcome of A1c, so far the data don’t suggest any specific advantage. If it can facilitate the use of insulin, that is welcome.

Q: Maybe we need a study to capture patient-reported outcomes in a better way.

A: Yes, we need to identify people gaining from this treatment.

Dr. Nancy Bohannon (California Pacific Medical Center, San Francisco, CA): A1c is only a poor reflection of control. I’ve had a really good experience with the current inhaled insulin. I believe the clinical trials were not done optimally because they didn’t know how to use it optimally. It took me a year of experience to figure out how to use it in each patient. Some need to increase the dose to the nearest next four units; others require four times as much. Many required an extra little dose at 90 minutes or three hours after the last dose. Some required an increase in basal insulin. For a standard injection of fast-acting insulin, let’s say the duration of insulin action is four to six hours. If this is gone in two hours, there’s a three-hour period there where fast-acting insulin was acting as basal insulin. On an individual basis you can often achieve much better control. In a study using the same method and the same way of administering it for every patient, we’re not seeing an improvement in A1c.

A: My point is that this is sensation and experience, not controlled trials. We need to design trials to respond to your question; otherwise we can’t conclude anything. I totally agree that we have to be smarter and come up with better ways to appreciate the potential of this treatment. I’m open to discussion but we don’t have the results.

Symposium: Inpatient Management of Diabetes and Hyperglycemia – Novel Insights and Effective Approaches

Effective Transition from IV to SQ Insulin Therapy – Best Practices and Tricks of the Trade

David Baldwin, MD (Rush University Medical Center, Chicago, IL)

Dr. Baldwin discussed the many subtle yet key considerations a physician needs to make when deciding how and when to transition a patient from intravenous (IV) to subcutaneous (SQ) insulin therapy. Readiness is determined by whether the patient is hemodynamically stable, whether they are dependent on vasopressors or epinephrine, and whether the current IV insulin requirement can realistically be mimicked with SQ insulin dosing. Particular attention also needs to be paid to whether the patient is eating regularly. Dr. Baldwin also highlighted the importance of judging transition success over the following 2-4 days rather than simply the first 24 hours, noting that many adjustments in basal/bolus doses over that time period are to be anticipated.

Corporate Symposium: A Case-based Approach to Understanding a Once-Daily Basal Insulin Option for Your Patients (Sponsored by Novo Nordisk)

Summary

Davida Kruger, MSN (Henry Ford Health System, Detroit, MI), Anne Peters, MD (USC, Los Angeles, CA), Christopher Sorli, MD, PhD (Billings Clinic, MT), Todd Hobbs, MD (North America CMO, Novo Nordisk, Plainsboro, NJ)

This star-studded, Novo Nordisk-sponsored corporate symposium featured an in-depth look at the company’s next-generation basal insulin Tresiba (insulin degludec), which was recently launched in the US. Ms Davida Kruger (Henry Ford Health System, Detroit, MI) and Drs. Anne Peters (USC, Los Angeles, CA) and Christopher Sorli (Billings Clinic, MT) spoke very highly of Tresiba’s long profile of action and, in particular, the opportunity for flexible dosing in the case of missed injections. Ms. Kruger pointed out that with other basal insulins, there is no recourse for a missed dose other than waiting until the next scheduled dose time, which often means the patient’s fasting glucose will be poorly controlled for the whole day. On the other hand, patients who miss a dose of Tresiba can inject it as soon as they remember as long as it’s at least eight hours before the next scheduled dose. Dr. Peters pointed out that the flexible dosing feature could be especially helpful for shift workers and other patients with unpredictable schedules. Dr. Peters also noted that, due to the enhanced stability of the steady state of Tresiba, her patients don’t have to adjust the dose day-to-day as some do for other basal insulins. Though Tresiba’s only been available on the US market for a few months, its clear that the product is already winning over many healthcare providers and educators with the clinical advantages offered by the product.

Product Theaters

A Treatment Option for Patients who are Severely Insulin Resistant (Sponsored by Sanofi)

Timothy Gilbert, MD (Texas Diabetes & Endocrinology, Dallas, TX) and Jeremy Pettus, MD (University of California San Diego, San Diego, CA)

Dr. Pettus asked the audience to think of Toujeo (U300 insulin glargine) as a completely new basal insulin, as it has a PK profile distinct from that of Lantus (U100 insulin glargine). He reviewed the basic characteristics of the drug, including its lower injection volume (one-third that of Lantus), the fact that it forms a smaller precipitate than Lantus, and the convenience offered by the one-to-one unit conversion between the Lantus and Toujeo pens. Both Dr. Pettus and Dr. Gilbert highlighted that Toujeo is more stable than Lantus over 24 hours. In reviewing the six-month non-inferiority phase 3 EDITION studies that compared Toujeo to Lantus, both physicians focused on EDITION 3, which recruited insulin-naïve type 2 diabetes patients uncontrolled on oral agents. They highlighted that both drugs had similar A1c reductions, and that Toujeo had improved rates of hypoglycemia. During the second half of the talk, the two physicians reviewed a patient example, walking the audience through the considerations of starting basal insulin.

  • For insulin-naïve patients, Dr. Gilbert recommended starting with a Toujeo dose of 0.2U/kg/day for type 2 patients and with one-third to one-half of the total daily insulin dose for type 1 patients. For patients on once-daily long or intermediate acting insulin, he recommended a 1:1 conversion. Lastly for those on twice-daily NPH insulin, he recommended starting with 80% of the total daily NPH dose. Dr. Pettus suggested increasing the Toujeo dose every three to four days based on the patient’s personalized fasting plasma glucose target.
  • In reviewing the EDITION 3 data, Dr. Pettus highlighted that both Lantus and Toujeo had similar A1c reductions, and that the rates of severe hypoglycemia and documented symptomatic hypoglycemia with Toujeo were 0.9% and 8%, respectively. Dr. Pettus acknowledged that the data for Lantus were not shown, and stated that studies have indicated a trend toward less hypoglycemia with Toujeo. That said, hypoglycemia with Toujeo has not been studied in a dedicated trial as it has with Novo Nordisk’s Tresiba (insulin degludec) in the SWITCH 1 and SWITCH 2 trials. We’ll be curious to see if Sanofi initiates a similar trial of hypoglycemia in Toujeo as it vies with Tresiba within the next-generation basal insulin market.

Options in Basal Insulin: Basaglar (Sponsored by Lilly/BI)

Tom Blevins, MD (Texas Diabetes & Endocrinology, Austin, TX)

In this Lilly/BI Saturday afternoon product theater, Dr. Tom Blevins reviewed Basaglar’s (biosimilar insulin glargine) phase 3 efficacy and safety data, highlighting its non-inferiority vs. Sanofi’s Lantus. Throughout the presentation, Dr. Blevins emphasized that while Basaglar is identical to Lantus in terms of amino acid sequence and dosing information, the FDA does not technically consider it a biosimilar – it was approved under the 505(b)(2) regulatory pathway, which will be consolidated with the newer “official” biosimilar pathway in 2020.  Dr. Blevins also commented on the delivery device – Basaglar will be delivered in a uniquely-colored KwikPen that is compatible with BD’s ultrafine needles. This is different than the delivery device for Lantus and could potentially make Basaglar more appealing for patients averse to needles. While Dr. Blevins did not comment on pricing during the presentation, he suggested during Q&A that the cost would “probably be more or less the same compared to Lantus.” We would be surprised and disappointed if this is the case given the widespread hope that biosimilar insulins can help counteract the trend toward skyrocketing insulin prices. So far, the product has been priced at about a 10%-20% discount compared to Lantus in the EU countries where it has launched. We have assumed that the discounts could be even steeper in the US given the higher list prices for basal insulin analogs there compared to Europe, though the discounts are still expected to fall well short of those for small-molecule generics. Dr. Blevins confirmed that Basaglar is expected to launch in the US launch around December 15, 2016 as per the terms of Lilly’s patent lawsuit settlement with Sanofi. During the presentation, Dr. Blevins also reviewed results from the phase 3 ELEMENT I and ELEMENT II trials (presented at ADA 2014) demonstrating non-inferiority between Basaglar and Lantus in terms of  A1c reduction and percentage of patients achieving an A1c <7% in type 1 and type 2 diabetes.

Questions and Answers

Q: Are there any differences in cost between Basaglar and Lantus?

A: The cost will probably be more or less the same. I’m not sure, as that information isn’t available yet. I would suggest continuing to communicate directly with BI and Lilly to find out exact information on pricing.

Q: Can you speak to the interchangeability in treatment with Basaglar and Lantus?

A: Basaglar did meet the criteria for non-inferiority vs. Lantus. However, I don’t believe that these two are officially interchangeable – that is not worked out. Basaglar is another option, that’s my best answer. However, there is no difference in achievement; Basaglar is non-inferior to Lantus.

A: Because Basaglar is regulated through an NDA, and interchangeability is a regulatory status, this follow-on is not deemed interchangeable in the US. We know that for sure.

Q: What does the experience of someone who is pregnant and on Basaglar look like?

A: We haven’t studied Basaglar in pregnancy.

Toujeo: A Once-daily Basal Insulin (Sponsored by Sanofi)

Bruce Bode, MD (Atlanta Diabetes Associates, Atlanta, GA), Bill Polonsky, PhD (University of California San Diego, San Diego, CA) Steven Edelman, MD (TCOYD, Del Mar, CA), Debbie Hinnen, APRN, CDE (Touro University California, Vallejo, CA)

At a relatively well-attended Sanofi product theater, Drs. Bruce Bode, Steve Edelman, Bill Polonsky, and Debbie Hinnen made a strong case for why providers should prescribe Toujeo (insulin glargine U300) in type 2 diabetes. The speakers began by taking turns presenting on Toujeo’s pharmacology, clinical data, and administration before walking through different case studies to demonstrate how to dose for a wide range of patients, from those who are insulin-naïve to those on basal-bolus therapy. Notably, the formulation was described as a particularly “forgiving” insulin, both in terms of its smooth basal rate (which allows patients to get away with errors – Dr. Bode actually noted that the flat profile is just like “what you see with an insulin pump”) and flexible dosing (which allows patients to get away with missing a morning dose). We got the sense that Toujeo fits better into patients’ lives – rather than patients having to fit their lives around the insulin – which led Dr. Edelman, in particular, to highlight the potential adherence benefits. He also acknowledged the company’s “very good” COACH program, stressing that more patient contact and support leads to better outcomes. Lastly, panelists spent time discussing the clinical transition from Lantus (insulin glargine) to Toujeo, stressing that it takes 3-4 days for the latter to achieve steady state – indeed, all the speakers had stories of patients who claimed Toujeo “didn’t work” because they did not stick with it long enough, and with that in mind, stressed that setting expectations is key.

DPP-4 Inhibitors

Posters

Sitagliptin and Risk of Fractures in Type 2 Diabetes: Results from the TECOS Trial (587-P)

R Josse, S Majumdar, J Buse, J Green, K Kaufman, C Westerhout, Y Zheng, E Peterson, R Holman, P Armstrong, and TECOS Study Group

This analysis of data from the TECOS CVOT demonstrated no increased risk of fractures with sitagliptin (Merck’s Januvia). Primary results from the trial presented at ADA 2015 demonstrated a neutral effect on cardiovascular outcomes with sitagliptin vs. placebo, including no signal of increased heart failure risk. This analysis found that during 43,222 person-years of follow-up, 375 patients (2.6%; 8.7 per 1,000 person-years) experienced a fracture. Of these, 146 were major osteoporotic fractures (hip [n=31], upper extremity [n=81], clinical spine [n=31]). There were 189 incident fractures in the sitagliptin group (8.7 per 1,000 person-years) compared to 186 incident fractures in the placebo treatment group (8.6 per 1,000 person-years). There was no significant difference between the groups in total incident fractures (hazard ratio [HR] 1.01, 95% CI 0.82-1.23, p=0.944), major osteoporotic fractures (p=0.779), or hip fractures (p=0.747). An adjusted analysis indicated that fracture risk increased independently with older age (p<0.001), female sex (p<0.001), white race (p<0.001), lower diastolic blood pressure (p<0.001), and diabetic neuropathy (p=0.003). It also found that insulin therapy was associated with increased fracture risk (HR 1.40, 95% CI 1.02-1.91, p=0.035) and metformin was associated with decreased risk (HR 0.76, 95% CI 0-.59-0.98, p=0.035). Fracture risk is an important consideration with type 2 diabetes drugs given the increased risk associated with type 2 diabetes itself and the potential for additional increased risk with drug classes such as TZDs; this analysis therefore provides welcome reassurance that sitagliptin does not carry undue risk.

Hypoglycemia Is Associated with Increased Risk of Cardiovascular Events: Results from the EXAMINE Trial (1091-P)

W White, R Bergenstal, C Cannon, S Kupfer, C Wilson, and S Heller

This analysis aimed to evaluate potential links between hypoglycemia and adverse cardiovascular outcomes in the EXAMINE study (CVOT for Takeda’s Nesina [alogliptin]). Of the 5,380 patients enrolled in the study, 354 (6.6%) reported experiencing hypoglycemia; rates of severe hypoglycemia were low in both groups (0.7% with alogliptin and 0.6% with placebo). Using a Cox proportional hazards model adjusted for age, sex, A1c, and study treatment, the researchers found that patients with reported severe hypoglycemia had a significantly higher risk of major adverse cardiovascular events (MACE) vs. those without (35.5% vs. 11.4%;hazard ratio [HR] = 2.42; p =0.007). Patients with any reported hypoglycemia also experienced a significant increase in MACE vs. those without hypoglycemia, though the difference was not as dramatic (18.1% vs. 11.1%; HR = 1.38; p=0.019). However, when the analysis was limited to MACE occurring after a hypoglycemic episode, the association was less strong and not statistically significant. The authors suggested that this may indicate the presence of a confounding variable. The authors also noted that classification of hypoglycemia in EXAMINE was determined by the discretion of local investigators and was not standardized. Greater standardization of the definition and measurement of hypoglycemia across clinical trials is essential and would go a long way toward enabling more robust analyses and would perhaps facilitate an easier regulatory path for hypoglycemia label claims.

Renal Outcomes Associated with Alogliptin vs. Placebo in Patients with Type 2 Diabetes Mellitus and Recent Acute Coronary Syndrome: Results from the EXAMINE Trial (1203-P)

M Vaduganathan, W White, D Chartyan, C Wilson, S Kupfer, L Lei, Y Liu, F Zannad, C Cannon, and G Bakris

This analysis examined renal outcomes and chronic kidney disease (CKD) progression with Takeda’s Nesina (alogliptin) vs. placebo in the EXAMINE trial. Primary results presented at ESC 2013 demonstrated a neutral impact of alogliptin on cardiovascular outcomes. This analysis looked at reported renal adverse events and renal function evaluation in follow-up; mean follow-up was 18 months. Renal outcomes were similar between the two groups: 22.5% of patients in the alogliptin group were reported to have renal adverse advents vs. 21.85% in the placebo group (p=0.53). Very few patients in each group initiated dialysis: 0.9% in the alogliptin group and 0.8% in the placebo group (p=0.79). Participants with mild to severe baseline renal impairment (eGFR<90 ml/min/1.73 m2) experienced a slight increase in eGFR in both groups, and those with normal baseline renal function (eGFR≥90 ml/min/1.73 m2) experienced a decline in both groups. The authors concluded that alogliptin appears comparable to placebo in terms of CKD progression over 18 months but called for more research on the longer-term effects.

Mortality Findings from the EXAMINE Trial (1090-P)

WB White, S Kupfer, CP Cannon, CR Mehta, SR Heller, C Wilson, GL Bakris, WC Cushman, SE Nissen, RM Bergenstal, P Fleck, and F Zannad

This study compared fatal outcomes between participants in the EXAMINE trial who previously experienced a major non-fatal cardiovascular event and those who did not. CV events included myocardial infarction (MI), stroke, hospitalized heart failure (hHF), and unstable angina (UA). The CV death rates in EXAMINE were 4.1% for those given the DPP-4 inhibitor alogliptin and 4.9% for those given placebo. Overall, the mortality rates were comparable for the alogliptin and placebo groups, but the majority of CV deaths in the EXAMINE trial occurred in those who had not suffered a major non-fatal event beforehand; however, those who had suffered such an event did see an elevated risk of CV mortality. The researchers found that patients who experienced a major non-fatal CV event had an adjusted hazard ratio for death compared with those who had not suffered an event as follows: 3.12 after MI, 3.08 after stroke, 4.96 after hHF, and 1.66 after UA. These findings ultimately help guide ongoing opportunities to reduce mortality in the large patient population of those with both type 2 diabetes and CV diseases.

  • According to the results, those who did not experience a non-fatal major CV event had a shorter diabetes duration compared to those who did experience such an event. Specifically, those who did not experience an event had an average disease duration of 6.8 years compared to 10.2 years, 9.9 years, 8.9 years, and 9.3 years for those who experienced an MI, hHF, stroke, and UA, respectively. Other differences in baseline characteristics between groups included age, BMI, likelihood of having coronary revascularization, rates of peripheral artery disease, and eGFR.
  • The EXAMINE trial had 2,701 patients in the alogliptin arm and 2,679 in the placebo group, with 153 any-cause deaths and 112 CV deaths in the former arm and 173 any-cause and 130 CV deaths in the latter. The most prevalent cause of death was sudden cardiac death, seen in 59 alogliptin and 73 placebo patients.
  • First non-fatal CV events during the median follow-up of 18.8 months included MI in 316 patients, hHF in 159, stroke in 57, and UA in 204. The remaining 4,644 patients experienced no such event, of whom 233 died, included 172 of CV causes.

Hypoglycemia Is Associated with Increased Risk of Cardiovascular Events: Results from the EXAMINE Trial (1091-P)

WB White, RM Bergenstal, CP Cannon, S Kupfer, C Wilson, and SR Heller

This poster evaluated the consequence of reported hypoglycemia on the risk for subsequent major adverse CV events from the EXAMINE trial of alogliptin, with findings suggesting an association between hypoglycemia and cardiac arrests in patients with type 2 diabetes and high cardiovascular risk. Building on previous research on this topic, this study found significantly higher incidence of major acute cardiovascular events (MACE) among those who had a serious hypoglycemic episode (12 incidences of MACE out of 34 such patients, or 35.3%) vs. those who did not (609 out of 5,346, or 11.4%), for an adjusted hazard ratio (HR) of 2.42. The researchers similarly found an association in patients who had experienced any hypoglycemia (64 out of 354, or 18.1%) vs. those who had not (557 out of 5,026, or 11.1%), for an HR of 1.38. The researchers concluded that this more robust relationship between MACE and hypoglycemia suggests at least some role for a confounding variable – for example, that hypoglycemia may be associated with other underlying comorbidities that increase the likelihood of MACE.

  • Previous research such as the 2008 ACCORD trial has suggested that hypoglycemia may contribute to cardiac event for a variety of reasons. These include an increased risk of cardiac arrhythmia during spontaneous hypoglycemia, particularly at night; an observed link between hypoglycemia and low A1c levels with an increased risk of death in patients with diabetes who are hospitalized for myocardial infarction; and the fact that experimental hypoglycemia could increase CV risk by impairing endothelial function, prolonging low-grade inflammation, and causing sympatho-adrenal activation.

Renal Outcomes Associated with Alogliptin vs. Placebo in Patients with Type 2 Diabetes Mellitus and Recent Acute Coronary Syndrome: Results from the EXAMINE Trial (1203-P)

M Vaduganathan, WB White, DM Charytan, C Wilson, S Kupfer, L Lei, Y Liu, F Zannad, CP Cannon, and GL Bakris

This poster evaluated the effects of the DPP-4 inhibitor alogliptin on chronic kidney disease (CKD) progression in the EXAMINE trial. The study’s authors noted that patients with type 2 diabetes are at higher risk of developing CKD and found that the effect of alogliptin was comparable to that of placebo in the EXAMINE trial, though they highlighted that longer-term evaluation of DPP-4 inhibitors’ renal effect is needed. CKD endpoints, including creatinine doubling and dialysis initiation, were assessed in patients with type 2 diabetes and recent acute coronary syndrome randomized to either alogliptin (n=2,701) or placebo (n=2,679), with a median follow-up of 18 months. The findings showed that 21.8% in the placebo arm and 22.5% in the alogliptin arm experienced a composite renal on-study adverse events, including albuminuria (1.5% vs. 1.1%), microalbuminuria (0.8% vs. 1.2%), and acute renal failure (3.3% vs. 3.6%). Thus, there were no significant differences in rates of CKD progression, albuminuria change, dialysis initiation, or other renal laboratory parameters. While no big safety signals were indicated, the study’s authors continued to emphasize the importance of developing therapies to prevent or slow diabetic nephropathy, as this remains a significant unmet clinical need.

Once-Weekly Treatment with Omarigliptin, a DPP-4 Inhibitor, Improves Glycemic Control in Patients Not At Goal on Metformin (1120-P)

R Shankar, S Inzucchi, I Gantz, V Scarabello, P Ceesay, S Suryawanshi, and E Lai

This randomized trial examined the effects of Merck’s once-weekly DPP-4 inhibitor omarigliptin vs. placebo in 402 patients with type 2 diabetes with inadequate glycemic control on metformin.  After 24 weeks, omarigliptin led to significantly greater reductions in A1c (0.54% vs. 0%; baseline = 8-8.1%; p<0.001), two-hour postprandial glucose (26.8 mg/dl vs. 12.2 mg/dl; baseline = 236-240 mg/dl; p=0.011), and fasting plasma glucose (10.7 mg/dl vs. 1.2 mg/dl; baseline = 169 mg/dl; p=0.010) compared to placebo. In addition, a significantly greater percentage of the omarigliptin group achieved an A1c <7% (35.8% vs. 16.9%; p<0.001). There were no significant differences in adverse events or hypoglycemia between the groups and no significant changes in body weight in either group. These results are consistent with our perception that omarigliptin offers fairly modest glucose-lowering efficacy and that its once-weekly dosing regimen would be its main advantage over other DPP-4 inhibitors. Merck announced in April that it had decided not to submit omarigliptin in the US or Europe due to “business reasons,” namely the concern that it would cannibalize market share from Januvia (sitagliptin) and the desire to commit greater resources to SGLT-2 inhibitor ertugliflozin. To us, this decision underscores the rising bar for new diabetes drugs and the relatively greater focus on SGLT-2 inhibitors compared to DPP-4 inhibitors in recent years. The commercial decision is depressing in our view since we see huge potential for better adherence with a once-weekly – the research on the payer state may not have been particularly positive, which is unfortunate for patients, payers, and providers.

Effect of Ertugliflozin Plus Sitagliptin on Glycemic Control vs. Either Treatment Alone in Subjects with T2DM Inadequately Controlled with Metformin (125-LB)

R Eldor, R Pratley, G Golm, S Huyck, Y Qiu, S Sunga, J Johnson, S Terra, J Mancuso, S Engel, and B Lauring

Dr. Eldor and colleagues presented interim, 26-week results from an ongoing 52-week randomized, double-blind, phase 3 trial comparing the safety and efficacy of Merck/Pfizer’s ertugliflozin plus sitagliptin (Merck’s Januvia) versus either drug alone in patients with type 2 diabetes. The study recruited 1,233 patients inadequately controlled (A1c 7.5-11%) on stable metformin (≥8 wks at ≥1,500 mg/day), who were randomized to one of five groups: ertugliflozin 5mg or 15mg daily plus sitagliptin 100mg daily, ertugliflozin 5mg or 15mg daily alone, or sitagliptin 100mg daily alone. Data at 26 weeks showed that co-administration of ertugliflozin with sitagliptin led to significantly greater reductions in A1c (1.5% for both groups) compared to either drug alone (1%-1.1% across the three groups; p<0.002). A similar effect was observed with fasting plasma glucose and percentage of patients achieving A1c <7%. Co-administration also led to significantly greater reductions in body weight and systolic blood pressure compared to sitagliptin alone. Static beta-cell responsivity increased across all treatment arms and no difference was observed with the co-administration groups. 

  • The retention rate across all groups at 26 weeks was 92-96%. The authors provided the ranges of baseline characteristics across all five groups: average age of 55 years, % male of 51-62%, mean A1c of 8.50-8.57%, duration of T2DM of 6-7 years, eGFR of 92 mL/min/1.73m2, weight of 88-90 kg [194-198 lbs], and BMI of 32-33 kg/m2

Table 1: Data from 26 weeks showing greater reductions in A1c, FPG, weight, and SBP with combined ertugliflozin + sitagliptin versus either drug alone.

Reduction from baseline:

ERTU 5mg

ERTU 15mg

SITA 100mg

ERTU 5mg + SITA 100mg

ERTU 15mg + SITA 100mg

N

250

248

247

243

244

A1c (%)

1

1.1

1.1

1.5*

1.5*

FPG (mg/dl)

35.5

37.1

25.9

44.4*

48.9*

Body weight

 

2.7 kg  [6.0 lbs]

3.7 kg    [8.2 lbs]

0.7 kg       [1.5 lbs]

2.5 kg                     [5.5 lbs]

2.9 kg

[6.4 lbs]

SBP

3.9

3.7

0.7

3.4#

3.7#

Pt with A1c <7%

66 (26%)

79 (32%)

83 (34%)

127 (52%)

120 (49%)

* p<0.002 vs. individual treatments

# p<0.005 vs. sitagliptin treatments (comparisons to ertugliflozin alone were not performed)

p<0.001 based on model-estimated odds ratio comparing ERTU+SITA vs. individual treatments

  • The safety profiles were similar between the five groups, with the exception of a higher observed rate of genital mycotic infections in the groups that included ertugliflozin. The authors note that there was no meaningful difference in urinary tract infection incidence between the groups, and that the rate of hypovolemia and symptomatic hypoglycemia were low across treatment groups.

Effects of Linagliptin on Glycemic Control and Albuminuria in Type 2 Diabetes – THE MARLINA-T2D TriaL (17-LB)

P Groop, M Cooper, V Perkovic, B Hocher, K Kanasaki, G Schernthaner, K Sharma, R Stanton, R Toto, J Cescutti, M Gordat, T Meinicke, A Koitka-Weber, H Woerle, and M Eynatten

Dr. Groop (who is a big deal) and colleagues presented full results of the MARLINA-T2D trial, a double-blind, placebo-controlled clinical trial that gauged glycemic and renal effects of the DPP-4 inhibitor linagliptin (Lilly/BI’s Tradjenta) in adult patients with type 2 diabetes and confirmed albuminuria (UACR 30-3000 mg/gCr). At baseline, participants (n=360) were on up to two oral glucose-lowering drugs or insulin and a stable dose of ACE inhibitor or ARB. After a two-week placebo run-in period, participants were randomized into linagliptin (n=182) and placebo (n=178) groups. Placebo-adjusted data collected at the end of the 24-week treatment period indicated a significant association between a once-daily 5 mglinagliptin treatment and reduced A1c levels (-0.60%, baseline A1c= 7.84%; p<0.0001). 36.2% of linagliptin-treated individuals with baseline A1c≥7% achieved a target A1c <7% in the trail, compared to 9.3% of placebo-treated individuals (p<0.0001). However, the placebo-adjusted treatment difference of UACR from baseline, -6.0%, was not significant. UACR reduction for patients with UACR <300 mg/gCr at baseline was near significant (-10%, p=0.059). Additional clinical studies are needed to determine renal effects of linagliptin, which is believed to have a more long-term anti-fibrotic mechanism. In terms of safety and adverse events, linagliptin was well-tolerated and had a safety profile similar to that seen in previous clinical trials. Hypoglycemic events were numerically higher in the linagliptin-treated group but event rate was low in both groups overall.

Oral Presentations: Treatment Choices after Orals in Type 2 Diabetes

Superior Efficacy of ITCA 650 vs. Sitagliptin in Uncontrolled Type 2 Diabetes on Metformin: The FREEDOM-2 Randomized, Double-blind, 1-Year Study

Julio Rosenstock, MD (University of Texas Southwestern Medical Center, Dallas, TX)

Dr. Julio Rosenstock presented results from the phase 3 FREEDOM-2 study demonstrating significantly greater A1c reductions (1.5% vs. 0.8%; p<0.001) and weight loss (4 kg vs. 1.3 kg; p<0.001) with Intarcia’s ITCA 650 vs. Merck’s Januvia (sitagliptin). Intarcia announced topline results from the trial in August. The double-blind trial randomized 535 patients with type 2 diabetes on metformin to receive either ITCA 650 + oral placebo or Januvia + implantable placebo for 52 weeks. Patients received the initiation dose of ITCA 650 for 13 weeks and switched to the maintenance dose for the remaining 39 weeks. The A1c difference between the groups was already significant at six weeks and stabilized at week 26; final reductions were 1.5% with ITCA 650 vs. 0.8% with Januvia (baseline = 8.6%-8.7%; p<0.001). ITCA 650 also produced significantly greater reductions in fasting plasma glucose (47 mg/dl vs. 28 mg/dl; p<0.001). Weight loss followed a similar pattern as the A1c reductions, with a fairly early separation that stabilized at around week 26 and remained stable throughout the trial. The final weight reduction was 4 kg (~8.8 lbs) with ITCA 650 vs. 1.3 kg (~2.9 lbs) with Januvia (baseline BMI = 33 kg/m2; p<0.001). ITCA 650 was also superior in terms of the percentage of patients achieving the composite endpoint of A1c reduction >0.5% and weight loss ≥2 kg (61% vs. 28%; p<0.001) and the percentage achieving A1c targets of <7% (61% vs. 42%) and <6.5% (44% vs. 21%). As expected, there were more GI events in the ITCA 650 group, though the discontinuation rates due to these events were low (4.5% for nausea and 2.3% for vomiting). Importantly, the rate of procedure-related adverse events was quite low (<1%) in both groups. Dr. Rosenstock also emphasized that nausea rates peaked when the initial dose was started and when the dose was escalated, but rates were quite low throughout the rest of the trial.

  • We are particularly impressed with the durability of the A1c and weight reductions – the difference between the groups held steady from week 26 through the end of the trial. We also found the results for the composite endpoint especially compelling and expect that payers will as well. Intarcia has reported results from three additional trials for ITCA 650: results from FREEDOM-1 and FREEDOM-HBL demonstrating significant A1c reductions vs. placebo were presented at ADA 2015 and topline results from the FREEDOM-CVO trial demonstrating a neutral effect on CV outcomes were announced in May. The impressive efficacy and guaranteed adherence should make ITCA 650 an appealing option for a wide range of patients and could significantly expand use of the GLP-1 agonist class, although we would not be surprised if the product’s commercial performance falls a bit short of the extremely high expectations that some in the field have set for it, particularly less informed investors looking at the first year or two. We have big expectations that the GLP-1 field will continue to grow, and expect Intarcia to be a meaningful part of this. We appreciate very much Intarcia’s focus on helping improve patient adherence and engagement and look very forward to seeing how the launch emerges. Ideally, this therapy will continue the path that a range of companies are trying to take to make various therapies easier to prescribe and take and stay on.

Questions and Answers

Q: Are there any issues around removal in terms of fibrosis?

A: There were no issues of fibrosis. The technique has been highly revised. It’s now done with a delivery device and different tools to ensure the placement is very superficial. Before there was not a tool to really make sure the device was not placed too deep. Now they have a device where you can’t get too deep, so that’s no longer an issue.

Q: Do you have to take the device out to change the dose?

A: Yes. This device could be used for six months, and eventually it will be one year. Taking it out takes less than two minutes.

Linagliptin (LINA) as Add-on to Empagliflozin (EMPA) and Metformin in Patients with Type 2 Diabetes (T2DM): Two 24-Week Randomized, Double-Blind, Parallel-Group Trials

Baptist Gallwitz, MD (Eberhard Karls University, Tubingen, Germany)

Dr. Baptist Gallwitz presented positive phase 3 data on the glycemic efficacy of Lilly/BI’s Tradjenta (linagliptin) as add-on to Lilly/BI’s Jardiance (empagliflozin) and metformin compared with placebo. These findings come from two 24-week randomized, double-blind, parallel group studies of Tradjenta vs. placebo, as add-on to Jardiance at either the 10 mg or 25 mg doses and metformin in participants with type 2 diabetes. Participants received metformin and either Jardiance at the 10 mg (study 1; n=352) or 25 mg (study 2; n=354) doses for 16 weeks in an open-label period, which was followed by a randomization to 24 weeks of double-blind, double-dummy treatment with additions of Tradjenta (n=126) or placebo (n=130). The findings demonstrated that at 24 weeks, the Tradjenta group resulted in statistically significant reductions in A1c compared with placebo: from a baseline A1c of ~8%, participants achieved placebo-adjusted A1c reductions of 0.32% and 0.47% in the Jardiance 10 mg and 25 mg dose groups, respectively. In addition, the proportion of participants who reached A1c levels below 7% at week 24 in the Tradjenta add-on groups was more than double that of the placebo groups (26% vs. 11% in study 1; 36% vs. 15% in study 2). There were no significant changes in body weight with either treatment group. Regarding safety and tolerability, no new signals emerged: the placebo group reported more adverse events than the Tradjenta add-on group, with three hypoglycemic events occurring in the placebo arm of study 2 (Jardiance 25 mg + metformin). Ultimately, these findings support an SGLT-2 inhibitor/DPP-4 inhibitor combination as a promising treatment option for patients who are inadequately controlled with metformin and an SGLT-2 inhibitor. Such a combination has certainly received increasing attention, as Merck has recently expressed greater excitement on the potential of a Januvia (sitagliptin)/ertugliflozin combination. We look forward to seeing longer-term data on this approach, as these data could potentially help craft more individualized guidance into treatment algorithms.

Questions and Answers

Q: What was the baseline A1c?

A: Around 8%.

Q: Did you add lina or did you switch the empagliflozin to an empa/lina combination?

A: We did not use the fixed-dose combination. We added the lina on.

Q: Do you have glucagon levels?

A: We do not have these yet.

Q: Did you perform a meal test?

A: No, we did not.

Oral Presentations: Beyond Basal Insulin in Type 2 Diabetes – Treatment Intensification Options

Comparison Between SGLT-2 Inhibitors and DPP-4 Inhibitors Added to Insulin Therapy in Type 2 Diabetes: A Systematic Review with Indirect Comparison Meta-Analysis

Se Hee Min, MD (Seoul National University Hospital, South Korea)

Dr. Se Hee Min presented the results of an indirect meta-analysis that compared the effect of SGLT-2 inhibitors plus insulin (SGLT-2i/INS) vs. DDP-4 inhibitors plus insulin (DPP-4i/INS) in type 2 patients. The group performed a systematic review that yielded 14 studies which investigated either SGLT-2i/INSU vs. placebo/INS or DPP-4i/INS vs. placebo/INS (five and nine studies, respectively). Results of the covariate-adjusted indirect comparison using meta-regression analyses showed that SGLT-2i/INS provided greater reductions in A1c (weighted mean difference [WMD] of -0.24%; 95% CI: -0.43 to -0.05%), as well as greater reductions in fasting plasma glucose (WMD -18.0; 95% CI: -28.5 to -7.6 mg/dl) and body weight (WMD -2.38 kg [lbs]; 95% CI: -3.18 kg [7.0 lbs] to -1.58 kg [3.5 lbs]). No difference in hypoglycemia was observed with SGLT-2i/INS compared to DPP-4i/INS (RR 1.19; 95% CI: 0.78-1.82). Dr. Min remarked that in the absence of head-to-head comparisons, these results could serve as the best available evidence for selecting oral agents in patients uncontrolled on insulin. These findings are not surprising to us, as we feel that it is widely understood that the DPP-4 class is slightly inferior in efficacy, but its solid tolerability profile (as well as how easy it is to prescribe) keeps it as a mainstream treatment option.

  • Dr. Min noted that her group focused on SGLT-2 inhibitors and DPP-4 inhibitors because the drugs do not require injections and do not contribute to significant weight gain. Thus, the team views them as preferable add-on agents compared to GLP-1 agonists and TZDs. Furthermore, Dr. Min highlighted that SGLT-2 inhibitors and DPP-4 inhibitors have complementary effects to insulin with regards to hypoglycemia and weight gain.
  • To perform their systematic review, Dr. Min and colleagues searched Medline, Embase, LILACS, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov for randomized controlled trials before June 2015 that compared either SGLT-2i/INSU vs. placebo/INS or DPP-4i/INS vs. placebo/INS. They included only trials that were ≥12 weeks long and that measured A1c as an endpoint. The search yielded 14 trials – five SGLT-2 inhibitor studies and nine DPP-4 inhibitor studies.
  • The indirect analysis involved comparing each drug’s efficacy over placebo. After the initial evaluation yielded no differences between SGLT-2i/INSU and DPP-4i/INS, the authors performed a meta-regression that guided a subsequent covariate adjustment, which yielded the results presented above.

Questions and Answers

Q: The DPP4i/INS studies generally looked at a single dose while the SGLT-2i/INS studies usually had a lower dose and a higher dose. Did you include both doses or the maximum dose?

A: We included the data from the maximum approved dose.

Q: I’m not sure if you could do this because you would need patient-level data, but would you consider comparing the two drugs by baseline A1c category?

A: Thank you for your question. We did not stratify the patients by A1c.

Oral Presentations: Management of Hyperglycemia in the Hospitalized Patient

Safety and Efficacy of Saxagliptin for Glycemic Control in Non-Critically Ill Hospitalized Patients

Rajesh Garg, MD (Brigham and Women’s Hospital, Boston, MA)

Dr. Rajesh Garg presented study findings, demonstrating non-inferiority of saxagliptin compared with the customary intravenous basal-bolus insulin treatment regimen in hospitalized hyperglycemia patients. In this study, type 2 diabetes patients hospitalized for hyperglycemia were randomized to receive either saxagliptin (2.5 mg or 5 mg) (n=30) or basal-bolus insulin therapy (n=32) over the course of six days of hospitalization. Correctional insulin was provided to both groups. According to the findings, there was no significant difference in mean blood glucose levels between the saxagliptin and insulin therapy groups. Across study days 2-5, blood glucose levels averaged 146.6 ± 26.7 mg/dl for the saxagliptin-treated patients and 150.9± 32.9 mg/dl for the insulin-treated patients (p=0.36). Dr. Garg thus concluded that the use of saxagliptin provides an opportunity to reduce insulin use in the hospital without compromising the patients’ glycemic control. As the DPP-4 inhibitor class appears to be inching out of the spotlight with the recent cardioprotection shown in SGLT-2s and GLP-1s, these findings remind us of the potential of this class in the in-patient setting – a use case in which this class is likely favored, due to its impressive tolerability. We are also keen to see more on the combination use of this drug.

Questions and Answers

Q: The FDA has a controversial warning about saxagliptin and heart failure. Do you have any comments?

A: I really don’t believe there is the risk for heart failure; we did our best including those patients.

Q: Can you speculate about why blood glucose got better in the treatment group over the control group?

A: I think it is the fear of the use of insulin. I think we should take that into the calculation when we talk about improving diabetes care on the inpatient side. Despite all the things it can do, there is still fear of insulin.

Q: Were there any treatment failures in the treatment group?

A: There were two patients who had to be switched to the control insulin treatment because they demonstrated two consecutive blood glucose readings above 200 mg/dl.

Q: What is your data on hypoglycemia?

A: There was no hypoglycemia. One patient in each the treatment group and the placebo group had blood glucose readings below 70 mg/dl, but none had readings below 50 mg/dl.

Oral Presentations: Tissue Lipids and Lipoproteins and their Consequences

DPP-4 Inhibitor, Anagliptin, Ameliorates Fasting and Postprandial Hypertriglyceridemia

Masami Sairyo, MD (Osaka University, Osaka, Japan)

Dr. Masami Sairyo presented results from a preclinical study demonstrating that the DPP-4 inhibitor anagliptin (Kowa’s Suiny, approved in Japan), diminished the accumulation of triglycerides (TG) and chylomicron remnants (CM-R) and decreased appetite and weight gain in Western diet-fed mice. Both effects attenuated postprandial hypertriglyceridemia (PHTG), a condition strongly associated with type 2 diabetes and cardiovascular disease that results from invasion of arterial walls by CM-R. In the study, 8-week old JAX mice were fed normal chow diets either without or with 0.3% anagliptin for one month. Then, oral fat loading (OFL) tests were performed with olive oil (17 µL/g body weight) after overnight fasting. Plasma concentration measurements of triglycerides, total cholesterol, free fatty acids, and apoB-48 (a chylomicron remnant) were taken in the fasting state and two, four, and six hours after OFL. Results showed that anagliptin-treated mice had significantly lower (p<0.05) levels of triglycerides and apoB-48 in both the fasting and postprandial states. RT-qPCR showed suppressed mRNA expression of NPC1L1, DGAT1, and MTP, which are associated with cholesterol uptake and chylomicron composition. Additional high-performance liquid chromatography analyses showed that treatment with anagliptin decreased both plasma and intestinal lymph peaks of CM and VLDL lipoproteins. In conclusion, these results suggest that anagliptin decreases the synthesis and secretion of chylomicrons, which decreases the risk of PHTG.

Symposium: Management of Hyperglycemia in the Hospitalized Patient

Randomized, Controlled Trial on the Efficacy of Sitagliptin Therapy for the Inpatient Management of General Medicine and Surgery Patients with Type 2 Diabetes: Sita-Hospital Trial

Francisco Pasquel, MD (Emory University, Atlanta, GA)

Dr. Francisco Pasquel presented data from a study of hospitalized patients with type 2 diabetes, which found that treatment with sitagliptin plus once daily glargine (n=140) results in fewer insulin injections and a smaller average daily insulin dose than a basal bolus regimen plus once daily glargine and rapid-acting insulin at mealtimes (n=140). The trial enrolled patients from hospitals at Emory, the University of Michigan, Temple University, and Ohio State University. Patients treated with sitagliptin required a mean of 2.2 insulin injections per day, significantly fewer than patients in the basal bolus group (2.9 injections/day, p<0.001). Similarly, patients treated with sitagliptin required a lower average dose of insulin (24 units/day vs. 34 units/day, p<0.001). The study found no significant differences in daily blood glucose, number of patients within range for blood glucose, length of hospital stay, rate of complications, extreme hypoglycemia events (<40 mg/dL), or extreme hyperglycemia events (>200 mg/dL) between groups. In fact, there wasn’t a single episode of severe hyperglycemia for any patient in this trial. Dr. Pasquel underscored that the decreased need for insulin makes sitagliptin a safe and convenient option to control hyperglycemia in hospitalized patients. These findings further confirm the DPP-4 inhibitor class as a very well-tolerated class with versatile use in patients.

  • Sitagliptin was dosed based on a patient’s eGFR (100 mg/day if eGFR >50 ml/min/1.73m2, 50 mg/day if eGFR 30-50 ml/min/1.73m2). Patients with more severe chronic kidney disease were excluded from the trial, along with any patients who had already experienced a severe hyperglycemia crisis, had diagnosed mental illness, or were pregnant.
  • Dr. Pasquel asserted that sitagliptin might be preferable to subcutaneous insulin as a treatment for hyperglycemia in non-ICU hospital settings. Current clinical guidelines recommend subcutaneous insulin for hospitalized type 2 diabetes patients, but according to these findings, sitagliptin alongside once daily glargine appears to be just as effective while reducing the frequency and dose of daily insulin injections.

Questions and Answers

Q: Many hospitalized patients with type 2 diabetes have renal or hepatic disease. For these individuals, was sitagliptin the best DPP-4 inhibitor? Would linagliptin have been better?

A: These patients are typically excluded from such studies, as we would expect higher hyperglycemia. We cannot extrapolate our findings to these two populations. If we were to try and extend our results, perhaps linagliptin would be a better choice because of lower accompanying insulin doses.

Q: I didn’t see pancreatitis or pancreatic cancer listed as exclusion criteria.

A: I presented a summarized list, but yes, we excluded patients with pancreatitis or pancreatic cancer.

Q: Many patients in hospitals aren’t eating well, or regularly. Were these people excluded? What are your thoughts on the utility of sitagliptin for patients who frequently miss meals at home?

A: In our study, the investigator could decide if a patient shouldn’t receive a full dose of insulin if he/she was not eating well. Maybe that’s why patients in the basal bolus group didn’t receive high doses of insulin, because of surgical procedures and not being able to eat well.

Q: What time did you administer sitagliptin?

A: For logistical reasons, it was administered ideally in the morning but at least by 2 or 3 pm on the first day. Subsequent doses were given around 9 am every morning.

Novel Therapies

Posters

MEDI4166: A PCSK9 Ab-GLP-1 Fusion Molecule That Elicits Robust Antidiabetic and Antihyperlipidemic Effects in Rodents and Non-Human Primates (35-LB)

J Trevaskis, A Suckow, T Hummer, M Chodorge, A Celeste, D Hornigold, J Naylor, L Jenkinson, M Feigh, D Fairman, M Agoram, C Lee, S Coats, J Grimsby, C Rondinone, and A Konkar

AstraZeneca presented preclinical data for its PCSK9 inhibitor/GLP-1 agonist combination MEDI4166 demonstrating improvements in glucose, body weight, and LDL cholesterol in rodents and non-human primates. First, MEDI4166 was proven to be an effective GLP-1 agonist based on cAMP production after transfection of Chinese hamster ovary cells with a series of mammalian GLP-1 receptors. Second, ELISA assays indicated that MEDI4166 inhibited PCSK9 and restored LDL uptake in HepG2 hepatoma cells.  Third, single subcutaneous injections of 0.1, 1, and 10 mg/kg MEDI4166 into diet-induced obese (DIO) mice improved glucose tolerance, measured by glucose excursions seven days after the injection. Two- and six-hour fasting blood glucose levels also decreased in a dose-dependent fashion. Repeated weekly injections of either 3, 10, or 30 mg/kg MEDI4166 also reduced body weight of DIO mice over a 28 day period and prevented diabetes progression in db/db mice. Lastly, single injections of either 10 or 100 mg/kg MEDI4166 into healthy male cynomolgus monkeys showed that the higher dosage produced greater reductions in LDL cholesterol. AZ is currently conducting a two-part phase 1/2 trial of MEDI4166 in patients with type 2 diabetes that is expected to complete in November 2016 – see our AZ 1Q16 report for more details. This combination could have enormous potential given how many patients with type 2 diabetes are at high risk for cardiovascular disease, particularly if the GLP-1 agonist and PCSK9 inhibitor classes are eventually both established as cardioprotective.

MEDI0382, a GLP-1-Glucagon Dual Agonist, Meets Safety and Tolerability Endpoints in a Single-Dose Study in Healthy Volunteers (107-LB)

P Ambery, S Klammt, M Petrone, W Pu, S Dicostanza, L Jermutus, and C Rondinone

This poster presented the findings of a phase 1 randomized, blinded study of GLP-1/glucagon dual agonist MEDI0382, which demonstrated that the candidate met safety and tolerability endpoints. The study was conducted in six cohorts of healthy participants in Germany; each cohort included eight participants, six of whom received one dose each of MEDI0382 at 5, 10, 30, 100, 150, and 300 µg, and two of whom received placebo. Blood pressure, pulse, food intake, and adverse events were monitored for 28 days. At the end of this study period, larger doses of MEDI0382 showed decreases in daily food intake and plasma glucose levels as compared to placebo. Specifically, doses of 30, 100, 150, and 300 µg respectively showed 96%, 82%, 60%, and 23% of daily food intake compared with placebo. Post-meal glucose level peaks decreased in all patients receiving doses of MEDI0382 compared to the placebo. Heart rate over the 28-day observation period did not statistically differ from the pre-dose baseline, except in the 300 µg dosing group. In addition, MEDI0382 was found to be well-tolerated, although vomiting, increased pulse rate, and blood pressure were observed at the higher doses, establishing a tolerability window for future studies in patients with diabetes (doses starting at 100 µg caused episodes of vomiting; 1 patient with 1 total episode of vomiting, 4 patients with 9 episodes, and 5 patients with 30 episodes at 100, 150 and 300 µg of MEDI0382, respectively). Otherwise, gastrointestinal disorders were the major reported adverse event (33.3% of participants). On the pharmacokinetic side, MEDI0382 showed a maximum concentration between 4.5-9 hours, as the data showed to be consistent with a profile indicating once-daily dosing. This candidate remains early in development, but we find this combination approach potentially promising, as it has clear benefits in both glycemic control and weight management. Next question – how cardioprotective or renal protective is it?

A Leucine, Metformin, and Sildenafil Combination Regresses Nonalcoholic Steatohepatitis (NASH) in Mice (260-LB)

M Zemel, A Bruckbauer, and O Flores

NuSirt presented data from a dose-finding study of its leucine/metformin/sildenafil combination in a mouse model of nonalcoholic steatohepatitis (NASH). This study builds on previous work showing that leucine allosterically overexpresses Sirt1, that leucine/metformin combination therapy reverses non-alcoholic fatty liver disease (NAFLD) in mice, and that the triple combination with sildenafil provides even greater efficacy. In this study, mice (n=90) were fed either a low-fat diet (10% calories from fat) or a high fat/atherogenic diet (1.25% cholesterol by weight and 60% of calories as saturated fat) for eight weeks and then randomized to one of nine treatment groups for an additional eight weeks. Treatment groups included two control groups (low-fat diet and high-fat diet) and seven active treatment groups involving 24 g/kg leucine paired with different doses of metformin (either 0.5 or 1.0 g/kg) and sildenafil (either 12.5, 25, 50 or 100 mg/kg). Treatment with the drug combination resulted in, on average, a 43% reduction in steatosis, a 55% reduction in inflammation, and a 50% reduction in fibrosis after the eight-week treatment period. These data confirmed previous results demonstrating that the appropriate dose for metformin is 0.5 g/kg in mice, with no additional benefit seen with higher doses. Sildenafil produced dose-dependent effects up to a dose of 25mg/kg, at which point there was no additional benefit. The optimal human equivalent doses were determined to be 2.2 g/day of leucine, ~500 mg/day of metformin and 2mg/day of sildenafil. NuSirt is currently conducting a phase 2a trial of the combination (also referred to as NS-0200) in patients with NAFLD-NASH that is expected to complete in 4Q16; see our interview with management earlier this year for more updates on the company’s plans.

Antidiabetic Effects of Novel, Long-Acting Amylin Analogue ZP4982 in ZDF Rats (283-LB)

J Skarbaliene and R Just

This study aimed to explore the anti-diabetic impact of Zealand’s long-acting amylin analog ZP4982, which improves glycemic control by inhibiting food intake and gastric emptying and suppressing glucagon secretion. Over the course of four weeks, Zucker Diabetic Fatty (ZDF) rats were subcutaneously administered either vehicle, ZP4982 (30 nmol/kg, dosed every fifth day), or liraglutide (40 nmol/kg, dosed twice daily). ZP4982-treated rats showed significantly lower non-fasting blood glucose levels after two weeks and significantly lower non-fasting and fasting blood glucose levels at the end of the study (p < 0.001 vs. vehicle for all; p-value vs. liraglutide not given). ZP4982 also resulted in significantly lower A1c levels compared to both vehicle- and liraglutide-treated rats after four weeks  (p<0.001 vs. vehicle; p<0.05 vs. liraglutide). Additionally, ZP4982 significantly increased insulin levels and lowered blood glucose levels during an intra-peritoneal glucose tolerance test (p < 0.001 vs. vehicle; p-value vs. liraglutide not given). This is the first data we have seen for this candidate, and we are excited to see continued early-stage activity in diabetes from Zealand despite the company’s stated shift toward specialty disease areas. We imagine that weight loss could be a key advantage for this candidate compared to existing type 2 diabetes drugs and look forward to seeing data on this endpoint in future studies.

Potent Cholesterol Lowering Effect of the Novel Long-Acting GLP-1/Glucagon Dual Agonist HM12525A (1026-P)

SY Jung, YJ Park, JS Lee, EJ Kim, YM Lee, YH Kim, M Trautmann, and S Kwon

This poster presented preclinical data suggesting a range of metabolic benefits for Janssen/Hanmi’s long-acting once-weekly GLP-1/glucagon dual agonist HM12525A. This study investigated HM12525A’s effects on levels of total cholesterol, HDL cholesterol, LDL cholesterol, liver LDL cholesterol receptor expression, serum cholesterol, serum PCSK9, hepatic triglycerides, NAFLD scores, PPAR-α and CPT-1, and ketone bodies in mice, hamsters, and rats. Previously studies had shown that HM12525A produced greater weight loss compared to GLP-1 agonist liraglutide (Novo Nordisk’s Victoza). In this study, HM12525A was found to lower serum cholesterol levels, decrease LDL cholesterol levels, and decrease the LDL/HDL ratio more than liraglutide. HM12525A treatment was associated with a 68% reduction in total cholesterol and a 48% reduction in LDL cholesterol, compared to 12% and 2% reductions, respectively, with liraglutide. HM12525A had little effect on increasing HDL cholesterol levels (and we’ve seen from CETP trials that increasing HDL cholesterol may not translate into positive cardiovascular effects). Mechanism of action studies showed that the use of HM12525A leading to decreases in levels of cholesterol and the LDL/HDL ratio may be attributed to its ability to increase hepatic β-oxidation, decrease the hepatic LDL receptor clearance by decreasing PCSK9 expression, inhibit hepatic cholesterol biosynthesis, and increase HDL cholesterol. These results suggest that HM12525A may have therapeutic potential to treat hyperlipidemia. Combined with previous mouse studies indicating greater reductions for HM12525A vs. liraglutide in terms of A1c (-1.4% vs +1.2%) and body weight (-31% vs. -17%), the efficacy profile of this dual agonist appears particularly promising. The GLP-1/glucagon dual agonist class has been the focus of significant industry interest and investment for some years and we’re intrigued by the possibility of a once-weekly drug that can offer a winning combination of A1c, body weight, and cholesterol reductions. We certainly hope these impressive results translate into human studies and into positive effects on cardiovascular outcomes down the line.

Long-Acting GLP-1 and Glucagon Receptor Dual Agonists for the Treatment of Type 2 Diabetes (1049-P)

S You, M McDonald, M Case, D Steiner, T Tat, C Jenkinson, R Pick, J Hart, V Moreno, J Parise, W Yan, R Camacho, R Swanson, E Chi, K Demarest, and J Leonard

Janssen introduced a new preclinical GLP-1/glucagon dual agonist, JNJ-54728518 candidate in this poster. The candidate is a PEGylated derivative of oxyntomodulin with an increased half-life (18 hours in lean mice) and retained potency for both the GLP-1 and glucagon receptors. Diet-induced obese (DIO) mice treated with JNJ-54728518 were found to be much more tolerant of glucose associated with greater secretion of glucose-dependent insulin. Compared to 10 nmol/kg of GLP-1 agonist liraglutide (Novo Nordisk’s Victoza), administration of 10 nmol/kg of JNJ-54728518 produced lower glucose levels (59 vs. 118 mg/dl), lower daily food intake (0.04 vs. 0.07 g/g body weight, more fat loss (12.3 vs. 6.0 g), and greater body weight loss (-27% vs. -7%). Janssen also shared that JNJ-54728518 “markedly” reduced cholesterol levels. Late last year, Janssen acquired Hanmi’s phase 2 GLP-1/glucagon dual agonist, which has a similarly promising efficacy profile in terms of A1c-lowering, body weight reduction, and cholesterol-lowering. We’ll be curious to see how this preclinical candidate fits into Janssen’s pipeline and wonder if Janssen may be “hedging its bets” by including multiple GLP-1/glucagon agonists in its pipeline in case one doesn’t quite meet the increasingly high efficacy bar for new diabetes drug.

Effects of Leucine-Metformin Combinations on Glycemic Control in Type 2 diabetes (1144-P)

K Niswender, O Kolterman, M Kosinski, and M Zemel

NuSirt BioPharma presented results from their phase 2a head-to-head study of  a leucine/metformin combination compared to 850mg metformin BID. After a washout period, a fixed dose of leucine was combined with different levels of metformin (125mg, 250mg and 500mg) and administered twice daily. The control, 500mg metformin, was administered twice daily for two weeks then titrated up to 850mg twice daily for an additional two weeks. Meal tolerance tests were conducted at day 0 and day 28 to analyze changes in glucose area under the curve (AUC). Fasting plasma glucose and insulin, A1c, and 24-hour glucose tests were also undertaken. In a per-protocol analysis, the metformin control arm exhibited greater improvements in fasting glucose (p<0.05) and average daily glucose (p<0.05) and non-significantly greater improvements in total, but not incremental, glucose AUC. An intention-to-treat (ITT) analysis demonstrated comparable glucose improvements between leucine/metformin and the metformin control. The authors attributed the lackluster results partly to the metformin control arm exhibiting markedly greater improvements in glucose and glucodynamics than expected (from previous trials). The metformin control arm had an ~two-fold greater loss of glycemic control during washout (p<0.05) resulting in poorer baseline control and a larger potential improvement with treatment compared to the other arms. Adjusting for this difference resulted in comparable effects of leucine/metformin and the control.

Safety, Pharmacokinetics, and Pharmacodynamics of the Novel Dual GLP-1/Glucagon Agonist SAR425899 in Healthy Subjects and Diabetes Patients

Joachim Tillner, PhD (Sanofi, Paris, France)

Dr. Joachim Tillner (Sanofi, Paris, France) presented positive phase 1 data for Sanofi’s GLP-1/glucagon dual agonist SAR425899 demonstrating a reassuring safety/tolerability profile, a half-life consistent with once-daily dosing, and improvements in glycemia and body weight. We saw some of this data at the Keystone Symposia on Molecular and Cellular Biology meeting in April demonstrating significant reductions in weight (-5.5 kg [~12 lbs] vs. -2.4 kg [~5.2 lbs]; p<0.001) and “clear” (p-value not specified) reductions in A1c (-0.59% vs. +0.06%) and fasting plasma glucose (-55 mg/dl vs. -22 mg/dl) with SAR425899 vs. placebo after four weeks in 36 patients with type 2 diabetes. In this presentation, Dr. Tillner also shared data from the other two parts of Sanofi’s phase 1 program for the candidate: a single ascending dose study in 32 healthy males and a three-week multiple ascending dose study in 40 healthy males. The three studies together demonstrated a safety/tolerability profile for SAR425899 that was comparable to GLP-1 single agonists. GI side effects were the most prominent adverse events (nausea was the limiting factor for dose escalation in the single ascending dose study) and the drug produced an increase in heart rate in the same range as previously studied GLP-1 agonists. Based on these results, Dr. Tillner expressed confidence that GLP-1/glucagon dual agonism works, despite his initial incredulity at the idea of a diabetes treatment that stimulates glucagon production. He stated that Sanofi’s goal for SAR425899 is to equal GLP-1 agonists in terms of glycemic control and surpass them in terms of weight reduction. We assume the company is planning to pursue a type 2 diabetes indication for the candidate, but we wonder whether there could be any potential in obesity or prediabetes as well. GLP-1/glucagon dual agonists have attracted a significant amount of industry interest and we will be curious to see how the various candidates can differentiate themselves – see our competitive landscape page for an overview of the current field.

Questions and Answers

Q: What kind of ratio are you expecting between GLP-1 and glucagon? Are you seeing evidence of glucagon target engagement?

A: Target engagement is something we discussed from the beginning. Glucagon increases blood glucose, so the idea is that if you increase the dose you’ll see a U-shaped curve of blood glucose. We haven’t seen that so far. We’ve thought about biomarkers like FGF21 and have measured them but seen no real effect. We’ve measured blood lipids hoping that glucagon might have an effect on lipid metabolism. For me the results are not absolutely clear. They don’t confirm that there’s no effect. We’ve measured ketone bodies and seen a change but that data is still in discussion. There’s no clear answer. Our plan is to go to the target of energy expenditure and do dedicated studies to see if glucagon does what it needs to do.

Oral Presentations: Preclinical Therapeutic and Signaling Regulation of Insulin Sensitivity

Acute Metabolic Effects of MEDI0382, a GLP-1/Glucagon Dual Agonist, in Wild Type and GLP-1 Receptor Knockout Mice

Sarah Will (MedImmune, Gaithersburg, MD)

Ms. Sarah Will provided a rapid-fire summary of data characterizing the acute effects of AstraZeneca’s GLP-1/glucagon receptor dual agonist MEDI0382 for diabetes and obesity. Results showed that a single subcutaneous dose of MEDI0382 reduced fasting glucose levels, glucose AUC, and food intake in wild type but not GLP-1 receptor knockout (KO) mice. Specifically, in wild type mice, MEDI0382 (3 nmol/kg) reduced fasting glucose levels by 42% (p<0.01) compared to vehicle, while an equimolar dose of liraglutide did not. Further, MEDI0382 reduced glucose AUC (area under the curve) levels to a greater degree than did liraglutide following an intraperitoneal glucose challenge (53% vs. 26%). In addition, MEDI0382 reduced food intake in overnight fasted mice by 18%, while an equimolar dose of liraglutide reduced food intake by 34%. These effects were completely blocked in GLP-1 receptor KO mice for both MEDI0382 and liraglutide; further, MEDI0382 elevated glucose levels in GLP-1 receptor KO mice but did not do so in wild type mice. In contrast, treatment with IUB118 (a selective glucagon-receptor agonist) significantly elevated glucose levels and failed to inhibit food intake in both wild type and GLP-1 receptor KO mice. Ms. Will noted that taken together, these data indicate that MEDI0382 engages both GLP-1 and glucagon receptors, though the acute effects of glucose tolerance and food intake are mediated solely by GLP-1 receptors. We have high optimism for dual agonists, and these results do not disappoint – however, greater research is required to determine the safety, efficacy, and durability of MEDI0382 in human participants.

Oral Presentations: Lipid Mediators

Treatment of Type 2 Diabetes Through Hepatic Insulin Signaling

Rongya Tao, PhD (Harvard Clinical and Translational Science Center, Cambridge, MA)

Dr. Rongya Tao presented data on the role of hepatic insulin signaling in metabolic homeostasis with the goal of unearthing possible treatment options for type 2 diabetes that target insulin resistance.  Specifically, insulin receptor substrates 1 and 2 were investigated in liver-specific knockout mice (LDKO), a diabetic mouse model.  Studies showed that insulin regulation of hepatic glucose production was disrupted in LDKO mice, but this was corrected when Fox01 was deleted in triple knockout mice (LTKO).  Therefore, hepatic insulin signaling is independent from the liver’s reduction of glucose production, and Fox01 is necessary to maintain hepatic glucose production at regular levels.  LDKO mice also had deregulated metabolic homeostasis in fat, but this was normalized in the LTKO mice.  The LDKO mice also showed greater oxygen consumption and energy use and remained resistant to high fat diet-induced obesity, while the LTKO mice consumed oxygen normally.  Insulin also did not inhibit lipolysis in LDKO mice, which suggests higher lipid synthesis and secretion.  A further RNA microarray revealed more than 20 secreted proteins that are different in the livers of LDKO mice, which may contribute to diabetes. This research should shed more light on the role of hepatic insulin signaling in the pathogenesis of type 2 diabetes and hopefully lead to the discovery of new therapeutic targets.

Oral Presentations: Clinical Therapeutic and Signaling Regulators of Insulin Sensitivity

Duodenal Mucosal Resurfacing Improves Metabolic Measures in Type 2 Diabetes: First-in-Human Study, 6 Month Data

Alan Cherrington, PhD (Vanderbilt University, Nashville, TN)

Dr. Alan Cherrington (Vanderbilt University, Nashville, TN) provided new details on the six-month data for Fractyl’s Revita Duodenal Mucosal Resurfacing procedure for type 2 diabetes. The procedure, which recently received CE Mark approval, involves ablation of a portion of the duodenal mucosa via a technique that the company has characterized as similar to an upper endoscopy. Dr. Cherrington shared that significant A1c reductions occurred in both patients with a baseline A1c >10% (mean baseline A1c=~11%) and those with a baseline A1c of 7.5%-10% (mean baseline A1c=~9%) who had a “long” segment of more than 9 cm ablated (mean= ~9.3 cm). The procedure demonstrated peak efficacy at three months, with A1c reductions of ~3.5% in the higher baseline A1c cohort and ~2% in the lower baseline A1c cohort. However, the effect was substantially attenuated at six months, (much more so in the subjects who reduced their diabetes medications), resulting in a final six-month A1c reduction of 2.1% in the higher baseline A1c group and 1.0% in the lower baseline A1c group. These A1c reductions are not as strong as we might have hoped, given the high starting A1c and the relatively invasive procedure (as compared to a more traditional oral or injectable medication). We imagine that Fractyl will need to demonstrate sustained efficacy in order for the procedure to appeal to a large number of patients, and we hope future trials can provide more clarity on this point. Dr. Cherrington also shared that the Revita DMR procedure improved insulin sensitivity (as measure by HOMA-IR) and metabolomic analysis indicated improved insulin sensitivity, reduced oxidative stress, and improved mitochondrial function following the procedure.

  • We previously saw six-month data demonstrating a mean A1c reduction of 1.2% (p<0.001) at six months, as well as improvements in fasting glucose (non-significant, p=0.09), postprandial glucose (p<0.05), and weight loss (-1.8 kg, p<0.05) in the cohort of patients who had a “long” segment ablated. Fractyl also recently presented data at the EASL International Liver Conference demonstrating improvements in hepatic transaminase levels (AST and ALT specifically, p<0.01) with the procedure.

Oral Presentations: Treatment and Management of Complications – Can a Dog Really Smell Hypoglycemia?

Superior Efficacy of a Dual GLP-1/Glucagon Receptor Agonist in Reversing Steatosis and Improving Indices of Nonalcoholic Steatohepatitis (NASH) Compared with GLP-1 Receptor and FXR Agonists in a Mouse Model of NASH

James Trevaskis, PhD (MedImmune, Gaithersburg, MD)

Dr. James Trevaskis presented results, showing the superior efficacy of dual GLP-1/glucagon agonist G49 in the mouse model of nonalcoholic steatohepatitis (NASH) compared to GLP-1 agonist liraglutide and FXR agonist obeticholic acid (OCA). As background, the dual agonist G49 combines elements of glucagon and exenatide. The study stratified C57BL6 mice (who were maintained on a high fat, fructose, and cholesterol diet) to liraglutide, OCA, G49, or placebo for 28 days. The findings demonstrated G49’s superiority to both liraglutide and obeticholic acid (OCA) in lowering blood glucose, hepatic triglycerides and collagen, and overall NASH score. Specifically, hepatic triglycerides were decreased 52% by G49, and less so by liraglutide (32%) and OCA (23%), p<0.001. G49 reduced hepatic collagen by 40% (p=0.053 vs. placebo vehicle), with more modest reductions by liraglutide (29%) and OCA (19%). Body weight declined approximately 10% in mice treated with G49 or liraglutide, but not OCA, and the weight loss was driven by changes in fat mass without substantial changes in lean mass. Dr. Trevaskis attributed this superiority to the greater impact of G49 on fibrosis, since the drug’s effect on steatosis was comparable to that of liraglutide. Dr. Trevaskis used this data to point out the promise of the dual agonist drug class, especially in treating NASH.

  • According to Dr. Trevaskis, the promise of G49 lies in its ability to work on three axes – reducing steatosis, reducing fibrosis, and improving metabolism. He stressed that there is a critical, unmet need for effective NASH therapies and shared that parallel to ongoing clinical trials for liraglutide and Intercept Pharmaceutical’s OCA, there is emerging interest in dual agonists like G49, which Dr. Trevaskis called a “magic drug” due to its multiple physiological targets.
  • Despite its pronounced effect on overall NASH score, G49 was less effective than liraglutide and OCA in reducing plasma ALT. Liraglutide resulted in a 61% decrease in ALT. OCA resulted in a 43% decrease, while G49 resulted in a 38% decrease (p=0.052 vs. placebo).

Questions and Answers

Q: One of your intriguing findings was that improvement in ALT was better with liraglutide than with other drugs. Clinicians tend to use ALT as a dominant measure, but is it as good of a marker for fat or fibrosis in the liver?

A: ALT is not a specific liver damage marker for NASH, but it’s how many patients come to realize that they have high liver fat. So ALT may indicate that there’s something else impacting liver health.

Q: What is the exact contribution of glucagon-receptor activation?

A: Glucagon-receptor activation increases lipid oxidation quite dramatically in isolated hepatocytes. This gives us reason to believe that there’s some kind of mobilization at the mitochondrial level, along with some links to lipid metabolism that are underappreciated at this point. The combined effect of glucagon-receptor activation and GLP-1 activation seems to override any negative effects of glucagon. The potency of the two compounds working together is very important. Too much glucagon alone will drive excessive weight loss.

Q: Have you looked at GLP-1 receptors in the pancreas, kidneys, or other organs?

A: A follow-up study is looking at the pancreas, but we haven’t looked at any other tissues.

Symposium: Fifty Winks of Diabetes

Circadian Timing of Metabolism in Mouse Models and Humans

Charna Dibner, PhD (University of Geneva, Switzerland)

Dr. Dibner presented a series of studies from her lab on rhythmic insulin and glucagon release. She opened with a broad view on peripheral clocks, noting that they control body metabolism in nearly all tissues, including the pancreas. She reviewed experiments that confirmed the presence of cell-autonomous, functional clocks in islet cells. A key component of this mechanism is the transcription factor CLOCK, which regulates rhythmic gene expression. Dr. Dibner showed that basal insulin secretion is circadian in nature, and is altered by disruptions in CLOCK. She then turned to studies comparing oscillation properties in alpha vs. beta cells. RNAseq data show that several important genes in these cells – including insulin and glucagon –  are regulated in a circadian manner, with similar and distinct characteristics between the two cell types. Notably, under constant in vitro glucose conditions, both hormones are secreted in a rhythmic manner, though the glucagon peak appears to lag behind that of insulin (per Dr. Dibner, this is to be confirmed with future data). Circadian timing has also been shown as a potential contributing factor to obesity, as this work likely has broad implications across the metabolic disease spectrum.

Questions and Answers

Q: Do you think that if you use an inhibitor against glucagon in your mice, that you will block the glucagon signal on beta cells and thus disrupt the circadian rhythm?

A: That’s a good question. We are doing this study. It is difficult to get glucagon knock-out mice, but we are blocking glucagon with siRNA. We are on the way to showing it. That is a very good point.

Q: You showed the difference in phase in the synchronized alpha and beta cells. That suggests that there is a period difference. The only alternative explanation would be an autocrine resetting that is occurring with each cycle. Can you clarify this? Your studies separated alpha and beta cells, so autocrine signaling is unlikely.

A: I can see your point. We have to consider the viability of the cell. Here, we rarely did more than 2.5 cycles. I am careful with the period – I don’t take the first period seriously. I think the alpha cells have a shorter period length, if you synchronize with forskolin.

Q: That would suggest that the composition of the clock mechanism is different in these two cell types. One explanation could be post-translational modification.

A: Right. I know you’re trying to help, but that’s difficult to imagine. It’s not very clear because we’re only doing 2.5 cycles. It’s difficult.

Q: To understand the idea that the cycles are staggered – this has the implication that the beta cells and alpha cells are intrinsically expressing a different period, or that they are being re-entrained with each cycle.

A: My feeling is that this is more on the entrainment level; but yes, it has to be better thought out.

Q: Have you thought about testing insulin secretagogues such as SFUs to see whether treating beta cells with these agents leads to different insulin secretion at different times of day?

A: Yes, Dr. Bass has shown that.

Symposium: Novel Experimental and Therapeutic Strategies to Target the Central Nervous System (CNS)-induced Regulation of Metabolism

Multi-agonism Therapeutic Strategies to CNS Regulation of Energy Homeostasis

Brian Finan, PhD (Novo Nordisk, Indianapolis, IN)

While GLP-1/glucagon dual agonists are known to induce greater body weight loss due to reduction in food intake and increase in energy expenditure compared to GLP-1 agonists alone, the benefits of adding additional components to that co-agonist is less clear. Dr. Finan discussed preliminary data regarding the potential of a GLP-1/glucagon/GIP triple agonist, presenting rodent and primate studies that demonstrated superiority of the triple agonist to a GLP-1/glucagon dual agonist in increasing body weight loss while maintaining robust glycemic control. Adding GIP agonism to a GLP-1/glucagon dual agonist introduces anorectic effects and buffers from glucagon-induced hyperglycemia. Dr. Finan further argued that targeting thyroid hormone via GLP-1 powerfully reverses obesity via synergistic central nervous system actions, in a molecular “Trojan horse-like approach.” Though the triple agonist is clearly still in its early stages of development, it’s clear that the triple agonist approach is gaining traction among those in the diabetes field. In particular, Dr. Richard DiMarchi (Indiana University, Indianapolis, IN) is a big proponent of the triple agonist approach involving GIP. The significant interest in multi-agonists involving some combination of GLP-1, glucagon, and GIP was a clear theme of the recent Keystone Symposia on New Therapeutics for Diabetes and Obesity and it appears that the significant potential for weight loss benefits on top of glucose-lowering is a major attraction for this approach.

Questions and Answers

Q: Was thyroid stimulating hormone measured when combining the three agonists?

A: Yes, we measured circulating levels of thyroid stimulating hormone, but we didn’t see any changes there.

Symposium: Genetic Analysis of Gut Flora in Diabetes and Metabolic Diseases

The Human Microbiome

George Weinstock, PhD (The Jackson Laboratory for Genomic Medicine, Farmington, CT)

Dr. George Weinstock spoke on one of the hottest areas of early-stage research in diabetes, the human microbiome. He explained that since its founding in 1998, research funding and publications on the microbiome field have grown exponentially. Characterizing microbial communities (e.g. salivary, gut) by next-generation or shotgun sequencing of 16s rRNA provides rich visual representations of the types of taxa within each body site, all of which are vastly distinct from each other. Stool sample analyses consistently show three microbe divisions: Ruminococcus, Prevotella, and Bacteroides. However, the gut microbiome makeup is extraordinarily sensitive to environmental effects. Mice from different geographical locations can have distinct microbiomes, despite being controlled for genotype and diet – a crucial point for researchers to consider. Dr. Weinstock and Mike Snyder are currently pursuing a Personal “Omics” Profiling (POP) project for people with diabetes. They plan to document genomes, microbiomes, cytokines, and other measures for adults (n=300) with diabetes over three years in order to build integrated profiles that may provide markers for disease progression. Biochemical analyses are also profiling differences in microbiomes within household environments (e.g. dust vs. filter) to further develop the hygiene hypothesis. Scientists hope in the near future to harness microbiomes therapeutically, though that will likely be many years down the road in diabetes. It is particularly encouraging that fecal transplants from healthy individuals to those with C. difficile infections have proved more effective than antibiotic treatments.

  • Dr. Weinstock presented data showing that compared to average healthy subjects, athletes have “golden” microbiomes. A study of downhill bike racers show that Prevotella are significantly more abundant in athletes than otherwise normal people (40% v. <5%), as is Clostridiales. More notably, the main archaebacteria found in humans, Methanobrevibacer smithii, is more abundant in professional racers. One hypothesis suggests that M. smithii metabolizes bacterial waste products, providing nutrients and energy used by athletes’ bodies.
  • One POP subject with prediabetes progressed to diabetes after an RSV infection, which prompted Dr. Weinstock to sequence viral genomes in conjunction with the microbiome. The advent of human rhinovirus, for example, was shown to spike gut Ruminococcaceae and deplete bacteriodetes, which likely affects glucose levels and contributes to diabetes.

Questions and Answers

Q: How are you going about trying to functionalize the role of taxa in promoting health or disease, and how are you trying to distinguish species to the level of granularity needed? For example, E. coli are both pathogenic and non-pathogenic.

A: For bacteria, the action is not at the genus or species level – it’s at the strain level. With shotgun sequencing, we can see everything; we can go down to the SNP level, we can see individual genes. Often, the analysis of shotgun is not at the taxonomical level, but rather at the individual and functional levels. With 16S, you can narrow it down to a species (we’ve done other papers where we look for polymorphisms within 16S genes that hit down to strain level) and look for associations that way.

Q: In the clustering of C57BL/6 mice at Bar Harbor v. West, was there a small group that was from Bar Harbor but had the microbiome equivalent to the JAX West site?

A: There could be some overlap. We didn’t have as many mice from Bar Harbor as we had from JAX West.

Q: If Bar Harbor were to buy a B6 from JAX West and import it, would the microbiome be impacted?

A: First, when a mouse comes to you from Bar Harbor or JAX West, it will change over time. Those experiments in Bar Harbor and JAX were not done at same time in the year. They were all fed the same monkey chow, but could be getting different grain at different parts of the year. Within JAX west, we did eight rooms that fell into two different groups. Groups of four were on different sides of the building and had different microbiomes. The microbiome is an extremely sensitive asset. You pick up things you otherwise didn’t see. How important it is and how to manage it is not clear yet, but it is something we should be officially aware of.

Symposium: Diabetes and Precision Medicine — What Can We Learn about Diabetes with “Omics”?

Microbiomics: Understanding the Role of Nutrition in Vascular and Metabolic Dysfunction

Nathalie Delzenne, PhD (Université Catholique de Louvain, Brussels, Belgium)

Dr. Nathalie Delzenne discussed the role of gut microbiota in metabolic diseases such as diabetes and obesity.  Dysbiosis, the changes that occur in the gut microbiome due to diabetes, leads to a decrease in bacterial diversity and beneficial bacteria and an increase in potentially harmful bacteria.  Therefore, the development of probiotics and prebiotics that target certain gut bacteria is an intriguing area of research in diabetes. Dr. Delzenne presented data showing that more than 100 microbial genes are modified after treatment with prebiotics; these modifications include an increase in bacteria correlated with intestinal L cells in mice, which is thought to be GLP-1 dependent. In addition, metabolic diseases often are associated with omega-3 polyunsaturated fatty acids depletion, which is considered to be linked to the gut microbiome; just three months of depletion in a low fat diet induces hepatic insulin resistance and vascular dysfunction in mic,  and prebiotics improve the metabolic disorders in this context.  Researchers are aiming to modify the gut microbiome to restore vascular function, which may have a positive impact on obesity and type 2 diabetes as well. Although there was plenty of buzz about the gut microbiome at this year’s ADA, much more work is needed to solidify the associations between the microbiome and diabetes and to translate this early-stage research into viable treatments for patients.

Symposium: Microbiota, Inflammation, and Diabetic Cardiovascular Disease

Probiotics and Microbiota Modulation

Max Nieuwdrop, MD, PhD (University of Amsterdam, Netherlands)

A clear theme at ADA 2016 was a surge of interest in the effects of microbiota on diabetes and metabolic disease. Much of the research in this emerging field has been conducted in animals, but Dr. Max Nieuwdrop’s work explores the human microbiome. He and his colleagues transplanted microbiota from lean individuals into individuals with obesity and type 2 diabetes using a procedure called fecal microbial transplantation (FMT). To their surprise, this procedure increased the patients’ insulin sensitivity to a comparable extent as oral diabetes medications, suggesting that microbiota play a role in mediating insulin sensitivity. In future studies, Dr. Nieuwdrop hopes to determine which particular bacterial strains are responsible for these benefits. He foresees that engraftment with beneficial bacterial strains may soon be used in combination with diet, exercise, and drugs as a therapy for diabetes. Although studies like this clearly demonstrate that the microbiome meaningfully influences metabolic health, Dr. Nieuwdrop was quick to point out that science is still a long way from demonstrating a causal relationship between microbes and metabolism. This is a particularly relevant caveat to bear in mind when considering human microbiome studies, which, unlike rodent studies, do not control for age, diet, or genetic background and are thus far less reproducible.

Questions and Answers

Q: Could the success of the engraftment process be modulated by diet? In your fecal transfer experiments did you report HOMA?

A: We studied HOMA and oral glucose tolerance test. We did not see strong effects there; you need large groups or a clamp to pick up a signal. And yes, I believe that diet can improve the chances of engraftment. We are trying that with the Mediterranean diet. Of course, diet would only help the chances of bacterial engraftment if the system is unstable to begin with. A large effect may not be expected.

Q: You talked about the Mediterranean diet having probiotic effects. It is known to be beneficial to cardiovascular health. Could there be some magic bullet in this diet?

A: Yes, we are studying that. We are also studying the vegan microbiome. It is interesting to consider how strong the influence of the microbiome can be on a disease that has been developing for years.

Joint ADA/ASN Symposium—Innovations in Treating Inflammation for Diabetic Kidney Disease

The MCP-1 Inhibition Story for Diabetic Kidney Disease

Hermann Haller, MD (Hannover Medical School, Hannover, Germany)

Dr. Hermann Haller shared exciting preliminary data from a trial of Emapticap pegol (NOX-E36), a novel drug that decreased albumin/creatinine ratio (ACR) by 32% compared to control in patients with diabetic kidney disease. According to Dr. Haller, the drug targets inflammation, as it is strongly implicated in the development and progression of diabetic nephropathy. Researchers specifically zeroed in on MCP-1, a factor that recruits inflammation-inducing monocytes from bone marrow to the kidneys and is found at higher concentrations in the kidney in conjunction with proteinuria and kidney injury. They developed a small, stable left-handed RNA aptamer (a type of molecule known commercially as a Spiegelmer), Emapticap pegol, that selectively binds and neutralizes the function of MCP-1. An initial animal study in db/db mice offered encouraging results, demonstrating a robust reduction in glomerulosclerosis following Emapticap treatment. A subsequent small (n=75) double-blind, 24-week phase IIa clinical trial randomly assigned type 2 diabetes patients with albuminuria (ACR >100mg/g) to either an Emapticap treatment regimen (n=50) or a placebo (n=25). After 12 weeks, the Emapticap group saw a 32% reduction in ACR relative to the placebo group (p=0.014). Notably, this reduction persisted for at least 12 weeks after treatment termination, a phenomenon that Dr. Haller surmised was due to diminished monocytes in the kidneys leading to reduced inflammation and proteinuria.

  • Though theoretically promising, Emapticap pegol requires patients to self-administer sub-cutaneous injections twice daily. This frequency and route of administration may be a barrier to use, and we wonder whether it would lead to sub-optimal regimen adherence. 
  • The placebo group experienced decreases in ACR during the 12-week treatment period that closely mirrored the decreases in the treatment group. To this point, one could argue that the improvements in ACR were solely due to behavioral and/or psychological changes. However, the placebo group returned to baseline ACR after the treatment period, while the experimental group’s ACR was maintained at lower levels at 12 weeks post-treatment.
  • Though not specifically a glycemic control agent, Emapticap reduced patients’ A1c by ~0.5% at the end of the 12-week treatment phase. Dr. Haller explained that MCP-1 has been implicated in insulin resistance, so inhibiting it has the added benefit of decreasing blood glucose and A1c.
  • Dr. Haller was initially concerned about infections and serious adverse events in patients taking Emapticap, but observed none in the phase IIa trial. Monocytes exist to fight infection, he stated, so using this drug “interferes with a system that is in place for a reason.” However, inhibiting the recruitment of monocytes to the kidney did not result in a greater risk of infection.

Questions and Answers

Q: We need to work on the biomarker side of the equation. Do you think that phenotyping MCP-1 would be sufficient, or do you think other biomarkers should be in such a panel?

A:  I think we should first focus on MCP-1, because there may well be differences amongst healthy and unhealthy individuals in this gene.

Q: If you were designing the next clinical trial, at what point do you think it would be the right time to introduce anti-MCP-1 therapy?

A: We have to rely on albuminuria for the time being. Traditionally, no albuminuria means no kidney disease, but we know this isn’t always the case. The question is, can we define more phenotypic metrics? I’m a big proponent of biopsies, we need to do more of these to diagnose diabetic kidney disease.

Pathway to Stop Diabetes Symposium

Summary

A high-powered group of researchers and industry representatives gathered in a closed session on Friday morning to hear presentations from the most recent recipients of the ADA’s Pathway to Stop Diabetes grants. Introductory remarks by ADA President Dr. Des Schatz and Dr. C. Ronald Kahn (Joslin Diabetes Center, Boston, MA) emphasized the program’s goals of promoting long-term, transformational change in diabetes care and encouraging collaboration. They also highlighted the selectiveness of the program: the 17 grant recipients selected thus far were chosen from a pool of 330 applicants, and as Dr. Kahn put it, “those 330 people were all pretty damn good.” The introductory speakers also noted that there was a concerted effort to focus attention on this program at this year’s ADA, with a dedicated poster session on Sunday and an oral presentation session on Monday in addition to this symposium. We remain very impressed with the Pathway initiative, which awards grants of up to $1.6 million over five to seven years to young diabetes researchers working on innovative projects focused on everything from neuronal regulation of feeding behavior to impaired wound healing. The program is supported by several heavy hitters in the diabetes industry, including Sanofi, Novo Nordisk, AstraZeneca, and Lilly, and we imagine this could make it easier for the researchers to eventually translate their findings into novel therapies. We think this program can play a major role in shaping the next generation of KOLs in diabetes. We also hope it can promote a more diverse group of leaders compared to the current crop (in a sign of some progress, 35% of the Pathway grant recipients are women compared to 26% of the mentors). See below for a more detailed overview of their work, though we unfortunately cannot provide specifics on the data presented at the symposium due to the closed nature of the session.

  • Dr. Praveen Sethupathy (University of North Carolina, Chapel Hill, NC) is exploring links between obesity and the gut microbiome. His research aims to identify genetic factors that contribute to the intestine’s response to microbes under normal conditions and in obesity and diabetes. Due to the intestine’s crucial role in metabolism, Dr. Sethupathy is optimistic that this research could eventually reveal targets for future therapies.
  • Dr. Zachary Knight (UCSF, San Francisco, CA) is investigating neuronal circuits that regulate food intake. While the field has a basic understanding of the mechanisms of weight regulation by the brain, Dr. Knight aims to delve deeper into the specific circuits that allow external cues to override normal regulation of feeding behavior. His research is focused on identifying the signals that activate the sensation of hunger and understanding how neural circuits promote food consumption. His goal is then to discover how these circuits are dysregulated in obesity, hopefully opening the door for new therapies.   
  • Dr. Philip White (Duke University, Durham, NC) is using metabolomics to better understand the biochemical signatures of diabetes and obesity. As compared to lean mice, the metabolome of obese mice is characterized by a disequilibrium in levels of enzymes involved in the breakdown of keto-acids in the liver. Dr. White hypothesizes that restoring homeostasis among these enzymes could be an effective strategy for improving glucose and lipid metabolism.
  • Dr. Andrew Scharenberg (Seattle Children’s Hospital, Seattle, WA) is using gene editing to engineer stable regulatory T cells (Tregs) in patients with type 1 diabetes. There is evidence suggesting that Treg dysfunction is one element of the immune imbalance in type 1 diabetes that leads to autoimmune attack on the beta cells. Dr. Scharenberg aims to edit genes in T cells to engineer Tregs that will remain stable and protect beta cells from autoimmune attack, potentially preventing or reversing type 1 diabetes. Dr. Jeffrey Bluestone (UCSF, San Francisco, CA) is currently furthest along in the Treg field with a therapy in phase 1 trials, but this approach (while at a much earlier stage) could potentially produce even more stable and robust cells with greater efficacy.
  • Dr. Sui Wang (Harvard University, Boston, MA) is developing biological tools to dissect the gene regulatory networks (GRNs) mediating diabetic retinopathy. Dr. Wang is interested in understanding the unique roles of different retinal cell types, with particular emphasis on the molecular events underlying the disease’s early pathogenesis. She hopes that an understanding of these complex forces will leave researchers well-positioned to identify potential therapeutic targets to arrest the progression of retinopathy in its early stages.
  • Dr. Daniel Ceradini (New York University, New York, NY) is investigating whether restoring a key antioxidant pathway can reverse the impaired tissue regeneration associated with diabetes. His research has previously demonstrated that this pathway is disrupted by hypoglycemia, and he aims to develop a therapy that can restore it and enable faster wound healing in people with diabetes. Wound healing is an area of particularly great unmet need in diabetes – the current standard of care consists of glycemic control and pressure off-loading – and we are very glad to see efforts to develop novel therapies.

Type 1 Diabetes Cure Therapies and Pathophysiology

Oral Presentations: Transplantation – Basic

Tissue Engineering of An Intra-Abdominal Endocrine Pancreas Using a Biologic Scaffold

David Baidal, MD (University of Miami, FL)

Dr. David Baidal discussed results from a study investigating the safety and efficacy of islet transplantation in the omentum of a 43-year-old woman with type 1 diabetes complicated by severe hypoglycemia and hypoglycemia unawareness. According to Dr. Baidal, the omentum is an appealing transplantation site due to its vascular supply, portal vein drainage, anti-inflammatory properties, and accessibility by minimally invasive surgery. The transplantation process involved a total of 602,395 islet equivalents from a single donor, which were combined with plasma from the recipient and applied gently to the omentum surface via a laparoscopic approach.  Next, recombinant thrombin and additional plasma were layered over the islets to create a 3D biologic scaffold that adhered to the omentum, which was then folded over the scaffold. Seventeen days after the operation, the patient displayed full insulin independence. At 75 days after transplant, fasting and stimulated C-peptide 90 minutes after a mixed meal tolerance test were 0.80 and 2.8 ng/mL, respectively. Notably, mean glucose measured by CGM was an incredible 99±17 mg/dl; A1c dropped to 5.6%; and euglycemia remained at six months follow-up with resolution of hypoglycemia. The patient has required immunosuppression with anti-thymocyte globulin, etanercept, tacrolimus, and mycophenolate sodium since the time of her surgery. Overall, islet transplantation into the omentum was well tolerated and resulted in insulin independence; Dr. Baidal expressed hope that the “biodegradable scaffold” platform technology may allow for future elimination of systemic immunosuppression, a key step in enabling long-term transplantation success.

Oral Presentations: Mechanistic Insights into Genetic Risk for Diabetes

Enhanced Early Proliferation of Beta-cells Prevents Progression of Type 1 Diabetes

Ercument Dirice, PhD (Joslin Diabetes Center, Boston, Massachusetts)

Dr. Ercument Dirice discussed the results of several studies in mice to explore whether enhanced beta cell proliferation early in life can prevent progression of type 1 diabetes. To do this, a liver-specific insulin knockout (LIRKO) mouse, which is characterized by enhanced beta cell proliferation, was crossed onto the non-obese diabetic (NOD) model. NOD control mice developed diabetes and died at about 20 weeks of age, whereas over 95% of the NOD-LIRKO mice survived with normoglycemia for two years. Dr. Dirice described further studies of the NOD-LIRKO phenotype, which showed that these mice have hyperplastic islets, increased beta cell mitosis and decreased beta cell apoptosis. The mice also showed a significant increase in regulatory T cells (p=0.008), which prevented the progression of type 1 diabetes. Dr. Dirice concluded that this research serves as new evidence that enhanced beta cell proliferation early in life alters the identity of beta cells and increases T cell counts, which prevent the progression of type 1 diabetes.

Questions and Answers

Q: I wonder whether the genetic manipulation might also lead to changes early in development or tolerance early in development that protects the beta cells? Have you looked at that?

A: No, we did not check that, but it is something that we want to do.

Oral Presentations: Update on Cell Sources for Beta-Cell Replacement

Pig Iglet Xenotransplantation

David Cooper, PhD (Thomas E. Starzl Transplantation Institute, Pittsburgh, PA)

Dr. David Cooper explained that for the 1.5 million patients with type 1 diabetes awaiting islet transplants each year, allotransplantation (transplantation of cells/organs from a human donor) is incredibly unlikely, primarily due to the shortage of donor islets. This shortage has spurred research across the globe to genetically engineer animal organs, particularly pig islet cells, for xenotransplantation. Current research focuses largely on eliminating barriers including immunologic responses, physiological differences, and safety hazards. Dr. Cooper’s team, in collaboration with biotech company Revivcor, is working on genetically engineering organs from donor pigs to eliminate potential rejection by transplant recipients. He presented research demonstrating that islet transplantation from pigs, both adult and neonatal, eliminated insulin dependence for more than six months in nonhuman primate models in seven research groups across the world. Anticoagulation agents (e.g. heparin), anti-complement agents, and immunosuppression therapy were used to combat the likelihood of rejection. Safety hazards were minimized by keeping pigs in biosecure housing and testing for ‘clean’ islets in culture. Combined, these techniques and precautions have enabled graft survival for longer than 12 months after xenotransplantation. While we believe the development of renewable sources of islet cells is a more sustainable solution to the current islet cell shortage, this approach could represent a valuable interim option if it is validated in clinical trials.

  • One solution that significantly delays organ rejection is engineering a transgenic pig for human complement-regulatory proteins (e.g. CD55) to provide protection from human complement-mediated injury. Another solution is to remove the Gal gene from the islet-source pig, which eliminates attack of pig galactose antigens by primate antibodies.
  • Islet xenotransplantation can be conducted either with or without immunosuppression.  Encapsulated islet transplantation is aimed toward protecting the islets from immune injury without the need for immunosuppressive therapy, but is not entirely successful and also results in poor nutrition of the islets. A clinical trial in New Zealand has been carried out using encapsulated islets from wild-type pigs. Graft survival was limited. Free islet transplantation requires immunosuppressive therapy, but has been more successful. Research groups are continually working to knock-out further pig antigens to minimize the primate immune responses. 

Symposium: ADA Pathway To Stop Diabetes Symposium

Autoreactive CD4 T Cells Target Hybrid Insulin Peptides in Type 1 Diabetes

Thomas Delong, PhD (University of Colorado, Aurora, Colorado)

Dr. Thomas Delong elaborated on the autoimmune pathogenesis of type 1 diabetes based on the results of a 2016 study of T cells from non-obese diabetic (NOD) mice as well from two human patients. He provided the background that previous research implicated the CD4 T cell response as a key component of beta cell destruction, but these findings lacked more depth of information on the specific proteins that elicit the autoimmune response. In a series of antigenic studies, Dr. Delong’s team identified a library of hybrid insulin peptide (HIP) sequences recognized by NOD mouse CD4 T cells. Beta cells secrete HIPs as a byproduct of protein synthesis and degradation, so to translate these findings to human patients, Dr. Delong’s team identified similar candidate HIPs using CD4 T cells isolated from pancreatic islets of two patients with type 1 diabetes. In particular, HIPs formed by a fusion of proinsulin C-peptide to neuropeptide Y elicited a significant immunogenic response as compared to control media (p<0.05). The link between HIP secretion and T cell autoimmunity thus leads to a more definitive explanation for the mechanism of beta cell destruction, and provides an intriguing explanation for the pathogenesis of type 1 diabetes as well as other autoimmune disorders.

Symposium: Immunobiology of Type 2 Diabetes

Dendritic Cells, Inflammation, and Diabetes

Kristin Tarbell, PhD (National Institutes of Health, Bethesda, MD)

Dr. Kristin Tarbell discussed two innate immune pathways that may play important roles in the pathogenesis of inflammation associated with diabetes and obesity: (i) the type 1 interferon pathway, which is the body’s main anti-viral response and can induce tissue damage if there is interference; and (ii) the interleukin-I pathway, an antibacterial response induced by lipopolysaccharides that includes cells such as monocytes and macrophages.  Dendritic cells help balance immunogenic and regulatory signals in all phases of type 1 diabetes pathogenesis, and researchers hypothesize that antigen-specific immunotherapy will require signals that block chronic autoimmune inflammation.  Dr. Tarbell focused on the type 1 interferon signal and found that non-obese diabetic (NOD) mice make more type 1 interferon but display a blunted TLR9/IFNαR response.  Lower induction of CD86 after TLR9 stimulation was observed in the spleen and peripheral/pancreatic lymph nodes.  NOD mice also have reduced STAT1 activation, which may impair IFN-dependent tolerogenic pathways such as the indoleamine 2,3-dioxygenase (IDO) pathway.  These insights could potentially lead to new drug targets for type 1 diabetes immune therapies, though this research is of course at a very early stage.

Symposium: Genetic Analysis of Gut Flora in Diabetes and Metabolic Disease

The Environmental Determinants of Diabetes in the Young (TEDDY) Project

Joseph Petrosino, PhD (Baylor College of Medicine, Houston, TX)

Dr. Joseph Petrosino introduced the TEDDY project and highlighted some of its major findings. He opened by stressing that there are many known and hypothesized contributing factors toward type 1 diabetes, such as risk factors and environmental exposures. According to Dr. Petrosino, the goal of the TEDDY project is to identify those environmental factors and study the immune-pathogenesis of those factors across diverse populations in order to establish a “central repository of data and biological samples.” The project recruited 8,500 neonates from various clinics in the US and Europe and followed them for 15 years, documenting early childhood diet, cases of infection, vaccinations, and many other factors, with the goal of identifying possible candidates that may trigger type 1 diabetes and to associate various microbiome changes with disease progression. Dr. Petrosino showed that the study found that there are significant differences in species abundance between islet autoimmunity cases and controls in the metagenomics data, but no significant associations between specific taxa and outcomes. He thus noted that the working hypothesis is that islet autoimmunity is associated with the failure to reach and maintain intestinal microbiome maturity. As the microbiome remains extremely complex, we see these findings as a first step in attempting to find a link but the field hasn’t quite reached a point where it can identify specific players in the microbiome.

Symposium: Issues Facing Clinical Beta Cell Replacement – Now and Later (Supported by a grant from the Leona M. and Harry B. Helmsley Charitable Trust)

Islet Autotransplantation After Pancreatectomy for Chronic Pancreatitis – Mixed Blessings

R. Paul Robertson, MD (University of Washington, Seattle, WA)

Dr. R. Paul Robertson discussed a fascinating implementation of treating chronic pancreatitis with total pancreatectomy followed by intrahepatic islet transplant to the liver (TPIAT), with the overall goal of reducing patient pain. He shared that he feels strongly about this treatment solution, due to its alleviation of pain, which he saw as the main issue driving poor quality of life in these patients. Dr. Robertson presented the results post-TPIT operation outcomes, which included normally timed insulin secretion from islet beta cells. However, a down side was the significant amount of time spent in hypoglycemia (15% time with glucose <70 mg/dL), and defective alpha cell glucagon secretion (likely the cause of the time spent in hypoglycemia). From these findings, he suggested that one way to counteract the hypoglycemia is to implant the islets at the liver but also in an additional site so that glycogenolysis is not prevented by local intrahepatic insulin secretion. Ultimately, because pancreatitis can eventually cause diabetes, Dr. Robertson concluded very passionately that clinicians should not wait to consider the treatment of patients with chronic pancreatitis by TPIAT.

Why Are So Few Islet Transplants Currently Being Done for Type 1 Diabetes?

Camillo Ricordi, MD (University of Miami, Florida)

Dr. Camillo Ricordi outlined the major challenges and barriers to islet transplantation in patients with type 1 diabetes. First, clinical islet transplantation procedures are reimbursed poorly and the cost, especially in the US, is enormous: about $235,000 per transplant. On this note, Dr. Ricordi emphasized the skyrocketing R&D costs and lengthy drug development cycles, sharing that he would rather encourage prioritizing investment in cures over better treatment options. Second, Dr. Ricordi identified systemic chronic immunosuppression as a major barrier to accessibility for patients with type 1 diabetes. Moving to a more promising note, he highlighted recent good news from his institution: on June 9, a 41-year-old man became the first type 1 diabetes patient in Europe to discontinue insulin therapy following an islet cell transplant using a new tissue engineering technique, successfully developed by Dr. Ricordi’s team at the Diabetes Research Institute (see the presentation by Dr. Baidal). Dr. Ricordi expressed hope that this novel tissue engineering technology will allow for more research in technologies that prevent the use of anti-rejection, which currently limit the applicability of the procedure to the most severe cases of type 1 diabetes. Dr. Ricordi concluded his presentation with possible solutions to the barriers on the path to developing cures. He emphasized that cellular products and cell-based therapies should be regulated differently than drugs, that accelerated pathways should exist for therapies in pilot trials that do not impose safety concerns for the general population, and that public-private-partnerships are necessary to reduce R&D costs.

Symposium: More than a Gut Instinct – Potential of the Microbiome from Pregnancy through the Life Cycle

The Early Microbiome and Risk for Development of Type 1 Diabetes

Mark Atkinson, MD (University of Florida, Gainesville, FL)

Dr. Mark Atkinson focused on the implications of the microbiome in type 1 diabetes, especially in children. He reviewed major findings from the TEDDY study and presented the hypothesis that probiotic supplementation increases diversity of the microbiome in young, high-risk patients, which then reduces their risk of developing islet autoimmunity. According to Dr. Atkinson, diversity of microbiota is largely considered a good sign of health, and pediatric patients who develop type 1 diabetes often lack this diversity. A major obstacle for microbiome research in disease-specific populations is that the human microbiome shows tremendous variability across the board. Still, Dr. Atkinson explained that the microbiome is an attractive area of research for those interested in type 1 diabetes because it ties together many of the disparate environmental agents that have been associated with increasing type 1 diabetes prevalence.

Questions and Answers

Q: Have studies found the microbiome to be associated with one specific autoantibody, like insulin, or with any autoantibody?

A: It could be any, although the first autoantibody to present is often the one for insulin.

Q: There was a recent paper comparing children in Estonia and Finland which found that loss of bacteria early on is implicated in glucose intolerance.

A: Yes, these studies are having an important impact, because we want to stress that type 1 diabetes is probably dependent on more than autoimmunity. There are other factors – beta cell development, pancreas development, pancreas size, and perhaps the microbiome.

Q: Is it possible that these bacteria are making antigens contributing to the autoimmune response?

A: From the mid-1960s until the 1980s, that was the dominant thought on how autoimmunity developed, not just for type 1 diabetes but for many diseases. It was the molecular mimicry hypothesis – the thought that peptides secreted by bacteria resemble something foreign and elicit an autoimmune response. Unfortunately, that hasn’t held up well for type 1 diabetes, though the notion keeps getting resurrected every few years.

Symposium: Genetic Analysis of Gut Flora in Diabetes and Metabolic Diseases

Gut Microbiota and Type 1 Diabetes

Aleksandar D. Kostic, PhD (Broad Institute of MIT and Harvard, Cambridge, MA)

Dr. Kostic shared evidence from several studies supporting the hypothesis that gut microbiota are rheostats of inflammation that can detect and predict type 1 diabetes incidence prior to diagnosis. A study on non-obese diabetic (NOD) mice showed that knockout of the MYD88 gene, thought to decrease immune response to symbiotic microbiota, decreased incidence of diabetes. In the DIABIMMUNE Consortium study, monthly stool samples were collected from HLA-risk-adjusted Finnish infants (n=400) from birth until four individuals were diagnosed with type 1 diabetes. Longitudinal analysis showed that alpha diversity, essentially the number of unique microbial species in the gut, dropped steeply one year before diagnosis for all four children. The next study delved into Finland and Russian Karelia, adjacent regions of the world. Habits of food storage and hygiene are relatively more developed in the former compared to the latter, which Dr. Kostic suggested likely influenced the six-fold higher rate of diabetes in Finnish children. A three-year study of Finnish, Estonian, and Russian children (n=74 each) controlled for HLA-risk showed higher serum antibody levels in Finnish/Estonian than Russian infants. Distinct phylum-level bacterial profiles showed that within the first year of life, significantly more gram-positive Actinobacteria were present in Russian microbiomes and more gram-negative Bacteroidetes in Finnish/Estonian ones. Notably, microbial lipopolysaccharide (LPS) acyl chains were different between the cohorts, which holds major implications on TLR-4 activation. Also Bacteroidetes dorei LPS was shown to inhibit TLR4 activation by E. coli LPS, a crucial species in the gut microbiome, at a 100:1 ratio in Finnish microbiomes. Lastly, B. dorei and E. coli LPS were injected weekly NOD mice, after which the E. coli LPS showed significantly protective qualities against T1D.

  • In the DIABIMMUNE study, pro-inflammatory taxonomies (e.g. Ruminococcus gnavus) spiked prior to T1D arrival, and fatty acid producers responsible for T cell induction (e.g. Lachnospiraceae) decreased. Microbe-associated stool lipids in the children with diabetes also showed strong associations – lithocholic acid, which actives intestinal epithelial cells, was positively correlated with T1D while sphingomyelin, an anti-inflammation agent, showed anti-correlation.
  • For the first, there is evidence showing that members of the gut microbiota have strong immune-modulatory effects on TLR4. In vitro human monocyte stimulation of both E. coli and B. dorei with LPS as a follow-up to the Finnish and Russian infant study showed high levels of activation in E. coli and virtually none in B. dorei, which indicates functional differences in microbiome species. Furthermore, stimulation of macrophages with E. coli and B. dorei LPS showed strong differences in TNF-α activation.
  • The gut microbiome is emerging as an increasingly important focus of study across multiple disease areas, including type 1 and type 2 diabetes and obesity. ADA Chief Medical Offer Dr. Robert Ratner has previously hypothesized that the rise of C-section births are altering the gut microbiome compositions of many children at birth, which may be contributing to the rising incidence of type 1 diabetes. At this point, little is definitely known about the impact of the microbiome and we’re likely many years of research away from any sort of therapeutic intervention for diabetes or obesity based on the gut microbiome. We were certainly glad to see recognition of this need for research into the microbiome at the federal level with the launch of the White House’s National Microbiome Initiative (NMI).

Questions and Answers

Q: Can you draw two cohorts together? It looks like for the Estonian kids, earlier microbial species may provide education of immune cells, leading to inflammatory response. In the first cohort, everything looks normal until diverges after a year. This draws the question back to what is in cohort 1 that might be effective in priming and might be something seeing. For example, C-sections and breastfeeding could be co-founders.

A: We tried to control for confounders – C-section and breastfeeding were pretty similar between the cohorts. The sample consisted of only four individuals, so there is not a strong effect. Also, the first cohort was entirely Finnish. If we compare the microbiomes early on, they are generally more pro-inflammatory compared to the Russian cohort.

Symposium: Joint ADA/EASD Symposium - Beta-Cell Heterogeneity - Are Some Cells More Equal than Others?

Beta-Cell Surface Molecules Reveal Different Subpopulations

Philip R Streeter, PhD (Oregon Health & Science University, Portland, Oregon)

Dr. Philip Streeter presented a thorough review of his work to develop and characterize monoclonal antibodies for cell surface molecules in order to isolate and study beta-cell subsets. He explained that normal human beta cells have a consistent distribution of subset markers and that beta cell populations can be defined by sequential surface antibody labeling. In contrast, type 2 diabetes beta cells are variable, often with high expression of the cell subsets ST8SIA 1, CD9 or both, suggesting that individuals with type 2 diabetes have very different pathologies that need to be explored further. Dr. Streeter concluded that human beta cells are in fact antigenically heterogeneous and that beta cell subtypes are not a culture artifact. Additionally, it appears that a small set of genes that are differentially expressed in beta cell subsets affect insulin release kinetics to control release of insulin in response to glucose.  Dr. Streeter finished his talk by calling for more research to better understand the abnormal beta cell subtype distribution in type 2 diabetes and for more research in type 1 beta cells. We’ve heard from luminaries such as Dr. Robert Ratner that diabetes – both type 1 and type 2 – is a beta cell defect at its heart and Dr. Streeter’s research further supports the view that there is something fundamentally different about beta cells within the context of diabetes.

Symposium: Update on Cell Sources for Beta-Cell Replacement

Beta-Cell Replacement in Type 1 Diabetes – Consideration in Design of Clinical Trials

Bruce Schneider, MD (FDA, Silver Spring, MD)

Dr. Bruce Schneider outlined FDA recommendations on clinical trial design for beta-cell replacement therapies and discussed strategies to improve trial design. Of the four types of cell sources (allogeneic, hESC-derived, porcine, and genetically modified [e.g. iPSC] cells), Dr. Schneider focused on allogeneic islets for having abundant preliminary clinical safety and effectiveness data. For phase 3 trials of allogeneic islets, FDA guidelines acknowledge that randomized controlled trials are not feasible and find that single arm trials may be able to provide evidence of effectiveness if the response rate is based on achievement of insulin independence (or the composite of A1c≤6.5% and absence of severe hypoglycemic events) and the trial is adequately sized to rule out a response rate of less than 50%. While many promising beta-cell replacement therapies are still a while away from phase 3 trials, we’re glad to see the FDA has thought about this and proactively implemented guidelines. We hope clearer guidelines on the regulatory process for this area of study may encourage more biotech and pharmaceutical companies to invest in the development of such therapies though we are not holding our individual or collective breath.

  • Dr. Schneider suggested that the traditional landmark analysis based on a single endpoint may not provide an accurate estimate of the treatment effect. Researchers can consider trial designs that measure overall time spent in a beneficial state (e.g. creating a composite endpoint combining time while insulin independent with a state where A1c≤6.5% without hypoglycemia instead of a single endpoint for severe hypoglycemia events). These trials may provide greater insight into the short- and long-term benefits of allogeneic islet implants and Dr. Schneider remarked optimistically on the ability of new technology to capture more detailed patient data from these small trials.

Symposium: Protecting the Beta Cell

Encapsulation

Girish Chitnis, PhD (Harvard Medical School, Boston, MA)

Dr. Girish Chitnes presented the overall biological engineering progress that has been made in encapsulation of islet cells as a potential treatment for people with type 1 diabetes. In his eyes, the vast benefit of utilizing the encapsulation method during an islet transplant is that is provides immunoprotection to the islet cells, therefore eliminating the requirement for immunosuppressant drugs. He reviewed the key components of the capsule structure that allow it to serve its function including: a semipermeable cell containment barrier (for nutrition input and therapeutic output); surface vascularization (to stimulate communication with the host); and a single layer islet arrangement (to maximize surface area and therefore nutrition exposure of each islet cell). Dr. Chitnes noted that the prime challenge of this method is that currently, the encapsulation devices hold too few islet cells, as it would take up to as many as fifty encapsulation devices to hold the three million islet cells required for treatment functionality. According to Dr. Chitnes, this work is ongoing with prototypes being tested in vivo with the vision of developing a more compact functional encapsulation device for islet transplants to treat people with type 1 diabetes.

Human Leukocyte Antigen Matching/Immunosuppression

Bashoo Naziruddin, PhD (Baylor University, Waco, TX)

Dr. Bashoo Naziruddin discussed the evolving role of how human leukocyte antigen matching plays into the pathogenesis of type 1 diabetes and how immunosuppression can affect transplantations in this context. He shared that while pancreatic islet transplantation is an effective and minimally invasive procedure to attain normoglycemia in some individuals with type 1 diabetes in the first year post-transplant, the islet graft tends to deteriorate over the long term. Although the exact mechanism of islet graft rejection is unclear, human leukocyte antigen (HLA) mismatching appears to play an important role in the development of an alloimmune response. Dr. Naziruddin explained that the HLA system encodes the major histocompatibility complex (MHC) in humans, which is responsible for regulation of the immune system. According to him, allogenic islet transplantations are often performed via multiple infusions, which exposes the islet transplant recipient to a high number of HLAs. Immunosuppression can decrease HLA sensitization, resulting in more effective transplantations. Looking to the data, Dr. Naziruddin compared the results of several small studies evaluating different modes of immunosuppression, including the Edmonton Protocol, anti-CD3 based immunosuppression, calcineurin inhibitor-free immunosuppression, and anti-inflammatory treatment. Of these, anti-inflammatory treatment was found to be most effective in safely improving islet engraftment and function, though larger and more long-term studies will be needed.

Next-Generation Islet Grafts

Jose Oberholzer, MD (University of Illinois, Chicago, IL)

Dr. Jose Oberholzer illustrated the needs, benefits, and challenges of next-generation islet grafts in today’s type 1 diabetes islet graft environment. He opened by stressing that  individuals with type 1 diabetes who receive current generation islet grafts can experience satisfactory glycemic control for many years following transplantation. Dr. Oberholzer shared that there is also considerable debate into the benefits and risks of immunosuppression in graft recipients, and showed encouraging long term studies showing a reduction in overall cardiovascular risk in patients with functional islet transplant despite the immunosuppression. While some individual have passed the 10 year mark of being insulin independent after single donor islet transplants, there still remain many challenges in making islet grafts beneficial for all people with type 1 diabetes. As the number of human organs suitable and available for transplantation is small, there have been serious efforts underway to investigate stem-cell derived islet cells, islet cells originating from pigs and other animals, and non-endocrine cells of the pancreas, as well as making isolated human islet cell grow. The latter can be achieved by viral delivery of cell cycle gene, but the use of viruses harbors risks to the future recipients of such bioengineered islet cell sources. However on the bright side, modified gold nanoparticle vectors have been recently developed as a biocompatible intracellular delivery system for pancreatic islet cell transplantation, which have proven to be nontoxic while still penetrating islets completely. Finally, once islet cells are delivered, long-term islet function can only be achieved by forming a capsule surface around the islet cells that is permanently free of fibrosis to ensure free oxygen, nutrition, and insulin diffusion. According to Dr. Oberholzer, researchers at MIT have developped microencapsulation techniques that provide a drug-free bioengineering approach for beta cell protection that could potentially be clinically applied. However, all of these methods still need to be further researched and tested in non-human primates before being implemented in human trials.

Scaffolding

Lonnie Shea, PhD (University of Michigan, Ann Arbor, Michigan)

Dr. Lonnie Shea discussed the potential of scaffolding as a powerful option for islet transplants. He noted the promise of this strategy, as it targets extrahepatic delivery, which contrasts with the currently islet transplantation approach used clinically and is often associated with complications such as steatosis, lipotoxicity, inflammation and low oxygen tension. The transplantation of islets on scaffolds has allowed for efficient engraftment of transplanted islets, and the scaffold can be manipulated to deliver factors that enhance engraftment. Dr. Shea noted that scaffolding, however, comes with its own set of challenges. Specifically, the scaffold for islet transplants is not immunoprotective, so patients are required to take immunosuppressant drugs. Alternatively, scaffolds can be modulated to locally protect the islets by modulating the innate and/or adaptive immune responses through strategies such as TGF beta delivery, and co-transplantation of regulatory T cells. This approach is currently being investigated in large animal models as a precursor to initiating human trials.

Symposium: What is the Future of Immunotherapy for Type 1 Diabetes?

IL-2 Immunotherapy

Thomas Malek, PhD (University of Miami, Miami, FL)

Dr. Thomas Malek reviewed progress made in the field to restore immune tolerance in autoimmunity with low-dose interleukin (IL)-2. He explained that low-dose IL-2 therapy increases the number of regulatory T cells in most individuals. As background, regulatory T cells modulate the immune system and prevent autoimmune disease, as they can down-regulate induction and proliferation of effector (i.e., helper) T cells. According to Dr Malek, in mouse models, low-dose IL-2 was found to safely prevent and reverse type 1 diabetes with no evidence of enhancing self-reactive effector T cells. A preliminary study of 24 individuals with type 1 diabetes demonstrated that low-dose IL-2 therapy (typically 0.3-3 x 106 IU daily subcutaneously for five days) did not result in serious adverse events or deleterious changes in glucose metabolism at 60 days of follow-up. Although Tregs increased in all patients receiving low-dose IL-2, some evidence was also presented suggesting that the response to IL-2 varied is some individuals. These findings suggest that personalizing this therapy may eventually be helpful to identify individuals most responsive to this type of immunotherapy. Looking forward, Dr. Malek noted that there is an ongoing phase 2 trial by Dr. David Klatzmann (Pierre and Marie Curie University, Paris, France) that is testing the clinical benefit of low-dose IL-2 for individuals with type 1 diabetes, which we hope provides a greater look into the mechanisms of action of this approach in the human model.

Overview of Prevention/Reversal Trials in Type 1 Diabetes

Jay Skyler, MD (University of Miami, FL)

In this presentation, Dr. Jay Skyler reviewed what has and hasn’t worked in the prevention and reversal of type 1 diabetes and provided his take on the field’s next steps and challenges. Dr. Skyler first opened with a discussion on the thoughts around immunological mediation and beta cell destruction and function, noting the wide variety of interventions that all target different mechanisms to stop immune destruction (i.e. GAD vaccine, anti-CD20, etc.). Examining the field’s research, Dr. Skyler highlighted that many efforts have proved successful in the NOD mouse model, but very rarely in humans, as he reviewed various approaches (i.e. antigen-based studies, immune-modulatory new onset studies, etc.) and how many of these have shown transient or no effects in humans. Turning to approaches that have shown some success, he highlighted studies involving cyclophosphamide, an ATG/GCSF combo, and a filgrastim/exenatide combo. Looking forward, Dr. Skyler stressed that one of our key challenges is to identify factors that will predict specific patients’ potential responses to particular interventions. Specifically, he touched on the differences in age seen in model-based estimates of average slopes of AUC C-peptide as well as how various blood and islet phenotypes indicate immunological heterogeneity in type 1 diabetes. Additionally, Dr. Skyler stressed the need for a combination therapy approach in this space, as he highlighted the potential of combining agents involved in anti-inflammation, immunomodulation, and beta cell preservation.

Questions and Answers

Q: On combination approaches, what do you think in decision on whether or not to include an antigen?

A: With my experience at the FDA and TrialNet, when we propose taking five drugs, people say the FDA will never allow it. So we like to pick five drugs that are already approved, and four already combined together. All of these have had testing in type 1 already. I wouldn’t want to include a non-approved drug because then that creates more confusion in the regulatory process. Ideally, I’d choose it but I’d choose a path easier for regulators.

Q: The FDA has a guidance on combination therapy where none of the components are meant to be marketed individually. What’s needed to facilitate more combo therapy in immunosuppression for type 1 diabetes? What would you like to see from ADA, JDRF, and NIH?

A: The FDA has been quite cooperative in thinking about this and in looking at animal models of combinations. If you have a good rationale for something and you put it together, I think you can make a case for regulators. Depending on how strong you make your case, regulators can be more flexible. There was a study of Tregs in 12-17 year-olds. And one would not think about starting in that group but it happened so they’re wiling to think about doing things in new manners. I hope people on the drug side will get that view as well.

Comment: It’s disappointing that for decades now, we haven’t really made much progress. We have to get rid of the NOD mouse model for preclinical testing because we need a solid preclinical model to transfer the best approaches to the human situation and not just on the NOD mouse. When you use the right models, you will be able to distinguish and identify very few combinations.

A: People should use more than just the NOD model, but I’m not quite ready to throw the NOD model down the river yet.

Comment: The NOD mouse model is a PhD-friendly model. It’s nice for PhD students to feel like they see something positive. But it’s disappointing for patients and for us. And it costs a huge amount of money.

Repurposing Imatinib for Type 1 Diabetes

Stephen Gitelman, MD (UCSF, San Francisco, CA)

Dr. Stephen Gitelman discussed the rationale, hypothesized mechanisms of action, clinical observations, and current clinical trial of (GleeT1D) imatinib, an approved cancer drug, as immunotherapy for people with type 1 diabetes. He shared that Imatinib or Gleevec is a tyrosine kinase inhibitor (TKI) and standard chronic myeloid leukemia treatment drug and affects various arms of the immune system including pathways of both the innate and acquired immune systems.  According to Dr. Gitelman, there have been multiple pre-clinical studies along with several cases of anecdotal evidence in which Imatinib has demonstrated positive results as a treatment for type 1 diabetes. In particular, he noted that there have been cases in humans, in which patients with both cancer and type 1 diabetes were treated with Imatinib and consequently required lower insulin doses. With this background, Dr. Gitelman shared his design for the ongoing clinical trial titled GleeT1D, a phase 2, randomized, double-blind, placebo-controlled, multicenter study studying the safety and efficacy of Imatinib therapy in adults with type 1 diabetes. According to Dr. Gitelman, the study will treat 66 newly diagnosed adults ages 18 to 45 with either 400mg of Imatinib or placebo for 6 months with the primary outcome measurement of c-peptide levels to mark for endogenous insulin secretion, with results expected in the summer of 2017. We love the idea of looking to cancer as an area of innovation for diabetes, as cancer has built itself a strong evidence base and has comparatively greater resources and expertise to pull from.

Questions and Answers

Q: In the NOD mouse models, was there still a diabetic immune system after short term treatment?

A: Approximately half of the mice that have been treated for 10 weeks remain in lasting remission when Imatinib is withdrawn.  We suspect that the reason is multi-factorial, including a reduction of endoplasmic reticulum stress and preservation of beta cells; reduced trafficking of T-cells to islets; and improved insulin sensitivity.  There may be additional effects on arms of the immune system, which are being further evaluated.

Q: Given the fact that you can block various tyrosine kinases, from an oncology perspective, is there a mechanistic biomarker to assess what kinases are inhibited? Will this treatment block the Tcells’ effect of dendritic cells?

A: We have attempted to pinpoint if there is a single tyrosine kinase that must be blocked, but have concluded from analysis to date that it is probably targeting of at least several that results in the positive effects seen in the NOD mouse.  Further studies are also underway to determine what arms of the immune system are affected by this therapy.

Closing the Loop and Insulin Delivery

Posters

Pivotal Trial of a Hybrid Closed-Loop System in Type 1 Diabetes (99-LB)

R Bergenstal, B Buckingham, S Garg, S Weinzimer, R Brazg, J Ilany, B Bode, T Bailey, S Anderson, R Slover, J Shin, S Lee, F Kaufman

Medtronic presented a late-breaking poster on its single-arm, non-randomized, three-month pivotal study of the MiniMed 670G/Enlite 3 hybrid closed loop system in 124 participants (n=94 adults, 30 adolescents). The topline data compared to a two-week open-loop run-in period was excellent: (i) a solid 0.5% reduction in A1c from a low baseline (7.4%); time <70 mg/dl declined 44% (6% to 3%); and time <50 mg/dl declined 40% (1% to 0.6%). Nice! – it was impressive to see the impact on A1c, given the strong reduction in hypoglycemia and the very well-controlled population of pumpers. Notably, those with a baseline A1c >7.5% actually saw a 1% reduction after three months on the 670G. Time-in-range (71-180 mg/dl) improved from 67% during the baseline run-in to 72% during the study, with time >180 declining moderately (27% to 25%). While that improvement does not sound significant, it is clear from the compelling glucose profiles (see below) that the MiniMed 670G made extreme highs (e.g., 300 mg/dl) more moderate (e.g., 200 mg/dl), which didn’t show up as improvement in time in 70-180 mg/dl. The profiles are really worth looking at – they show how the MiniMed 670G tightened the range of glucose values throughout the entire day in both populations, with particularly strong efficacy overnight. Total daily dose increased ~7% from baseline (48 u to 51 u; p<0.001), though a smaller proportion of insulin was given as basal insulin (we unpack this below). Both adolescents and adults gained a bit of weight on the MiniMed 670G: +3 lbs (1.4 kg) in adults and +2 lbs (1.0 kg) in adolescents. While weight gain is never a positive, this does not strike us as big concern for the 670G or other hybrid closed loop systems, given potential for less hypoglycemia-induced weight gain. Hybrid closed loop was used for an impressive 87% of the three-month study period (median), with slightly higher usage in adults (88%) than adolescents (76%). The new Enlite 3 sensor showed a solid improvement, with an overall MARD of 10.3% vs. reference (i-STAT) over a 24-hour measurement period (part of the study’s six-day hotel phase). This was consistent with data shown at ATTD, though only 2% of points were in hypoglycemia.

  • Overall, we see these pivotal data as very encouraging for the entire field of automated insulin delivery. This study was clearly designed for speed and to prove safety to the FDA, so it’s hard to read too much into the efficacy results, where were not pre-specified endpoints. Still, reducing A1c 0.5% at the same time hypoglycemia declined 44% is a huge win – and the results were consistent in adolescents and adults. This was also a very real-world study in current pump users, some of whom were on CGM prior to study start. It’s clear that automated insulin delivery will make a difference even with first-gen hybrid closed loop products, and even in well-controlled patients. Of course, the hope is it can really improve outcomes for those with an A1c >10% or at high risk of severe hypoglycemia, groups that were both excluded from this study.
  • In talking to investigators, the patient reactions they’ve heard have been even more impactful than the data. Said Dr. Rich Bergenstal, “This is a definite step forward. Beyond what the numbers say, the true benefit is in the stories of sleeping at night, peace of mind. I’m happy to get a little help from technology.” With an FDA submission planned before the end of this month, and 80% of pivotal study patients using this device as part of the FDA’s continued access program, we assume many of the other pump companies are nervous about these results. Of course, that will push all of them to move faster and differentiate their offerings.

RESULTS

  • The MiniMed 670G drove a strong 0.5% reduction in A1c from a low baseline (7.4%; p<0.001), including a 1% A1c reduction in patients with a baseline A1c >7.5%. Those with a baseline A1c of 7.0-7.5% saw a 0.3% reduction in A1c, while those with an A1c under 7% saw a 0.1% reduction in A1c. By the end of the study, 55% of trial participants had an A1c <7%, up from 31% at baseline.
    • The A1c improvement was consistent and highly significant across adults and adolescents: -0.5% in adults (baseline: 7.3%) and -0.6% in adolescents (baseline: 7.7%). Both were highly significant with p<0.001.
    • It is notable to see the impact on A1c, given the 44% reduction in hypoglycemia (see below) and the well-controlled population. We’re especially glad to see a strong 1% improvement in those with an A1c >7.5%, which brings hope this will be even more effective in those with an A1c >10% (who were excluded from the study).

 

Baseline
(open loop: pump+CGM)

Study Phase
(hybrid closed loop)

Change

P-value

A1c – All

7.4%

6.9%

-0.5%

p<0.001

A1c - Adults

7.3%

6.8%

-0.5%

p<0.001

A1c - Adolescents

7.7%

7.1%

-0.6%

p<0.001

 

A1c Change if Baseline <7.0%

-0.1%

A1c Change if Baseline 7.0%-7.5%

-0.3%

A1c Change if Baseline >7.5%

-1.0%

  • The MiniMed 670G tightened the range of glucose values throughout the entire day, particularly overnight. The modal day plots below show the median and interquartile range of sensor glucose values throughout the day and night in all patients (Panel A), adults (Panel B) and adolescents (Panel C). The gray band and dotted line shows the run-in phase, while the pink band and solid line show the study phase.
    • Consistent with pre-pivotal trials, the MiniMed 670G is most impactful overnight, driving patients down to ~140 mg/dl by early morning, tightening the range of overnight values, and eliminating hypoglycemia.
    • These modal plots really capture how much hybrid closed loop can make a difference at all times of day, even if it still requires manual boluses. Of course, systems are only going to get better with subsequent generations and faster insulin, and hybrid closed loop is a valuable first step.

Figure A: Modal Day – All Patients 

Figure B: Modal Day – Adults

  • The 670G narrowed the range of glucose values in well-controlled adults, though was slightly more conservative than open-loop therapy during the day. Note in the below that the black average line at most daytime points is higher than the dotted average line. This makes sense given the well controlled, early adopter study population and first-gen hybrid closed loop. Future generation products with more aggressive algorithms and faster insulins should drive further improvement during the day.

Figure C: Adolescents

  • The 670G showed excellent efficacy in the tough adolescent population, improving hyper glycemia at all times of day, particularly extreme highs after breakfast and moderate highs in the evening. Average glucose levels were fairly consistent, with perhaps a slight edge to the 670G.

  • Time-in-range (% of SG in 71-180 mg/dl) improved from 67% during the baseline run-in to 72% during the study, with time <70 mg/dl nearly halved (6% to 3%), time <50 mg/dl declining 40% (1% to 0.6%), and time >180 improving moderately (27% to 25%). All had p<0.001, and the improvements were pretty consistent between adults and adolescents. [Exceptions: adults saw more benefit on time <50 mg/dl, while adolescents saw more improvement in time >180 mg/dl.]
    • While the improvement in time-in-range does not sound significant, there are several critical factors to consider: (i) the reduction in hypoglycemia is very meaningful; (ii) patients were doing quite well during the run-in (67% in range); and (iii) based on the glucose profiles below, the MiniMed 670G clearly made extreme highs (e.g., 300 mg/dl) more moderate (e.g., 200 mg/dl), which didn’t show an improvement in time in 70-180 mg/dl, but still improved overall glycemia (see profiles below). The latter also explains why A1c improved at the same time hypoglycemia declined (which should raise A1c) and time >180 mg/dl didn’t change significantly.

 

Run-in
(open loop: pump+CGM)

Study Phase
(hybrid closed loop)

P-value

% of SG* <50 mg/dl

1.0%

0.6%

p<0.001

% of SG <70 mg/dl

5.9%

3.3%

p<0.001

% of SG 71-180 mg/dl

66.7%

72.2%

p<0.001

% of SG >180 mg/dl

27.4%

24.5%

p<0.001

Within Day SD of SG

50 mg/dl

47 mg/dl

p<0.001

* SG= Sensor Glucose

  • The MiniMed 670G increased total daily dose ~7% from baseline (48 u to 51 u; p<0.001), though a smaller proportion of insulin was given as basal insulin. Since the MiniMed 670G only automates basal insulin delivery, the implication is patients were taking more manual boluses on hybrid closed loop (either in number or larger in size). Were they eating more or differently while on hybrid closed loop? If so, this could also explain the slight weight gain (see below)? The increase in insulin dose does not seem clinically significant, and many other studies have shown less or the same amount of insulin given.

 

Baseline
(open loop: pump+CGM)

Study Phase
(Hybrid closed loop)

P-value

Total Daily Dose

47.5 u

50.9 u

p<0.001

% as Basal Insulin

53%

47%

p<0.001

  • Both adolescents and adults gained a bit of weight on the MiniMed 670G: +3 lbs (1.4 kg) in adults and +2 lbs (1.0 kg) in adolescents. Oddly, these were both higher than the average weight gain for the overall study population reported on the poster (+1.5 lbs / 0.7 kg), so we’ve broken them out separately – we’re not sure what’s happening there but are following up with Medtronic.
    • While weight gain is never a positive, this does not strike us as a major concern for the 670G or other hybrid closed loop systems. We would not be surprised if further analyses reveal different eating behaviors while on hybrid closed loop. Keeping patients out of hypoglycemia could also help them lose weight, so the weight piece seems a bit difficult to interpret at this stage.

 

Baseline
(open loop: pump+CGM)

Study Phase
(hybrid closed loop)

Change

P-value

Weight - Adults

79.9 kg

81.3 kg

+1.4 kg

p<0.001

Weight – Adolescents

67.4 kg

68.4 kg

+1.0 kg

p<0.001

  • Hybrid closed loop was used for an impressive 87% of the three-month study period (median), with slightly higher usage in adults (88%) than adolescents (76%). This was not further specified, but we see this usage as encouraging in a well-controlled population. Plus, >80% of pivotal study participants have continued using the system through the FDA’s continued access program, a good sign the benefits are worth it from a patient perspective. 

ENLITE ACCURACY

  • The new Enlite 3 sensor showed a solid improvement, demonstrating an overall MARD of 10.3% vs. reference (i-STAT) over a 24-hour measurement period (part of the six-day hotel phase). There were very few points in hypoglycemia (2%) and hyperglycemia (25%), making it hard to compare this accuracy with other sensors. Still, the results are pretty consistent with what we’ve seen for Enlite 3 in other studies, including 11% in the pre-pivotal study presented at ATTD. Larger and more robust studies of Enlite 3, presented in four poster abstracts here at ADA 2016 (879-P, 897-P, 901-P, 916-P), suggest a similar ~10% MARD.
    • Medtronic still recommends 3-4 daily calibrations for Enlite 3, though the poster did not specify how many occurred in this study. We’re also not sure on what day of the sensor life this 24-hour CGM-reference accuracy comparison occurred.

Reference Glucose Range

Mean Absolute Relative Difference (MARD)

Percentage of Points in Range

Overall

10.3%

-

>180 mg/dl

11%

25%

71-180 mg/dl

9.8%

73%

<70 mg/dl

12 mg/dl*

2%

STUDY STRENGTHS AND LIMITATIONS

Strengths

Limitations

Multicenter design to evaluate safety (10 sites)

Large number of subjects, both adults and adolescents, using the system for 24 hours per day

Three months of unsupervised home use of system

Time in target confirmed by reference blood glucose measurements during hotel stay

Single-arm, non-randomized design with no pre-specified efficacy endpoints

Data quantity imbalance between run-in (two weeks) and study phases (three months)

Exclusion of subjects with A1c >10%, recent episodes of severe hypoglycemia or recent DKA

STUDY BACKGROUND AND POPULATION

  • This single-arm, non-randomized study enrolled pump users (≥6 months), with or without current use of CGM. Participants had to have type 1 diabetes for ≥2 years, an A1c <10%, and age 14-21 years old (adolescents) or 22-75 years old (adults).
    • Adolescent participants (n=30) had a mean age of 17 years, mean A1c of 7.7%, a mean BMI of 24 kg/m2, and a total daily dose of 0.8 u/kg/day. The study enrolled 16 adolescents females and 14 adolescent males.
    • Adult participants (n=94) had a mean age of 45 years, mean A1c of 7.3%, a mean BMI of 27 kg/m2, and a total daily dose of 0.6 u/kg/day. The study enrolled 53 adult females and 41 adult males.
  • The MiniMed 670G/Enlite 3 was used in open-loop mode (with CGM) during a two-week run-in phase (baseline), then in closed-loop mode in a three-month study phase (unsupervised). The three-month phase included a six-day, five-night hotel stay for supervised activity and frequent venous blood glucose measurements (during one 24 hour period) with a reference instrument (i-STAT). This study was conducted at 10 sites in the US and Israel. 
  • The 670G hybrid closed loop algorithm (ePID) automatically increases or decreases basal insulin, but all boluses require user input and confirmation (i.e., meal and correction boluses). Though not noted on the poster, here’s what we know about the algorithm: it targets 120 mg/dl, which can be raised to 150 mg/dl during exercise; it has a max limit on insulin delivery per hour and uses basal modulation to keep blood glucose in range (i.e., a hybrid closed loop that still requires meal boluses, and it cannot just correct a 350 mg/dl in one big correction bolus); it gives a new dose every five minutes; the 670G uses open-loop parameters to initialize hybrid closed loop (total daily insulin, basal, insulin:carb, insulin sensitivity factor); at the start of hybrid closed loop, there is a sensor accuracy check, along with a glycemic target adjustment for a smooth transition to closed-loop; the algorithm can adapt over time as things change; the 670G will revert to open loop if the sensor is inaccurate; and it will switch to safe mode or the pre-programmed basal rate in cases like sensor failure.
    • It’s worth noting that a missed meal bolus on the 670G hybrid closed loop could still mean several hours above range, as the higher basal rate will take a while to bring blood glucose back in zone. Still, the system is clearly much better than most patients are doing right now, and the hybrid closed loop is a great way to go until insulin gets faster and algorithms get even smarter.

POST 670-G UPDATE

  • Medtronic’s post-670G product will further close the loop by performing automatic correction boluses based on CGM values. Medtronic’s dinner during ADA suggested it will enter a clinical study this month (June) and be called the MiniMed 690G. This product will integrate the DreaMed MD-Logic algorithm to close the loop further – instead of only increasing basal insulin to gradually mitigate highs (670G) and bring blood glucose back to target, the next-gen algorithm will add automatic bolusing to correct highs. That should improve time-in-range much more and make the system more aggressive with missed meal boluses. The pre-ADA Analyst Meeting showed a picture of a smaller, touchscreen-looking, future-gen pump platform, but we’ve confirmed with Medtronic that is not the 690G.

Real-World Use of Open Source Artificial Pancreas Systems (104-LB)

D Lewis, S Leibrand, and the #OpenAPS Community

This illuminating poster presented self-reported outcomes from 18 out of the first 40 users of OpenAPS, the DIY automated insulin delivery system created by Ben West, Dana Lewis, and Scott Leibrand (now over 150,000 hours of AID use outside any clinical trial setting!). While using OpenAPS, self-reported outcome measures showed median A1c dropped from 7.1% to 6.2%, an impressive 0.9% reduction in a well-controlled and motivated population. Self-reported median percent time-in-range (80-180 mg/dl) increased from 58% to 81% - consistent with presentations of actual data we’ve seen recently from Mark Wilson (Day #1) and Chris Hanneman (D-Data last fall). Fourteen out of 15 respondents reported some improvement in sleep quality, and 56% reported a large improvement. Respondents were “extremely satisfied with the “life changing” improvements associated with using an APS,” even if they “require significant effort to build and maintain” and “cannot be considered a technological cure.” The poster notes that OpenAPS is designed to be, and has been, far safer than standard pump/CGM therapy, as measured by duration of hypoglycemia and hyperglycemia, with no reports of severe hypoglycemia or hyperglycemic events. The OpenAPS design considerations posted here are pretty instructive on the safety front (only temp basals, no automatic correction boluses, etc. – much like the 670G hybrid closed loop!). Our takeaways from this poster and inspiring community are: (i) automated insulin delivery can make a huge difference, even for well-controlled patients; (ii) even though the system is burdensome to set up and wear, patients would not do it and use it unless the benefits were worthwhile; (iii) lots of learning is occurring in the OpenAPS community that could be leveraged for commercial systems; (iv) OpenAPS could push the FDA and industry to move faster, and that is a good thing; and (v) the relative risks here seem low, given the setup burden, the solid design for safety, and real-world dangers of insulin therapy. 

  • As an aside, and as would be expected, patient researchers – like any other researchers – buy badges to present posters. That is part of supporting ADA in bringing together so many researchers for discussion. However, patient-researchers do not have funding from work environments like manufacturers or universities. This creates a wonderful opportunity for a foundation or other organization to endow funds to create a pathway for patient researchers to not lose savings to present their data. We hope patient research will increasingly be supported by the existing healthcare community, since greater dialogue can be particularly beneficial. We are eager to see more patient learning make its way into professional organizations, such as Dr. Joyce Lee’s commentary from “Digital Health: Hope or Hype?” and we hope that can change. We salute Dana and Scott for submitting this poster and getting it accepted as a late-breaker and we look to the field to come up with creative solutions to support this work.
  • OpenAPS now has over 80 users worldwide, though only 40 were using the system at the time of abstract submission, which makes this 18-person evaluation a near 50% response rate. Of course, as with any other research, the self-reported component of the outcomes may be interpreted cautiously.
  • The poster has an instructive discussion section, noting that some healthcare providers are supportive of OpenAPS, and others showed a “lack of interest.” However, OpenAPS experiences “are instructive for what patients can expect from commercial APS when they become widely available, and can help HCPs be prepared to set patients’ expectations properly when discussing or recommending APS.”  We totally agree and hope to see more dialogue between the traditional healthcare community and the OpenAPS community. 
  • The poster’s questions for HCPs to consider are also fascinating:
    • Artificial pancreas systems are already here. One of your patients may already be building one. Would you know it if they are? Do you discuss with your patients which tools they choose to use to help manage their diabetes?
    • APS are a powerful tool, but not a cure. Patients and HCPs will still need to do a lot of work to use them effectively to improve diabetes management.
    • Patients and HCPs must educate themselves and each other on how APS can be used effectively in daily life.
  • Though OpenAPS has improved in wearability and form factor, it still requires carrying extra gear, as accessing pump commands remains difficult. The community has posted all the reference design, documentation, code, and community channels at www.openAPS.org, though this system requires a fair amount of effort and motivation to put together – hence why we don’t see it as high risk right now. In the process of building it, users must intimately understand how it works, and it is certainly not plug and play. We know smart people using the system now that spent hundreds of hours setting it up.

Patient User Experience Evaluation of Bolus Patch Insulin Delivery System (995-P)

V Zraick, D Dreon, R Naik, D Shearer, S Crawford, J Bradford, and B Levy

This poster presented solid data demonstrating that patients (n=44; 40 with type 2, four with type 1) were very pleased with J&J’s OneTouch Via (formerly Calibra’s Finesse), a “discreet, wearable, on-demand, mealtime insulin delivery solution.” Over 50% of the cohort completed product training within a half hour – a strong testament to the usability of the bolus-only, three-day wear device. Following the eight-week trial, 86% of users reported being extremely/very satisfied with the system, and 79% were extremely/very likely to request a prescription from their HCP. Similarly, 74% of patients said that they would incorporate the Via into their routine. There was an interesting learning curve that emerged in the data: After week one, patients reported that they dosed with the Via the same number of times that they typically would with their pen/syringe. By the midway and end points of the study, patients had adjusted to the device, and >50% reported injecting prandial and snack-time insulin more frequently than they had with their pens/syringes. Of course, because information about dosing frequency was self-reported, it’s hard to know how dosing actually changed. We will be curious to see the results of the ongoing OneTouch Via outcomes study (n=312), which has a primary completion date set for this December. J&J reported at its Medical Device Business Review last month that it will file OneTouch Via for approval in 2H16, and we’ve learned from the company that it will be commercially available in select market outside the US by late 4Q16, with US to follow soon thereafter in early 2017 – this is an update from the Medical Device Business review, which called for a launch within the next 12 months (by May 2017).

  • HCPs were also big fans of the OneTouch Via! Every single one was satisfied at the end of the eight-week usage period and was likely to recommend. A large majority also viewed the Via favorably when compared with syringes and pens.
  • This simple device has the potential to improve regimen adherence. With the Via, the majority of users in this study reported satisfaction with their abilities to (i) discreetly and easily administer a bolus in public without painful injections, (ii) worry less about the possibility of forgetting pens/syringes, and above all, (iii) lead less stressful lives. Thus the Via overcomes many barriers to usage associated with MDI.

Glucommander Outpatient, a Cloud-based Insulin Management Solution Adjusted Insulin Doses and Achieved 2.7% Drop in A1c Percentage Points (84-LB)

John G. Clarke, Bruce W. Bode

A Glytec poster (84-LB) showcased very impressive results from a 41-patient, uncontrolled, 3-month, outpatient study testing its Glucommander insulin dosing clinical decision support software – from a high baseline A1c of 10.3%, patients ended three months with an estimated average A1c of 7.6% (p<0.000001). The study enrolled 41 type 1 and type 2 patients (mean age: 38 years, BMI: 32 kg/m2) at Dr. Bruce Bode’s clinic in Atlanta, who were treated for 12 weeks with Glucommander Outpatient. The cloud-based software provided periodic insulin dose titration recommendations to a provider based on analysis of a patient’s SMBG glucose data, communicated wirelessly via the cellular-enabled Telcare meter. The provider then communicated the new insulin doses to patients via text message or email. The topline findings from this small study are very impressive – patients using Glucommander saw a 2.7% reduction in A1c (baseline: 10.3%) at three months, and only 1.6% of blood glucose values were <70 mg/dl. Strikingly, no values were <40 mg/dl and, on the human factors side, patients satisfaction results indicated that 96% of patients would recommend the service to family and friends. The poster hinted at Glytec’s strong long-term data as well, citing a smaller cohort of patients that have continued on Glucommander for six (n=14) and nine (n=5) months and have maintained this 2.7% reduction. Small cohorts, but still, this is a whopping improvement. The outcomes are encouraging given the challenges of titrating insulin and the potential for this software to scale expertise, though larger prospective randomized clinical trials are needed to confirm these positive early findings from an uncontrolled study. The company does plan to begin a larger study that includes cost-related metrics such as readmissions, emergency room visits, medication adherence, and healthcare provider productivity, and we’re hopeful that data will show this kind of clinical decision support is very warranted (a “no-brainer” many say). We’re not sure what the business model looks like going forward, but assume Glytec’s in-hospital experience will be very valuable as it thinks about going outpatient. As a reminder, Glucommander Outpatient is already FDA-cleared and is in the process of being deployed across the US. See our previous in-depth coverage here.

  • How could the Glucommander software be scaled? Could it be packaged with existing devices or even drugs? We’ve long thought that insulin-dose titration is a missing piece in the diabetes data ecosystem, and this early data shows how much can be done (and parallels what Hygieia has shown in Europe). We wonder how this Clinical Decision Support software could be packaged with existing devices or even drugs on the market to enhance their effectiveness in the hands of providers. We also have to assume this product saved tremendous provider time, and we look forward to seeing larger studies showing cost-effectiveness. This is where we see digital health really driving better outcomes: collecting data seamlessly and making valuable recommendations that drive seriously better outcomes with less effort.

Do Type 1 Diabetes Patients Really Want An Artificial Pancreas? (1005-P)

S Franc, I Xhaard, L Orlando, M El Makni, M-H Petit, C Randazzo, and G Charpentier

This poster investigated real-world attitudes about closed-loop systems, asking 101 patients with type 1 diabetes to fill out an artificial pancreas questionnaire before and after a presentation about what such a system entails. The informational forum increased the number of patients expressing a desire to use automated insulin delivery – from 40% to 67% – though we were far more surprised by what the questionnaire revealed about the confusion around “artificial pancreas” terminology. Before the session, 42% of patients thought that an artificial pancreas involved an organ graft and 18% thought it was a smartphone app; these numbers changed to 16% and 68%, respectively, following the informational forum, though we’re still a bit shocked that many patients maintained these perspectives following the session [It does makes us wonder about how rigorous and engaging this training was, and how hard automated insulin delivery is to explain.] The session was more successful, however, at convincing patients that the artificial pancreas will be safe and beneficial: the percentage of patients reporting that they would be “extremely likely” to wear an artificial pancreas if it were available grew from 24% before the forum to 41% after it. Overall, it’s tough to read too far into the results considering how little is known about how these questions were asked, how the informational session was conducted, and who these patients were – however, the findings do hint at a general lack of knowledge about these devices and at the need for more rigorous educational efforts to counter misperceptions about what an artificial pancreas actually is.

  • The poster reported that the recency of diagnosis (p=0.014), the existing use of pumps vs. MDI (p=0.058), and the willingness to use a smartphone to manage the device (p=0.038) were all positive predictors of desire to use an artificial pancreas. However, a number of other factors were not positively correlated: (i) dissatisfaction with current therapy; (ii) hope of improved HbA1c levels, decreased risk of hypoglycemia, or associated complications; (iii) hope of improved freedom or comfort; and (iv) the length of time needed to develop the device.
  • Given that pump use positively predicts desire to use the artificial pancreas, we wonder whether this study may have overestimated the number of patients that would be accepting of such a device. Notably, 67% of patients who filled out the survey reported that they use an insulin pump. In a cohort that is more representative of the global MDI vs. pump distribution, we wonder whether fewer subjects would have expressed interest in an artificial pancreas.
  • The artificial pancreas will make insulin therapy safer, increase time-in-range, and could improve burden, but patients certainly will not accept it if they do not understand it. We came away from this study reminded that for the product to make the impact we hope it will, the field needs a much more coordinated education effort to teach patients and providers how an artificial pancreas works and how it could benefit them.

Barriers to Device Uptake in Adults with Type 1 Diabetes (914-P)

M Tanenbaum, S Hanes, K Miller, D Naranjo, and K Hood

This study invited 1,503 adult patients (mean age=35 years) in the T1D Exchange to take a 30-minute web-based survey in order to understand barriers to insulin pump and CGM uptake. Coming into the survey, 32% of patients reported using both a pump and CGM, while 5% used just a CGM, 38% used just a pump, and 25% used neither. Unsurprisingly, a majority of patients cited financial burden as the biggest barrier to the use of either device – 60% of patients expressed concern about insurance coverage, the cost of the device, and the cost of supplies. Other popular barriers appeared far more modifiable: 35% did not like having diabetes devices on their bodies, 47% did not like the hassle of having to wear the device all of the time, 26% did not like how the diabetes devices looked on their bodies, and 20% were nervous that the device might not work. The survey also asked patients who had discontinued use of their devices for their rationale – patients reported abandoning CGM because of too many alarms, inaccurate data, a distaste for the device on their body, time requirements, or discomfort, while a majority of patients discontinued use of pumps because they didn’t like the device on their bodies or because the device was uncomfortable. We wonder how attrition breaks down by manufacturer. Younger adults (18-25 years old) were less likely to use devices than older adults, and this younger population had higher levels of diabetes distress and higher A1cs. Overall, findings suggest that cost remains the biggest barrier to address, but size on the body is not far behind. We wonder if many of the CGM quitters were on earlier systems that were less accurate (e.g., Seven Plus), and perhaps they would be less frustrated with the more accurate out now or coming soon. Of course, with self-reported data, there is always some question about the reliability of results, though the data echo much of what we hear about the real-world barriers to device uptake anecdotally.

  • We’d note that CGM users in this study were five times more likely to be on a pump (38% used pump+CGM vs. 5% used MDI+CGM), echoing what Dexcom has long said – patients are more likely to be prescribed a CGM if they are already on a pump. We hope the positive results from Dexcom’s DIaMonD study can change that (see Drs. Howard Wolpert and Elena Toschi’s talks elsewhere in this report).
  • The survey also compared the differences between CGM users and non-users. CGM users were, on average, five years older than non-users (38 years vs. 33 years; p <0.001), viewed technology more favorably, and had significantly lower A1cs (7.3% vs. 7.7%; p =0.003).

Closed-Loop Control Reduces Hypoglycemia during Extended Winter-Sport Exercise in Youth with T1D: The AP Ski Camp (103-LB)

Daniel R. Chernavvsky, Mark Deboer, Jessica Robic, Boris P. Kovatchev, Marc D. Breton

This poster shared findings from an RCT that investigated the efficacy and durability of UVA’s DiAs closed-loop system (n=8) vs. SAP therapy (n=8) in 16 adolescents with type 1 diabetes at a five-day ski camp (five hours of skiing/day!). The intense physical activities – compounded by altitude (~1,300 meters) and cold weather (-10 degrees Celsius) – brought a higher risk of hypoglycemia and a super challenging setting for testing closed loop. Overall, findings were consistent with the group’s previous impressive results and indicated that patients on closed-loop therapy experienced far tighter glycemic control than those on SAP – overall time spent <70 mg/dl decreased from 4.1% (SAP) to 1.6% (CL) (p=0.008) and nocturnal time spent <70 mg/dl decreased from 3.6% (SAP) to 1.6% (CL). Consistent with these findings, the incidence of overnight hypoglycemia treatments were cut roughly in half on closed-loop control (2.6 treatments/subject/day vs. 5.3 treatments/subject/day (p=0.04). There were no AP-related adverse events and patient evaluations of the system and study were reportedly overwhelmingly positive. Ultimately, the results confirm that UVA’s closed-loop system performs reliably and safely in cold temperatures, reducing hypoglycemia during and after intense prolonged exercise. The UVA’s system’s daytime target is 160 mg/dl, which makes it a bit conservative for tightly controlled patients, but excellent at mitigating lows. Bigger picture, we loved the very real-world nature of this study, and as systems get closer to commercialization, we’d love to see additional groups test their closed-loop systems in similarly rigorous environments in even larger populations. These “edge cases” will inform patients’ experience with closed-loop systems, and it’s crucial (for safety and peace of mind) that products are robust to the toughest real-world challenges: sensor offline, sensor inaccurate, incorrect fingerstick calibration, kinked or occluded infusion set, denatured insulin, water, high heat, etc.

Oral Presentations: Closing the Loop on Insulin Management – Are We There Yet?

Automated Artificial Pancreas System in Type 2 Diabetes in the General Ward: A Randomised, Controlled, Parallel-Design Study (84-OR)

Hood Thabit, MD (University of Cambridge, UK)

Dr. Hood Thabit presented brand new, exciting data from the Cambridge team’s automated insulin delivery system in inpatient type 2 diabetes – the first of this kind of closed-loop study ever done. The study shared striking improvements in efficacy and safety vs. the truly grim standard of care achieved with open-loop in the hospital. The parallel-arm study randomized 24 patients to receive either closed-loop therapy (n=12) or conventional subcutaneous insulin therapy per clinical guidelines with masked CGM (n=12) for a period of 72 hours. The data looked outstanding and terrifying at the same time – closed-loop control significantly improved time-in-target from 38% to 61% for the 100-180 mg/dl range (p<0.001). Mean glucose improved from 182 mg/dl to 161 mg/dl (p=0.065), though that signal was not significant. The study used unannounced meals, which made control much harder in the closed-loop arm. There was absolutely no difference in hypoglycemia in this type 2 population: time spent < 63 mg/dl = 0% [CL] vs. 0% [OL]. On safety, there were no severe hypoglycemia or adverse events associated with diabetes therapy and total daily insulin did not differ between the groups (63 units per day [CL] vs. 66 units per day [OL]). Ultimately, we were not sure what to expect coming into this oral, but the group’s impressive track record certainly delivered in another new setting. Ultimately, we left the presentation reminded yet again of the very negative state of current inpatient glucose management. Indeed, we were downright disheartened by the standard of care overnight (mean glucose = 202 mg/dl; see below), and the findings served as a striking reminder of: (i) the need for glucose management education in the hospital setting; and (ii) the great potential for inpatient technology to improve diabetes management and resulting outcomes. The tendency to accept hyperglycemia in inpatients is truly wrong.

  • We were particularly impressed with data overnight Dr. Thabit shared – see Table 1 below. Closed-loop control doubled nocturnal time-in-target from 29% to 59% for the 100-180 mg/dl range (p<0.001), while mean glucose improved from 202 mg/dl to 161 mg/dl (p=0.065) with no hypoglycemia. There were zero episodes of glucose < 63 mg/dl on closed-loop vs. isolated incidents on open loop, making the hypoglycemia difference significant overnight too. We imagine nurses and other hospital-based HCPs would appreciate the chance to safely reduce blood glucose – many are very scared from what we know to have patients at “normal” blood glucose levels, given the risk (real or perceived) of hypoglycemia. Many inpatients likely run “high” against their wishes.
  • This trial did NOT use meal announcements, making this the first fully automated closed-loop Cambridge study. All the type 1 studies have used meal announcements, but Dr. Thabit stressed that a fully automated system is particularly practical in the inpatient type 2 setting where patients and nurses are less well educated – more on this below.
  • Dr. Thabit shared very positive user experience data from type 2 patients on the closed-loop system. According to Dr. Thabit, a majority of these patients had never been on a device previously, making these glowingly positive results all the more impressive.
    • Were you happy with your glucose levels in the hospital during the study?
      • Better than expected: 17 patients.
      • What you expected: 3 patients.
      • Worse than expected: 0 patients.
    • Were you happy to have your glucose levels controlled automatically by the system?
      • Better than expected: 18 patients.
      • What you expected: 1 patient.
      • Worse than expected: 1 patient.
    • If a friend or family member was in the hospital, would you recommend this system to them?
      • Yes: 19 patients.
      • No: 1 patient.
    • Would you be willing to wear a portable version of this system as part of your diabetes treatment at home?
      • Yes: 17 patients.
      • No: 3 patients.

Questions and Answers

Q: This is a very important study. Thank you. On the first day when sensors were not as accurate, did you wait any period of time before starting closed loop?

A: We did not wait. Once the sensor was put in and one hour warm-up period elapsed, closed loop went online.

Q: In the closed-loop group, how did you decide how much Lantus to use?

A: Our decision to give 20% Lantus was a pragmatic one after chatting with clinical colleagues abut what would avoid ketosis.

Dr. Hans DeVries (Academic Medical Center, Netherlands): I believe this is the first study from Cambridge when meals were not announced. Can you talk about the rationale behind that?

A: The decision to go with a fully closed-loop system was pragmatic because we expect this will be used this way in the real world. The last thing we want is for nurses or patients to miss a meal announcement. Our hypothesis was that in the type 2 diabetes population in the hospital, a fully closed-loop system is needed because patients and nurses are not as well educated.

Q: What was the patient perception like?

A: We got a very positive endorsement from patients. Many patients had never worn devices in their lives and live had a very good experience.

Similar Estimated A1c Results Reported between Patients with Diabetes Using CGM whether on Multiple Daily Injection (MDI) or Continuous Subcutaneous Insulin Infusion (CSII) (81-OR)

David Price, MD (Dexcom, San Diego, CA)

Dexcom’s Dr. David Price shared a retrospective database evaluation from six months of G4 Share users, showing no differences in mean glucose, estimated A1c, or glucose variability between pump (n=939) or MDI (n=648) users. The de-identified data on glucose values were supplemented by customer info (age, insulin delivery) that Dexcom collects. The pump and MDI groups had identical average glucose values and variability across every age group (from 2-6 year-olds all the way to 65+ year olds), with just a single small exception: glucose variability was statistically significantly lower in adolescents (13-18 years) using injections. As would be expected, adult CGM users had better average glucose values vs. pediatric CGM users by ~30 mg/dl (see tables below estimated from the charts shown). This analysis also aligns with results from the T1D Exchange showing that in every age group, the same pattern holds – similar A1cs for CGM users on MDI or a pump. Dr. Price noted that CGM use is increasing (now up to 16% in the T1D Exchange), but is overwhelmingly prescribed to pumpers: of all Exchange CGM users, 85% are on pumps vs. just 15% on MDI. Studies like this also underscore the inherent value in data streaming from devices to the cloud automatically – companies can use it to put data behind their arguments, drive study design, and inform marketing. Medtronic has written the book on this with CareLink, and we expect Dexcom will begin driving this too. 

All Pediatrics 2-18 years

 

MDI
(n=300)

Pump
(n=301)

P-value

Mean CGM Glucose

~180 mg/dl

~180 mg/dl

0.92

Estimated A1c

~7.9%

~7.9%

--

Standard Deviation

~65 mg/dl

~60 mg/dl

0.39

~ Estimated from Bar Graphs

Adults >18 years

 

MDI
(n=403)

Pump
(n=369)

P-value

Mean CGM Glucose

~158 mg/dl

~159 mg/dl

0.55

Estimated A1c

~7.1%

~7.1%

--

Standard Deviation

~57 mg/dl

~59 mg/dl

<0.23

~ Estimated from Bar Graphs

Home Use of a Bihormonal Bionic Pancreas vs. Conventional Insulin Pump Therapy in Adults with Type 1 Diabetes—A Multicenter, Randomized Clinical Trial (77-oR)

Ed Damiano, PhD (CEO, Beta Bionics / Boston University, Boston, MA)

Beta Bionics’ CEO Dr. Ed Damiano revealed that Zealand’s phase 2 liquid stable glucagon analog will be tested in the 4Q16 bridging study of the fully integrated iLet Bionic Pancreas. The pivotal studies are still expected to start in 2Q17, and the bihormonal pivotal will last 12 months to gain chronic glucagon exposure data. Zealand actually put out a press release announcing the collaboration with Beta Bionics, a big win for Dr. Damiano’s new public benefit corporation to commercialize the Bionic Pancreas. Xeris has not moved particularly fast on its stable glucagon, and Zealand’s deep experience in protein chemistry will be a major asset on this intractable problem. Dr. Steven Russell hinted at ATTD that Zealand’s phase 2 glucagon might be used, though today was the first confirmation it is the glucagon of choice going forward. Dr. Damiano did not comment on the submission timing, but we assume the plan is still an end of 2017 insulin-only PMA submission, with a potential PMA supplement to add glucagon in early 2019.

  • Dr. Damiano’s oral presentation focused on the Bionic Pancreas 11-day multi-center home study (n=39), shared at several symposium presentations since GTCBio 2015 over a year ago. As a reminder, the study was the team’s first true home-use study, comparing 11 days of Bionic Pancreas to 11 days of conventional pump therapy. Mean CGM glucose improved from 162 mg/dl on usual care to 141 mg/dl on the Bionic Pancreas, projecting an A1c improvement of 0.8% (baseline: 7.3%). Time <60 dropped by two-thirds (from 1.9% to 0.6%), while time >180 declined from 34% to 20%. Dr. Damiano emphasized the device’s ability to dramatically reduce inter-subject variability, to not deliver excess insulin (0.62 u/kg/day vs. 0.66 u/kg/day), and to adapt to patients based on using just body weight at initialization.

Outpatient Glycemic Management in Type 1 Diabetes with Insulin-Only vs. Bihormonal Configurations of a Bionic Pancreas (79-OR)

Laya Ekhlaspour, MD (MGH, Boston, MA)

MGH’s Dr. Laya Ekhlaspour reiterated the insulin-only vs. bihormonal glycemic target studies first shared at ATTD. “Glucagon allows more subjects to have a mean glucose <154 mg/dl without increasing hypoglycemia.” We’ve reproduced the key findings below from the randomized, crossover study (n=20) comparing usual care to insulin-only and bihormonal versions of the Bionic Pancreas at different glycemic targets (insulin-only: 130 and 145 mg/dl; bihormonal: 100, 115, 130 mg/dl). The insulin-only and bihormonal systems were actually very similar with a glycemic target of 130 mg/dl: a mean glucose of 161 vs. 156 mg/dl and time <60 mg/dl of 0.8% vs. 0.5%. As the bihormonal target dropped to 115 and 110 mg/dl, mean glucose improved to 146 and 136 mg/dl without increasing hypoglycemia. The team is now exploring an insulin-only target of 110 mg/dl, as the use of 130 mg/dl was intentionally conservative.

  • This study shows just how important glycemic target is to system performance, and echoes the takeaway from the D-Data Exchange that closed-loop system should have adjustable target set points. The big question for glucagon, of course, is how much mean glucose, hypoglycemia, and user experience improves when the hormone is added to an insulin-only system.

System

Target BG

Control

Insulin Only

145 mg/dl

Insulin Only

130 mg/dl

Bihormonal

130 mg/dl

Bihormonal

115 mg/dl

Bihormonal

100 mg/dl

Mean

158 mg/dl

174 mg/dl

161 mg/dl

156 mg/dl

146 mg/dl

136 mg/dl

Time <60 mg/dl

1.4%

1.0%

0.8%

0.5%

0.9%

0.8%

Randomized Crossover Clinical Trial Comparing MPC and PID Control Algorithms for Artificial Pancreas (80-OR)

Frank Doyle, PhD (Harvard, Cambridge, MA)

Dr. Frank Doyle presented results from what he termed the “first, balanced, randomized study” comparing MPC and PID closed-loop control algorithms that came to two major conclusions: (i) that MPC outperformed PID on both the primary outcome and several secondary clinical metrics; and (ii) that both algorithms provided safe and effective glycemic control. This is the first time we’ve seen results from this crossover study, which randomized 20 patients to each algorithm for a supervised 27.5-hour session that incorporated both announced and unannounced meal challenges. Broadly, findings very strongly favored the MPC algorithm – patients using MPC saw significantly greater time in range (70-180 mg/dl) throughout the study vs. those on PID (74% vs. 64%, p=0.02). Patients on MPC also seriously reduced their mean glucose both during the entire trial (138 vs. 160 mg/dl, p=0.012) and during the five-hour period after the unannounced meal (181 vs. 220 mg/dl, p=0.019). Dr. Doyle noted that there were no statistically significant differences in hypoglycemia (<70 mg/dl) though he did acknowledge that the frequency of hypoglycemic episodes was higher in the MPC group. Ultimately, we would point out that these were both relatively basic iterations of both control systems and that the results do not preclude the use of PID in the closed-loop setting or suggest that all MPC systems are superior to those leveraging PID. Instead, we felt Dr. Doyle made the case that the core of the MPC algorithm may be better suited to managing artificial pancreas (insulin delays and pump constraints), in addition to that fact that MPC is a more flexible platform for adding other functionality.

  • For context, Dr. Doyle shared that standard and matched versions of both the MPC and PID algorithms were developed using well-known model-based methods. The algorithms had identical set-point control objectives (110 mg/dl) and had similar built-in features to prevent insulin stacking to ensure equitable testing conditions. Indeed, Dr. Doyle presented data from an in silico modeling experiment confirming that both algorithms performed very comparable in this controlled setting.
  • Study design: Dr. Doyle explained that both algorithms were compared in two supervised 27.5-hour closed-loop sessions. Challenges in the study were designed to mimic the use of an artificial pancreas in the real world and to stress the algorithms. These challenges included no prior optimization of insulin pump parameters to initialize the system, overnight control after a 65 g carbohydrate (CHO) dinner, response to a 50 g CHO breakfast (both bolused at mealtime), and an unannounced 65 g CHO lunch to evaluate a missed meal bolus scenario.

Questions and Answers

Q: This may be an artifact of the short study but I noticed that your two algorithms were pretty convergent for first day and where you saw separation was in evening. Do you have differences between these algorithms overnight? Because that’s when you really see that separation occurring.

A: There was insulin-on-board vs. insulin feedback built into the MPC and PID algorithms, respectively, so it could have to do with that. I will say that the number of occurrences of pump suspension was higher for PID, so there’s an indication that MPC was more effectively using insulin in the presence of pump constraints (including IOB).

Quantitative Evaluation of a Predictive Low-Glucose Management (PLGM) System (83-OR)

Bruce Buckingham, MD (Stanford University, Palo Alto, CA)

Dr. Bruce Buckingham shared results from an in-clinic, overnight study testing the MiniMed 640G predictive low glucose management (PLGM) algorithm’s ability to prevent hypoglycemia – this would have served as the 640G US pivotal study, though Medtronic is of course now leapfrogging the 640G to launch the 670G hybrid closed loop in the US. The 68-person trial induced hypoglycemia (via basal rate increase), and patients wearing the 640G/Enlite 3 were monitored with YSI over a nine-hour period to confirm hypoglycemia and sensor accuracy. The 640G’s predictive suspend algorithm successfully prevented hypoglycemia (two YSI values <65 mg/dl) in 41 of the 68 experiments, a solid 60% prevention rate. The mean duration of pump suspension was 105 minutes, and mean glucose was 83 mg/dl one hour after pump suspension, 129 mg/dl after three hours, and 152 mg/dl after six hours. It was good to see no significant hyperglycemic rebound, a testament to the algorithm’s design – it automatically resumes basal insulin delivery once glucose levels are recovering, a big step up over the 530G/Veo. This encouraging hypoglycemia prevention data parallels what we have previously seen on the 640G’s PLGM algorithm: the SportGuard trial from ATTD 2015 (41% reduction in hypoglycemia events <65 mg/dl) and the PILGRIM study presented at ADA 2013 (!) (80% hypoglycemia prevention). A deeper dive on the 640G can be found in our ATTD 2015 report, and our initial report on its January 2015 international launch.

  • Will all pumps have PLGS (at minimum) in a few years? We’d note that Tandem is also developing a PLGS system (before its hypoglycemia-hyperglycemia minimizer), though all other companies are jumping straight to hybrid closed loop. See our AID landscape here.
  • As we’ve previously noted, the MiniMed 640G suspends insulin delivery with a 30-minute prediction horizon and resumes insulin delivery once glucose levels recover. The suspend-before-low limit was set at 65 mg/dl in this study. For a “suspend before low” event to occur, both of these must happen: (i) the sensor glucose value is at or within 70 mg/dl above the low limit; and (ii) the sensor glucose value is predicted to reach or fall below a level that is 20 mg/dl above the low limit within approximately 30 minutes.
    • Following a mandatory 30-minute suspend time, basal insulin delivery will automatically resume if the following conditions are met: (i) the sensor glucose is at least 20 mg/dl above the low limit; and (ii) the sensor glucose is estimated to be more than 40 mg/dl above the low limit in 30 minutes. The pump will resume basal insulin delivery after a maximum two-hour suspension.

Questions and Answers

Q: Nice study, Bruce. This looks at one of the milder ways you can go hypoglycemic overnight, but another way is that you can overshoot the bolus dose before bed. What does this system do for these more immediate blood glucose decreases?

A: There was actually a study released this month from Australia – it looked at 28 patients given a morning bolus projected to bring them down to 55 mg/dl. 14% of patients became hypoglycemic in the control condition, 4% became hypoglycemic in PLGM. Also, overnight, everyone went hypoglycemic in the control condition, but only 13% did in PLGM.

Q: You were involved in both of these last two studies. There was 60% prevention in this one, 78% didn’t go below 60 mg/dl in the last one. Could you please compare the effectiveness of the two therapies?

A: This study was much bigger. We had 100% effectiveness at Stanford – other centers are not as experienced with these kinds of studies. It is hard to take one set of patients and compare them to another. Dr. Ly presented studies done at home…this was at a research center. I’m impressed with the similarities between the studies, given this fact. Bottom line, this system is fairly safe, it works, no hyperglycemia rebound, no DKA. But it’s not perfect, the amount of insulin on board really determines how effective these systems are.

Q: Has it been assessed in exercise induced hypoglycemia?

A: Not that I’m aware. [Editor’s Note: The PILGRIM study presented at ADA 2013 did test the PLGM algorithm under exercise-induced hypoglycemia; it was a small study in 22 patients, but showed 80% prevention.]

Overnight Closed-Loop (OCL) at Home Compared with Sensor-Augmented Pump with Low-Glucose Suspend (SAP-LGS) Improves Time in Target Range in Adults and Reduces Hypoglycemia in Adolescents (78-OR)

David O’Neal, MD (University of Melbourne, Melbourne, Australia)

Dr. David O’Neal presented data from a small crossover study showing that overnight closed-loop systems offer benefits for both adults and adolescents vs. sensor-augmented pumps. The study randomized 16 adults (baseline A1c = 7.3%) and 12 adolescents (baseline A1c = 7.8%) to either the MiniMed 530G overnight (control) or closed-loop control (intervention – Enlite 2 CGM, Medtronic pump, proprietary PID algorithm) for four nights at home. In adults, overnight closed-loop performance was strong – time in the tight range of 72-144 mg/dl increased from 45% to 58% vs. SAP (p=0.005) and time <72 mg/dl decreased from 1% to 0% (p=0.025) without a concurrent increase in mean glucose (145 mg/dl on closed loop vs. 152 mg/dl on open loop). There were fewer instances of symptomatic hypoglycemia on closed loop (13 events vs. 5 event; p=0.059), and all these benefits carried into the following day as time in range from 8 AM to 4 PM rose from 47% to 53%. In adolescents, the difference between the treatment arms was more nuanced – the main benefit was a reduction in overnight time spent <70 mg/dl from 2% to 0% vs. SAP along with a reduction in instances of symptomatic hypoglycemia (10 events vs. 1 event; p=0.007). Adolescents achieved quite impressive open-loop glucose control (time in range = 64%), leaving little room for time-in-range improvement with automation.

  • There’s little question that automated insulin delivery will make a big difference overnight, even in very tightly controlled patients. In fact, we expect many patients doing pretty well on open loop therapy now to adopt early closed-loop systems, even if they only wear them overnight.
  • We love too that overnight automation can actually live up to patients’ high expectations for AID systems. Overnight closed loop will really ensure patients wake up at a good glucose on most mornings, and patients’ open-loop control while ASLEEP can’t possibly be better than an automated system. First-gen hybrid closed loops are well suited for nighttime anyways, since they will modulate basal insulin delivery and won’t have to deal with meals or exercise.
  • Aside from glucose control, the key overnight design principle is alarms – systems must take care of things in the background and let patients sleep overnight.

Questions and Answers

Q: What do you think was the driving factor for the differences between the populations you studied?

A: I suspect that part of what we’re seeing is the impact of parental oversight of adolescents. Because these patients were moving on sensor-augmented pump from less sophisticated systems, I think adolescents in particular were able to achieve very good control overnight given the accessibility of these new tools (e.g., 64% time in target range in the control group).

Q: The adults and adolescents used different CGMs, didn’t they? Does that impact our interpretation?

A: We found that the MARDs in adults and adolescents were very similar, so we do not think the differences in CGMs played a role.

Predictive Hyperglycemia and Hypoglycemia Minimization: In-Home Evaluation of Safety, Feasibility, and Efficacy in Type 1 Diabetes (82-OR)

Trang Ly, MD (Stanford University, Stanford, CA)

Dr. Trang Ly presented results from a randomized, crossover, at-home overnight study comparing a hypoglycemia-hyperglycemia minimizer algorithm to a predictive low glucose suspend (PLGS) algorithm (Enlite 2, Veo pump, bedside laptop with algorithm). The six-week trial accumulated 641 nights on PLGS and 648 nights with hypoglycemia/hyperglycemia minimization, recruiting 30 patients who were randomized every evening for six weeks to either system. As expected, results showed the hyperglycemia mitigation made an incremental difference – time in range (70-180 mg/dl) increased from 71% to 78% (p<0.001) and mean glucose decreased from 152 mg/dl to 143 mg/dl (p<0.001). The benefit came largely from less time spent >250 mg/dl, which dropped from 4.5% to 1.6% (p<0.001), while average time spent < 70 mg/dl was not significantly different between the groups (1.1% [HHM] vs. 1.0% [PLGS]). Dr. Ly stressed that the group has taken a conservative approach in designing the algorithm, opting for safety in this study with the intention of tweaking the system to get greater glycemic control in the future. Indeed, larger randomized trials and studies in pediatrics are planned for the near-term and we look forward to seeing more data on the added benefits of a hypo/hyper minimizer component vs. just PLGS. In addition to better glycemia, shaving off those extreme overnight highs is highly valuable from a sleep and quality of life perspective too! We’d note that most of the field is skipping straight to commercial products with hypoglycemia/hyperglycemia minimization, with the exception of Tandem, who is pursuing PLGS first

  • J&J has previously used the name “Hyperglycemia and Hypoglycemia Minimization,” though this algorithm was not connected to Animas’ work. Still, it shows what can be done by adding even a conservative insulin modulation algorithm to shave off highs >250 mg/dl.

Questions and Answers

Q: Can you contrast this system with the UVA system?

A: We use a more conservative algorithm where the goal was not perfect control. This is very different from UVA’s overnight algorithm that targets a glucose of 120 mg/dl by morning. This algorithm was designed to be more conservative and to essentially provide a little bolus on top of the basal insulin people are getting. We’re still learning and it’s still evolving and we’re tweaking parameters. We’re going to be doing further studies in younger children. This was our first large trial using the full system.

Q: Have you considered a stricter target?

A: We started with a lower target of 120 mg/dl and we were seeing a bit of hypoglycemia so that’s why we raised it. We have to start somewhere, and it’s a constant balance between safety and efficacy.

Oral Presentations: ADA Presidents Oral Session

Closed-Loop Glucagon Administration for the Automated Prevention and Treatment of Hypoglycemia in Type 1 Diabetes (378-OR)

Courtney Balliro, RN, CDE (MGH, Boston, MA)

Ms. Courtney Balliro presented updated, full results from the Bionic Pancreas team’s placebo-controlled, double-blind, glucagon-only study in patients with type 1 diabetes. Time spent in hypoglycemia declined 78% overall and 93% overnight. The study enrolled 22 people with type 1 diabetes, who wore a Bionic Pancreas at home for 14 days that administered glucagon-only on seven of those days vs. placebo-only on seven of those days, interspersed in random order (insulin was self-regulated). Results were just as impressive as those first presented by Dr. Steven Russell at AADE 2015 – time spent in hypoglycemia (<60 mg/dl) was reduced from 5.8% with placebo to 1.3% with glucagon for the entire day (a 78% reduction). The overnight improvement was even more striking – 7.9% time spent <60 mg/dl with placebo vs. 0.5% with glucagon, a 93% improvement! Glucagon administration reduced hypoglycemia exposure (area over the curve and less than 60 mg/dl) by 77% (p<0.001) relative to placebo administration without affecting mean blood glucose (mean: ~154 mg/dl, in both arms). Performance was not at the expense of hyperglycemia, as time spent >180 mg/dl was not significantly different – 28% (glucagon) vs. 29% (placebo) (p=0.7) – nor due to greater insulin utilization – 39 units/day (glucagon) vs. 37 units /day (placebo) (p=0.12).

  • Ms. Balliro stressed that the Bionic Pancreas did not deliver excessive glucagon (~0.48 mg/day – on par with previous studies) and noted that there were no differences in self-reported nausea. The team continues to show strong data on this front, countering those arguing that glucagon administration may prove problematic on nausea.
    • The other big question is the effects of chronic glucagon exposure, and it will take some time to get an answer. We learned from Dr. Ed Damiano on during ADA that the team will use Zealand’s liquid stable glucagon analog and plans to begin clinical trials with the iLet device in 2H16. As we noted on Day #2, the pivotal studies of the insulin-only iLet are still expected to start in 2Q17. The bihormonal pivotal trial, which will begin after the start of the insulin-only pivotal trial, will require that a subset of the study cohort use the iLet for 12 months in order to gain chronic glucagon exposure data for the FDA. Dr. Damiano has forecasted an end of 2017 insulin-only PMA submission, with a potential PMA supplement to add glucagon in early 2019.
  • Ms. Balliro confirmed that the Bionic Pancreas team plans to test its glucagon-only Bionic Pancreas in patients with post-bariatric hypoglycemia and chronic hyperinsulinemia “in the next year or so.” The device could be particularly suited to the former group given that carbohydrate intake was reduced 35% in the glucagon arm. That said, Ms. Balliro stressed that the near-term focus is on bringing the dual-hormone device to the market – no surprise there – but it was terrific to hear that the team thinks a glucagon-only system does have commercial application.
  • Glucagon-only study design: Patients wore a Bionic Pancreas at home for 14 days that administered glucagon-only on seven of those days vs. placebo-only on seven of those days, interspersed in random order (insulin was self-regulated). Patients were not restricted in their daily activities and were blinded to which days they were on glucagon vs. placebo, which Ms. Balliro noted was effective: patients were able to distinguish glucagon from placebo treatment on < 50% of days [i.e., less than chance].

Questions and Answers

Q: In the individuals that had partial hypoglycemia unawareness at baseline, did they have restoration of hypoglycemia awareness at the end of the study?

A: We did not look at that, but I’m going to say probably not because the amount of symptomatic hypoglycemia reported did not correlate with actual hypoglycemia.

Q: Can you talk about why you switched back and forth between glucagon and placebo?

A: We didn’t want patients to recognize patterns between hypoglycemia and other adverse effects they experienced. In other studies, they have days in a row so the reason we did this was to make sure it was blinded.

Q: Do you have plans to test the system in other groups?

A: We have plans to test the system in patients with post-bariatric hypoglycemia and chronic hyperinsulinemia in the next year or so. However, the hope is any patient that wants it will be able to get a bihormonal bionic pancreas first – so that’s our priority.

Oral Presentations: Management of Hyperglycemia in the Hospitalized Patient (with State-of-the-Art Lecture)

Sensor-Augmented Pumps vs. Multiple Daily Injections for Achieving Glycemic Goals in Hospitalized Patients with Type 2 Diabetes in China (18-OR)

John Shin, PhD (Medtronic, Northridge, CA)

Dr. John Shin presented results from a Medtronic RCT comparing use of sensor-augmented pump (SAP) therapy to MDI in people with type 2 diabetes hospitalized for high glucose levels. The study enrolled 81 patients who were randomly assigned to use either the Medtronic MiniMed 722 (n=40) or MDI (n=41) to manage their diabetes (baseline A1c = 10.0%). Patients were given general instructions to increase or decrease their insulin bolus and basal dose according to real-time CGM (intervention group) or seven daily fingerstick tests (control), with physicians overseeing the adjustments. Patients were discharged once their glucose levels were between 80-130 mg/dl pre-meal and 80-180 mg/dl post-meal. Patients using SAP had significantly shorter hospital stays (3.7 days vs. 6.3 days, p <0.001), with greater time spent between 70-180 mg/dl (77% vs. 64%, p<0.05) and less time spent < 50 mg/dl (0.04% vs. 0.32%, p<0.05). Apart from some mild bleeding around the sensor insertion site, there were no adverse safety events reported. We would have loved to see patients go home on the different arms and tracked over time – would the pump advantage last outside the inpatient setting?

  • The proportion of time spent in relevant ranges almost unanimously improved with SAP. The one exception was time <70 mg/dl, which was not significantly different in the two arms

 

SAP

MDI

p-value

≤ 50 mg/dl

0.04%

0.32%

p<0.05

<70 mg/dl

1.00%

0.64%

NS

70-180 mg/dl

77.44%

64.33%

p<0.05

≥ 180 mg/dl

21.56%

35.03%

p<0.05

≥ 250 mg/dl

4.13%

8.53%

p<0.05

Questions and Answers

Q: Why were the patients in the hospital?

A: Glucose management issues.

Q: People would not be hospitalized for this in the US. So this was not really a hospital study, but more of a randomized pump vs. MDI study.

A: Yes. We essentially looked at the current therapy patients were on and saw how we could decrease time spent in a Chinese hospital.

Q: Who was making the adjustments in the algorithm on a day-to-day basis?

A: It was done by a physician.

Q: Upon release, did the patients stay on the SAP?

A: No, they did not go home with the technology. Once they achieved the target, they left without the pump. We haven’t tested what happens after the hospital stay – whether they remain in range or if they have to come back.

Efficacy, Safety, and usability of A Clinical Decision Support System for Basal-Bolus Insulin Therapy in Hospital Routine Care (15-OR)

Katharina Neubauer, BSc, MSc (Medical University of Graz, Austria)

Ms. Katharina Neubauer presented data demonstrating the efficacy, safety, and usability of GlucoTab – a mobile decision support system that provides suggestions for insulin dosing – in non-critically ill type 2 patients (n=92). The software aids nurses by providing a starting basal dose based on a patient’s age, weight, renal function, and insulin sensitivity and recommending subsequent bolus dosing depending on the patient’s food consumption and blood glucose levels throughout the day. Results were solid, especially given the typically inadequate care inpatients with diabetes receive – patients on GlucoTab achieved a mean glucose of 159 mg/dl (baseline: ~220 mg/dl) with 69% of blood glucose measurements in-range (70-180 mg/dl). Notably, the software completely eliminated episodes in which blood glucose dropped below 40 mg/dl and only 2.3% measurements came in <70 mg/dl. Equally importantly, findings suggested that provider’s adherence with advised insulin doses exceeded 91%, implying that there was a relatively high level of trust in the automated system (this is always a key question when talking about handing over decision-making to technology). This confirms the huge potential of meaningful clinical decision support in the hospital setting, which could shorten hospital stays and make healthcare professionals’ jobs easier. This was not a randomized controlled study, so there could be some study effect, but it’s clear that digital insulin titration is a heck of a lot better than what’s happening in hospitals right now. We hope to see more work on hospital insulin management, particularly in automating insulin delivery with the technology that is already available.

  • GlucoTab aids nurses by providing a starting basal dose based on a patient’s age, weight, renal function, and insulin sensitivity and recommending subsequent bolus dosing depending on the patient’s food consumption and blood glucose levels throughout the day. The process is repeated the following morning, with the new basal dose informed by the objective experience of the patient the previous day – i.e., if there were many hypoglycemic episodes, then the basal dose of insulin would be decreased. This study enrolled 92 hospitalized patients (40 female, mean age = 70 yrs), most of whom were already on insulin.
  • We noticed one unexpected result – pre-lunch blood glucose values were elevated compared with other pre-meal blood glucose levels. We wonder whether the algorithm could be tweaked to address this concern or whether this was an artifact of the study design in some way.

Questions and Answers

Q: Does GlucoTab account for the number of carbohydrates that the patient eats?

A: No, it only considers if the patient is eating or not.

Q: Do you make adjustments for steroids?

A: Not many patients in our studies were on steroids. It was not in the exclusion criteria, but we have an ongoing clinical trial for patients treated with steroids.

JDRF/NIH Closed-Loop Research Meeting

Pivotal Study Design

Steven Russell, MD, PhD (MGH, Boston, MA)

Dr. Steven Russell summarized a paper he co-authored with Dr. Roy Beck, soon to be published in Diabetes Care. The table below highlights their thought on pivotal study design for artificial pancreas systems, building off the question we asked last year, “What is the appropriate control group for an artificial pancreas pivotal study?” Below the table is further commentary on this very tricky topic.

  • Pivotal AP studies have several goals besides regulatory approval: advantageous labeling, reimbursement by payers, prescribing by practitioners, and adoption by patients. We loved hearing Dr. Russell emphasize the payer point upfront: “There’s approval, and then there’s approval. The design of the trial itself can make a very big difference in how persuasive the case is to payers.” This is where the study design considerations (see below) might really drive payer decisions about this technology. For instance, if a pivotal trial only enrolls sensor-augmented pump users, will payers only offer closed-loop to this group of patients?
  • Sensor-augmented pump therapy is a scientifically valid control group (the best therapy available), but it is also a small slice of type 1 diabetes. “We want to democratize good glycemic control,” said Dr. Russell. Those already using a pump and CGM “are atypical, self-selected patients that may not be representative” of the broader population. Drs. Russell and Beck recommend that studies enroll those on MDI and pumps, with few exclusions (i.e., representative of the candidate population for artificial pancreas systems).
    • “Sensor-augmented pumps without automation will be obsolete soon.” This is another reason SAP may not make sense as the control group – what a good point! It will be interesting to see what the pump field looks like in five or ten years; will the vast majority of SAP users be on automated insulin delivery? Will it take much longer than expected for patients to move to automation? Will some SAP users never convert?
  • “Time-in-range doesn’t tell you what’s happening with time outside range. We argue that A1c and time in hypoglycemia are the best outcome measures.” This is consistent with the co-primary outcomes the Bionic Pancreas team has always reported (mean glucose and time <60 mg/dl), and we wonder if other companies and investigators will pursue this going forward.
    • For comparison, Medtronic’s MiniMed 670G pivotal was a single-arm safety study comparing baseline control to three months, and it was not actually statistically powered to show a reduction in A1c. As we noted on Day #2, however, it did show a statistically significant 0.5% reduction. CGM endpoints were secondary: time-in-range (% of SG in 71-180 mg/dl) improved modestly from 67% during the baseline run-in to 72% during the study, with time <70 mg/dl nearly halved (6% to 3%), time <50 mg/dl declining 40% (1% to 0.6%), and time >180 improving moderately (27% to 25%).
  • The FDA wants pivotal trials to include all ages, rather than limiting exposure to adults. “They know that this is likely to be prescribed off-label.” This echoes early June commentary from FDA’s Dr. Courtney Lias during her live Q&A webinar on the artificial pancreas.
  • The FDA wants pivotal studies to be at least three month long, meaning a parallel group design makes sense to keep the study short.
  • “You need range of A1c’s to make sure the system works well.” This has been a historic challenge in automated insulin delivery trials, and we hope investigators can really enroll a wide spectrum of patients going forward. Those most likely to benefit from these systems – high A1c patients, severe hypoglycemia – need to be included in studies!
  • To encourage retention in the usual care group, the Bionic Pancreas bi-hormonal pivotal will include an “incentive study” – those randomized to usual care will get three months on the Bionic Pancreas at the end of the trial.

Pivotal Study Design Consideration

Recommendation

Alternative

Comment

RCT Type

Parallel

Crossover

Crossover design requires long washout

Study Population

Representative of population, patients who use MDI and CSII, with few exclusions. Range of A1c’s.

Adults-only, high-risk patients excluded

Given the potential for off-label use, the FDA may not approve if the device is not demonstrated to be safe in a broad population and payers may limit coverage to only the population that was studied

Randomization (artificial pancreas: Control)

2:1

1:1

2:1 randomization provides greater exposure to artificial pancreas, 1:1 randomization will require a smaller sample size or give greater power for same sample size if equal variance.

Control group

Usual care

SAP

Both scientifically valid, usual care has numerous pragmatic advantages

Superiority vs. non-inferiority

Superiority

Non-inferiority

Non-inferiority may be sufficient for approval but is not likely to drive reimbursement and adoption

Run-in period

Blinded CGM monitoring

Unblinded CGM (SAP training)

Unblinded run-in must be sufficient to achieve competency for SAP trial enrolling non-SAP users

Duration

6-12 months

3 months

3 months min for A1c; longer duration shows continuation of use and durability of effect

Primary outcome(s)

A1c, time <60 mg/dl

A1c only

A1c does not capture hypoglycemia; CGM more reliable and quantitative than participant recall

Outcome Measures for Artificial Pancreas Clinical Trials: A Consensus Report

David Maahs, MD (Barbara Davis Center, Aurora, CO)

Dr. David Maahs also summarized a soon-to-be-published Diabetes Care paper focused on standardizing a short set of basic, easily interpreted outcomes in artificial pancreas studies. The paper has 24 authors, all of whom are leading thinkers in the field. The goal is to facilitate interpretation and basic comparison between studies, and more importantly, to accelerate adoption of artificial pancreas technologies via regulators, HCPs, payers, and patients.

Outcome Metrics

Comment

A1c

Mean CGM glucose

If intervention >3 months)

% time in 70-140 mg/dl

% time in 70-180 mg/dl

All CGM measures should be reported for the overall 24-hour period, and also stratified by daytime and nighttime period. The time midnight to 6am is proposed as a nighttime definition.

% time <50, <60, <70 mg/dl

 

% time >180, >250, >300

 

Standard Deviation

Coefficient of Variation

SD much more dependent on mean than CV

Severe hypoglycemia

As defined by ADA (adults) and ISPAD (children/adolescents)

DKA events

ADA definition

% of time closed loop active

 

TDD of insulin

TDD of glucagon or other hormones

 

Other considerations

# of symptomatic hypoglycemia events per week

CGM calibration, MARD

Study design and stratification into relevant subgroups

ITT analysis

Report medians (quartiles) instead of mean if not normally distributed

Driving Access to Artificial Pancreas Systems

Amanda Bartelme (Director, Avalere Health, Washington, DC)

Ms. Amanda Bartelme provided a reimbursement overview of automated insulin delivery, highlighting some of the key challenges: too much focus on A1c, hard-to-predict contracting negotiations, data needs that differ from FDA approval requirements, and more. JDRF is already talking to payers about AID reimbursement, though there was no commentary on what is being learned from those conversations. From what we can tell, Medtronic will pursue the existing reimbursement channels for the MiniMed 670G (i.e., sensor-augmented pump reimbursed via DME), though this field seems ripe for a new business model (e.g., AID for $75 a month). Ms. Bartelme cautioned that “if a payer thinks every type 1 patient wants to go on this tomorrow, that’s huge dollar signs and huge panic.” It served as a reminder that nothing is a given with payers in this environment – even devices that reduce A1c, hypoglycemia, and patient burden. How can industry show a positive short-term return-on-investment for AID?

  • Diabetes therapies and technologies cannot be fully assessed by A1c alone.” Ms. Bartelme provided a value graphic showing the “current” and “desired” states, noting that payers and FDA (drug division) both have a ways to go before they accept outcomes beyond A1c. This ADA had much more discussion on the limitations of A1c, but it will take time for this to trickle up to decision makers. As a reminder, JDRF has an ongoing health policy initiative to define the key outcomes beyond A1c, and an FDA meeting will occur on August 29 on this very topic.

Current State

Desired State

  • Regulators and payers have a singular focus on A1c
  • Regulators do not always allow other outcomes on product labeling
  • Achieving payer coverage for diabetes technologies that improve other outcomes, but do not reduce A1c is challenging
  • Expanded set of diabetes outcome measures that reach beyond A1c, and that better reflect the impact of emerging therapies on people with diabetes
  • Regulator and payer acceptance of a full range of diabetes outcomes
  • Increasingly, payers require more and different data than are necessary to receive FDA approval. Most of all, payers look at whether something is worth paying for –is it safe and will it improve outcomes? What does the label look like? How was the study designed? Ms. Bartelme highlighted that the timing of data collection is important to ensure payer coverage post FDA approval – yet another reason why pivotal studies should be designed with reimbursement in mind.
  • The payer contracting process brings uncertainty and can be a gating factor to access. Sometimes payers limit coverage to the FDA label, sometimes they expand beyond it, and sometimes they narrow it. Ms. Bartelme noted that “creative contracting” can support post-market data collection, patient affordability, and improved access. We wonder how that specifically played a role in the UHC/Medtronic partnership announced a few weeks prior to ADA.
    • “Fantastic data might make more challenging contract discussions. If a payer thinks every type 1 patient wants to go on this tomorrow, that’s huge dollar signs and huge panic.” Whoa – we hadn’t thought about that, but it’s a good point, and one we’re not sure companies can control. It serves as a reminder that nothing is a given with payers, and the key may be showing that short-term return-on-investment is very positive with AID.
    • Increasingly, payers are willing to entertain value-based contracts in addition to traditional fee for service arrangements. Will subscription approaches to pump therapy and automated insulin delivery become more common? If so, companies like Insulet and Bigfoot would seem to have an advantage, as their hardware has lower upfront costs. Would Medtronic be able to change its DME business model (~$5,000 upfront), or would their pump hardware need to be overhauled? What will Tandem, Animas, and Roche do?
  • “FDA approval is necessary but not sufficient for payers to provide coverage. To be considered for coverage, a new therapy or tech must be reasonable and necessary, which is: determined by clinical evidence that shows an improvement in net health outcome; determined by proving that is non-inferior to or beneficial over existing alternatives; increasingly determined by showing improvement is attainable in a real-world setting.” That latter point is the trickiest in our view – clinical trials are almost always not real-world, particularly because the control group does so much better (and thus, underestimates the incremental impact of new technology).
    • A technology or therapy may also only be covered when certain other criteria are met: age, not achieving desired outcomes on traditional therapies. Both of these continue to make CGM reimbursement challenging, and we wonder if automated insulin delivery will make the process easier or harder.

Psychosocial Outcome Assessment

Korey Hood, PhD (Stanford University, Stanford, CA)

Stanford’s Dr. Korey Hood revealed that by fall 2016, a full set of validated questionnaires will be available to assess the psychosocial impact of automated insulin delivery. Fantastic news! The team has done 60 focus groups, 89 individual interviews, and engaged 400 participants ranging from no experience with closed loop technology to OpenAPS users. Some of the thematic areas include: burden, concerns, features, financial aspects, benefits, context, human vs. system, nighttime, quality of life, and relationships. Dr. Hood shared some example questions, such as, “I believe that using an AID system will... help me worry less about diabetes...” The assessment will also ask about benefits and tradeoffs to using systems – “If the AID system improves my A1c, I will put with ... meal announcement, carb counting, etc.” We love the holistic, behavioral view of these systems, which will be just as important as the impact on glucose. Enormous thanks to the Helmsley Charitable Trust for funding this major project!

Brief Summary of AP Highlights from the Past Year

Vincent Crabtree, PhD (JDRF, New York, NY); John Lum, MS (Jaeb Center for Health Research, Tampa, FL)

Dr. Vincent Crabtree and Mr. John Lum gave a broad overview of JDRF and NIH-funded artificial pancreas highlights from the past year, offering several updates we had not heard previously.

  • Dr. Roman Hovorka’s NIH-funded DAN05 study will investigate closed loop therapy in 6-18 year-olds over 12 months. The study will randomize patients on pumps to either automated insulin delivery (n=65; MiniMed 640G/Enlite 3 + the Cambridge algorithm running on an Android phone) or standard pump therapy (n=65). It’s not clear when it will start. It’s outstanding to see this study getting off the ground after it received ~$6.4 million of the UC4 grant for major artificial pancreas trials (announced at DTM 2015). We’re not sure if Dr. Hovorka would apply for regulatory approval after this study, though it is notable that he is now using Medtronic hardware to do his research.
    • The planned CLOuD study will test automated insulin delivery in new onset type 1 diabetes over two years. The study will have 96 participants randomized to either closed loop or usual care, and the goal is to show an impact on C-peptide – wow! As a reminder, Dr. Bruce Buckingham and colleagues did a similar study, though the time on closed loop was just a brief period at diagnosis, followed by sensor-augmented pump therapy. Hopefully this study can show this technology makes a difference in preserving beta cell function if it is added right at diagnosis, which could be transformative for guidelines and treatment approaches. 
    • Dr. Hovorka also has three 24/7 home studies underway, continuing the team’s trailblazing work of longer-term, outpatient studies. We assume we’ll see some of this data at EASD 2016 or ATTD 2017.
  • Dr. Crabtree is “hopeful” that the upcoming International Diabetes Closed Loop study (n=240) could be used to support regulatory approval. This is consistent with what TypeZero CEO Chad Rogers told us earlier this year. We’ve learned that the TypeZero control algorithm will reside on an Android phone, and the study intends to use insulin pumps from more than one manufacturer (Cellnovo has signed on thus far).
  • Dr. Tim Jones will conduct an independent, six-month RCT of the MiniMed 670G hybrid closed loop (n=80), starting in 3Q16. The trial will randomize patients to standard therapy (both CSII and MDI) or use of the hybrid closed loop. An ongoing study has been examining the MiniMed 640G over six months of use, with completion expected in November. We love the idea of independent academic investigators validating commercial systems – this can grow the body of evidence around these systems, but do so impartially (helpful for payers).
  • SGLT-2 inhibitors are now being studied in conjunction with closed loop at Yale (Dr. Jennifer Sherr) and Montreal (Dr. Ahmad Haidar). This could help cut the need for manual pre-meal boluses and make systems more fully automated.
  • Plenty of work is happening to advance algorithms further, including fault detection (infusion set issues; CGM errors); coping with exercise; and making algorithms more adaptive. All clearly have a role in making this technology safer and enabling tighter control and lower glucose targets. 

Opening Remarks

Aaron Kowalski, PhD (JDRF, New York, NY)

Dr. Aaron Kowalski gave brief introductory remarks before handing it over to JDRF’s Dr. Vincent Crabtree and Jaeb’s Mr. John Lum. Dr. Kowalski highlighted the completed MiniMed 670G pivotal study, which reported earlier in the day with strong outcomes: a 0.5% reduction in A1c from a low baseline (7.4%); time <70 mg/dl declined 44% (6% to 3%); and time <50 mg/dl declined 40% (1% to 0.6%). “I cannot believe we are on the cusp; we are right around the corner from artificial pancreas. We are now talking about broader issues: special populations, reimbursement, etc. These are incredible times. I’m really grateful.” It’s been an amazing journey since JDRF founded its artificial pancreas program ten years ago, and we cannot wait to see how the 670G fares once it hits the market as the first commercial closed-loop product (FDA submission by the end of this month).

Panel Discussion

Dr. Aaron Kowalski: Steve [Dr. Russell] captured the best bullet I’ve seen in a long time. Sensor-augmented pump therapy without automation will soon be obsolete. It’s so cool to see that on paper.

Dr. Rich Bergenstal: I love the standardization for outcomes of artificial pancreas studies. My request is that it be branded not just metrics for artificial pancreas, but general metrics. To have one definition for artificial pancreas community, and then have “this long-acting insulin vs. this insulin” reported a different hypoglycemia is no good. These don’t sound like artificial pancreas metrics, this sounds like broader metrics. If I’m in clinic and wanting to know if I’m improving, I could use these too.

Dr. Maahs: We had that in the paper – studies of all type 1.

Dr. Roy Beck: You did not include LBGI or AUC. I actually like the ones you picked, but those seem like they might be better – they capture not just time but amount?

Dr. Maahs: We should consider this paper a first step. It was something we could agree on, a basic set of measures. Drs. Hovorka, Kovatchev, and Weinzimer wrote a paper with more details and more math. There is lots of room to do more.

Dr. Beck: We should be cautious about using the standard metrics to compare across studies, particularly those without a control group. The best way to compare across studies is to determine the within study intervention group versus control group difference and then to compare this difference among studies.  Even then there are potential problems since study designs vary, clinics are different, and eligibility criteria may be different. 

Dr. Peter Chase: We need some help with patient selection. We have these high tech families with low A1c’s. How do you go about getting a representative population?

Dr. Hood: Great question. In the pilot projects, we often don’t get a representative sample. The larger project is developing measures that can assess some of these aspects in CGM naïve, pump naïve, and system naïve users. The data that we have, data from participants is the first wave of information. We might have double and triple the barriers and problems when access is broadened. It’s likely that once you get beyond this early adopter population, we’re going to face  the same barriers to uptake. We are working to design interventions so that once we get beyond that first wave, we can onboard people.

Dr. Russell: It may be the only way to get more representative population is to achieve geographic diversity. We selected 16 sites with a geographical consortium, not just eastern and western seaboard. Clinics that had different populations and different socioeconomic data.

Dr. Beck: And higher A1c’s. Roman will use 25% above 8% or 8.5% to force that issue with a quota. Then, you fill the quota of under 8.5%. Boris will have half the patients with higher A1c’s.

Dr. Roman Hovorka: What happens at the end of the trial in those recruited from MDI to closed loop. Unless we are a big company, they cannot continue using an investigational device for treatment. What does the panel suggest?

Dr. Helen Murphy: In cancer trials, there is a cancer drugs fund that is made available to participants. Maybe Aaron and JDRF can start advocacy for artificial pancreas funding. [Editor’s Note: Dr. Murphy also gave a presentation on closed-loop in pregnancy, but it included confidential material, and we have not covered it in this report.]

Dr. Hovorka: I asked in the UK, and you cannot actually continue using an investigational device in the UK.

Dr. Maahs: In the MiniMed 670G trial, many adults were allowed to continue devices, though that is in the US.

Adam Brown (Close Concerns, San Francisco, CA): One of my biggest worries is we will undersell the benefit of this technology, because of the patients being enrolled in these studies. In the MiniMed 670G pivotal, they had a baseline A1c of 7.4% and spent 67% time-in-range during the run-in. How can we get a broader patient group? What about those with severe hypoglycemia? Those with really high A1c’s?

Ms. Bartelme: We can’t let perfect be the enemy of the good. Taking people in really poor control, and showing changes is not easy. There’s also the mental burden that is harder for people to wrap their head around. We have to educate payers on this front.

Dr. Beck: In the study today presented on CGM in MDI users, their mean time-in-range 70-180 at baseline was about 45%. I think that is pretty reflective of what the average probably is.

Dr. Beck: What is the ideal study design and potential to get payers to agree on what they might expect for the magnitude of effect?

Ms. Bartelme: We need a targeted approach: find a couple of high functioning payers that are more innovative. I think there is some value there. But you don’t want to have conversations with payers who say, “These are the 14 endpoints we want to see.” Typically six months to a year before FDA approval is a good time to start talking to payers. With more innovative payers, you can do progressive things and partner earlier on in the process. There is a desire among payers to do risk-based contracting and value-based payments. There is lots of talk about that in the drug world. Once you get people in the real world, the data is very difficult to collect. Fortunately, artificial pancreas technologies are collecting data with patients all the time.

Brandon Arbiter (Tidepool, San Francisco, CA): Across board, we hear that people would gladly take the device home; that was not my experience in the study. The user experience around alarms was so illogical and awful that I withdrew. But my question is that I realized i wasn’t in an end of study focus groups. Is there a process to collect feedback from those who drop out?

Dr. Hood: We can do the focus group later if you would like [Laughter]. You raise a great question. Tomorrow I will be talking about responders vs. non-responders to a treatment. There is an attribution, often false, that you didn’t respond to a treatment because of some set of reasons that didn’t have to do with the intervention. That means when an intervention works, it’s because of the intervention; when it fails, it’s because of the person. We don’t do enough about that. You offer a valuable set of experiences. Many times, when we get beyond two and four weeks and do an evaluation in six months, we got lots of good info on high vs. low users. We haven’t tapped into that enough.

Dr. Russell: We can learn from these reasons – we’ve only had one person voluntarily drop out of one of our studies. That person had spectacular blood glucose control with no hypoglycemia. But she felt very uncomfortable at that mean glucose. She was used to running very, very high, and actually felt low at a mean of 110 mg/dl. That’s one of the reasons why there is option to raise the target and get a higher mean glucose if you don’t want to achieve the lowest mean. Maybe over time, a person would become more comfortable. That wasn’t a problem I would have anticipated.

Joint ADA/JDRF Symposium: Optimizing Use of Technology and Therapeutics in Pediatric Diabetes

Automated Insulin Delivery and Bihormonal Artificial Pancreas in Pediatrics―Coming Soon!

Trang Ly, MD (Stanford University, Stanford, CA)

Stanford’s Dr. Trang Ly provided a whirlwind tour of automated insulin delivery systems in development, highlighting the now-complete MiniMed 670G pivotal study (“outstanding results,” particularly in adolescents and in well-controlled patients; see here); UVA’s DiAs system (pivotal trial starting later in 2016, but final device not decided on), Beta Bionics (works in insulin-only mode; big wins: adjustable target, qualitative meal boluses, few alarms; insulin-only pivotal starting in 2Q17, followed by the bihormonal pivotal), Tandem’s predictive low glucose suspend system (pivotal trial later this year), Animas’ hypoglycemia hyperglycemia minimizer (pivotal trial later this year), Bigfoot Biomedical (smartphone app to interface with system and bolus), Cambridge (“amazing results,” but no commercial partner), Diabeloop with Cellnovo’s pump and Dexcom CGM (pivotal trial later this year, apply for CE Mark in 2017), Insulet’s artificial pancreas system (first ever picture we’ve seen, human trials starting later in 2016), and Inreda’s bihormonal system in Europe (studies ongoing, CE Mark in 2017) WOW! We had not previously heard these timelines for Diabeloop or Inreda. Dr. Ly also highlighted that the next-gen Medtronic pump, the MiniMed 690G, is already in development and will include the DreaMed algorithm to perform automatic correction boluses based on CGM readings (entering a trial this month, according to Medtronic’s Saturday dinner).

At a higher level, Dr. Ly called for customizable glucose targets that allow patients to titrate algorithms’ aggressiveness. While this isn’t available in the first-gen 670G, it could be available in other systems (e.g., Beta Bionics’ iLet), and hopefully it will be widespread in next-gen products (of course, there is tough balance to strike here between complexity and customizability). Dr. Ly summarized that closed loop represents “a new paradigm in diabetes management,” and “these therapies will be transformative for pediatric diabetes care.” She emphasized that first-generation systems are still going to be conservative, still require maintenance, and will not be a cure – in short, “managing expectations” is critical, particularly with the first-to-market 670G. We couldn’t agree more on that point!

  • Dr. Ly noted called the 670G pivotal trial data “outstanding,” and was particularly impressed with the adolescent results (see our coverage here). She noted that the adolescent patients were already doing well at baseline (A1c: 7.7%), and still saw an “incredible” 0.6% reduction in A1c AND less hypoglycemia.
    • Managing expectations will be the big challenge with the 670G. Dr. Ly noted that the glucose control “is not perfect,” and in this first-gen hybrid closed loop, the algorithm has to be conservative because it needs to be safe. She explained that the 670G will work great for patients who are already testing and doing pre-meal boluses, but it’s not going to do everything – in other words, it’s not a device you turn on, do nothing, and get an A1c of 7% with no hypoglycemia. Still, she called it “incredibly promising data” and is clearly psyched about its potential.
    • “Dr. Ly, thank you for giving me back the son I had before he was diagnosed with diabetes,” shared one mom of a 670G pivotal trial participant. This echoes what we have heard for a long time about automated insulin delivery – it frees up mind space and brings awesome quality of life benefits. We hope those are captured as the FDA weighs risk-benefit, and as payers weigh reimbursement. As a reminder, 80% of 670G pivotal study patients are still using this device as part of the FDA’s continued access program, a strong vote of confidence in the benefits vs. burden balance.
  • Dr. Ly showed the first picture we’ve ever seen of Insulet’s artificial pancreas system, which included a slim handheld controller, an MPC algorithm built directly into the pod, and Dexcom CGM. Clinical studies will start in 2016, consistent with expectations, and we assume the plan to be in market in 2018 still stands. Insulet management had previously hoped the system might use a phone, but obviously a handheld is likely a faster and easier development path – we assume a phone app could still show data and perhaps add remote bolusing over time. We’re glad to see the handheld will be pretty slim and small, an improvement from the fairly clunky PDM that has not changed much since the OmniPod originally launched. As a reminder, the MPC algorithm is a commercial version of the UCSB algorithm licensed from Mode AGC in 4Q15.

Questions and Answers

Q: If you’re looking for A1c improvement, why not try this in A1c’s of 12-14%? 

A: That will be the next challenge. You have to think about why a patient has a 12-14% A1c. If they are doing it because they are not testing and not bolusing, closed loop is not going to fix that. Closed loop will ideally be the new normal like pump therapy should be the new normal. But we’re not going to fix a 14% A1c that doesn’t want to take insulin because he or she is trying to lose weight.

Q: People don’t want to push buttons. Won’t this make a huge difference now that patients don’t have to push the buttons?

A: In the first-gen you will have to push buttons. You need to calibrate the sensor, for instance, otherwise you won’t stay in closed loop. There is still a lot of work to be done on the patient side.

Q: What about pump failures, failure to insert, kinking, etc.?

A: It depends what you mean by pump failures. I think you mean infusion set failures. There are lots of different companies developing better infusion sets. From our experience with the 670G, it has better detection for that occlusion. I think that is still a work in progress. We’ve done some work at Stanford, UCSB, and RPI to develop closed loop algorithms to better detect infusion set failures. It’s tricky because it’s hard to tell. There is a balance between false alarms and true alarms. It’s really hard to develop those algorithms to better detect that, and we need to make them functionally better. Companies are working on that and studies are happening.

Q: In the first gen, it’s amazing that system can be way better than control group with a target range of 70-180. Can you imagine the next gen will be even better range, say a range of 70-130?

A: I think we need to get it out, and after the first-gen, allow patients to modify the set point, so it’s the right percentage of time-in-range for them. That’s what systems need to have. When patients first test it, they say it’s great and it works really well. But when we started to test it out for longer, say three or six months, patient say, “Well, actually, sometimes I want the algorithm to be more aggressive and I want to be a bit lower.” So it needs to be adjustable for patient needs.

Q: We have a lot of Medicaid and managed care patients; just getting CGM is difficult. Where do you see closed loop? Will it be harder or easier? Looking at the data, with a reduction of 0.6%, will insurance companies say that is not relevant?

A It’s going to take long conversations, lots of work, patient advocacy groups, and Aaron might be able to talk more about this. We need to get it out, and I think it will actually help improve things once it becomes standard of care, potentially all systems will need to have automated closed-loop control to remain competitive on the market. But someone is going to have to pay for it.

Q: My concern when CGM first came out is that all insurance companies were paying for it. But two years down the line, all the sudden they’re saying we’re not paying for it.

Dr. Aaron Kowalski (JDRF): This is a top priority at JDRF. We have started a large health policy initiative with the Helmsley Charitable Trust. It doesn’t do any good if we develop new technology or therapies that are not accessible. The payer feedback has been pretty positive, and we are engaging with the major players. We want to make sure these are accessible for anybody who would benefit.

Status of Insulin Pump and Continuous Glucose Monitoring Use in Pediatric Diabetes

Jenise Wong, MD, PhD (UCSF, San Francisco, CA)

Dr. Jenise Wong provided a comprehensive overview of device utilization in pediatric type 1 diabetes. Beginning with pumps, she noted that there are a host of studies documenting the glycemic and quality-of-life benefits in children and adolescent but noted that use remains very variable by country. Dr. Wong attributed the variability to a number of factors from reimbursement and guidelines around pump use to the availability of pump reps and supplies – she cited T1D Exchange data suggesting that pump penetration is as high as 60% in the US, more than three or four times the penetration in EU countries. She contrasted that level of penetration with CGM, noting that the penetration of this technology remains VERY sparse (~15% in the Exchange). She was very positive on the benefits of sensor technology, though noted that a significant discontinuation rate prevents serious uptake. We do think that part of this has to do with patients’ sky-high expectations for CGM technology and the reality that the devices – while improving in accuracy and usability – are still not perfect, particularly on day one. She noted that even among CGM users, few patients take full advantage of the technology since such a minority of patients routinely review device data (see below) – we think this is because device data does not offer nearly enough benefits relative to the hassle of obtaining it and making sense of it. Once powerful, automated pattern recognition and compelling insulin titration algorithms are in place, we think device downloading will improve, or perhaps move to a real-time notification model. Ultimately, she suggested that education on the importance of device data (both on a provider and patient level) is a key step toward greater penetration in the future. We agree with her, though believe that CGM reimbursement, factory calibration, on-body form factor, a BGM replacement claim, and clinical decision support are more important for expanding uptake.

  • Dr. Wong presented valuable data on the lack of device data utilization from the T1D Exchange. Unsurprisingly, utilization is lowest among young adults with higher use among children and adolescents (where we assume parents are very involved with care). This does not surprise us one bit – CGM download software does not yet provide enough benefits to make the hassle of obtaining it and interpreting it worth it. Further, we believe the retrospective data mindset must change to a real-time model that gives patients more in-the-moment pattern recognition. What is more useful – a “morning high” pattern alert that is triggered every few months someone downloads, or a real-time notification at 10 am (“High pattern after breakfast observed for the past six days”)? In our view, personal CGM is a real-time technology, and patients stand to benefit the most from real-time, in-the-moment data analysis.

CGM Download Frequency

Never

1-3x per month

1x per week

Children

24%

37%

8%

Adolescents

36%

22%

12%

Young Adults

45%

16%

4%

Adults

42%

17%

5%

  • Dr. Wong also shared broader data comparing data downloading frequency (BGMs + CGMs) among adult patients and caregivers. We assume these numbers are self-reported (meaning they are probably overestimates), and they still fall woefully short of where we would like them to be. This will unquestionably improve as devices become connected to the cloud and stream data automatically, such as Dexcom’s G5, Abbott’s LibreLink, Medtronic’s MiniMed Connect, and a host of cellular- and Bluetooth-enabled meters. However, it still begs the philosophical question – is the future of diabetes data in real-time decision support and automatic pattern recognition? Is it realistic to ever expect patients to download and review their historical data?

Device Download Frequency

Never

Sometimes

Routinely

Adults

69%

20%

12%

Caregivers

44%

40%

27%

Questions and Answers

Q: What is surprising to me is the lack of penetration of pumps in pediatric patients considering the low discontinuation rate. That must mean we’re not getting people onto pumps in the first place?

A: Yes, that’s the first barrier – getting people onto pumps. We talked about the 60% on a pump; what we didn’t talk about is what is keeping those other 40% from starting. There are social factors to be sure - racial disparities, socioeconomic disparities. There are very real ways we could change the system and address cultural barriers that would help. So you’re right that discontinuation isn’t as much of a factor in pump use. The factor is getting people to start.

Q: Is discomfort a limiting factor with CGM? I’ve heard with Libre in the EU that skin reactions stops some kids from using the device.

A: Skin reactions are a common reason for discontinuation for all CGMs. I don’t know if the solution is better troubleshooting from an educator and clinician standpoint or a device innovation that needs to happen. However, it is a common cause of discontinuation and people who are using it will still complain.

DiabetesMine D-Data Exchange

The standing-room-only DiabetesMine D-Data Exchange gathered some of the best minds in diabetes technology, headlined by: a vision for interoperable, component AP systems (FDA’s Dr. Courtney Lias); a standing ovation for OpenAPS developer Mark Wilson; a masterful overview of different closed-loop systems from Stanford’s Dr. Trang Ly; a strong desire for customizable closed loop algorithm glucose targets; and more need for industry to engage with and learn from the DIY community. See a couple themes immediately below, followed by full talk write-ups.

Themes

  • There was consensus that closed-loop devices should: (i) include algorithms with customizable glucose targets; (ii) insulin-on board on the home screen; and (iii) have highly adjustable alarm settings. The patient panel was clear that customizing an algorithm’s aggressiveness is very key – some patients want more control, particularly because early-generation systems are more conservative. Indeed, Dr. Trang Ly pointed to this as an area for improvement in the Medtronic MiniMed 670G, which targets 120 mg/dl and does not allow the user to lower the target. Of course, there is a tough balance between customizability and simplicity – tweaking every parameter might be ideal for early adopters, but will add too much complexity that could hinder adoption. Dr. Ly felt strongly that systems should include insulin-on-board, a sentiment we agree with.
  • The DIY community is dying to interact with industry, though companies are still resistant. OpenAPS co-creator Dana Lewis indicated that industry’s regulatory concerns are a “phantom worry.” Dr. Courtney Lias urged the DIY community to talk to the FDA. Ms. Lewis argued that companies can still talk to and learn from the OpenAPS community, even if it is not an “approved” product – engaging does not imply support or anything illegal. Dr. Lias said the FDA “comes from a place of understanding,” but OpenAPS technically falls under FDA jurisdiction. The agency has the option of using enforcement discretion and will enforce based on risk – FDA may not choose to spend resources on someone building a system for their own personal use. However, the Agency does want a level playing field: “There is no difference between a movement developing a platform, and a small company developing a platform. We are definitely open to talking about the community, and how we cover the responsibility piece and make sure adverse events are reported...I would push the patient community to start solving the responsibility piece, even if it’s not the current FDA path, we are open to talking about that. There are lots of ways to meet the FDA requirements...Vendors are skittish because of the area of responsibility....We can solve problems by talking together, not by assuming FDA will or won’t do something. I would invite people to talk with me about it, and encourage bigger discussion between this community and FDA – how do we get you what you want, and how do we get what we need?”

FDA on Interoperability & Artificial Pancreas Progress: Where Guidance Can Take Us

Courtney Lias, PhD (FDA, Silver Spring, MD)

FDA’s Dr. Courtney Lias shared a strikingly optimistic goal to build an infrastructure for interoperable, modular, component artificial pancreas systems. “We don’t see a way artificial pancreas can be what it needs to be without this. I’m sharing our intention of solving this problem.” As she noted at last week’s AP Webinar, the current regulatory paradigms are easier for single companies submitting a combined pump/CGM/algorithm system (e.g., Medtronic’s MiniMed 670G). Showing a “FACE PALM” slide, she noted that this “system” framework could hamper innovation and product iteration. Dr. Lias highlighted Dexcom’s pump partnerships with Animas and Tandem as two examples, which were hampered by months of legal contracts and ironing who is responsible when things go wrong – a very inefficient process. Dr. Lias envisioned a day with standardized, interoperable devices, allowing patients to swap in different system components (pumps, CGMs, and algorithms; see picture below). She outlined a list of current challenges that FDA and the scientific community/industry must address (see table below), noting this might take ~10-15 years to totally solve though certain pieces could be accomplished in the short term. [Many in the audience thought it could be faster.] It was clear that device communication standards are mission critical in all of this, leading us to wonder how Dr. Joe Cafazzo’s and Melanie Yeung’s work in Toronto on diabetes device standards could be integrated into commercial products. Dr. Lias concluded that FDA wants to be the “lead penguin” on artificial pancreas component interoperability, which might even include forward-looking guidance to pave an easier path for interoperable products. Nice! We were highly impressed with her open and forward-looking perspective, and wonder if industry will consider more modular approaches to AP system design. Plug and play component AP systems could significantly enhance patient choice, spur innovation, and improve automated insulin delivery far more quickly than the current paradigm. This will be a further topic of discussion at the FDA/NIH Artificial Pancreas workshop in Washington, DC on July 6-7.

  • “Mobile phones are a must. We’re very pro putting artificial pancreas systems on mobile phones.” The strikingly positive commentary was great to hear, since this has been an open question mark – what are the risks of patients dosing insulin from a phone? The devil is of course in the details here: will the algorithm sit on the phone and communicate to the pump and CGM separately, or will the phone simply act as a window to what’s happening in the fully integrated pump? We were definitely encouraged to hear optimism on this front, since it opens up so many advantages to developers: faster iteration (software updates), remote monitoring, better user experience, etc.

  • Dr. Lias succinctly summarized the challenges around modular, component artificial pancreas systems, with a clear emphasis on the lack of device communication standards.  

Challenge

FDA

Industry/Scientific Community

Data format

Need assurance that devices compatible – standards will facilitate

Need to develop standards? Discuss needs

Secure/private communication protocols

Need assurance that devices secure – standards will facilitate

Standard under discussion, discuss needs

Component device modifications

Need assurance that device modifications will not have unintended impact on systems

Need to develop standards?

Post-market responsibility

Need to define who is responsible in case of component/system failure (investigations, complaints, etc.)

Should provide suggestions/input

Mobile phone capabilities (alarms, app priority)

FDA encourages use of mobile apps

Need to address current limitations and difference between operating systems

Operating system updates

FDA already has efficient pathway developed

Needs to identify technical challenges to allow multiple systems

Academic artificial pancreas update

Trang Ly, PhD (Stanford University, Palo Alto, CA)

Stanford’s Dr. Trang Ly provided an outstanding overview of artificial pancreas systems, calling the technology “transformative”; characterizing first-gen product algorithms as “conservative”; and summarizing systems’ strengths, areas for improvement, and algorithm nuances (see tables below). Dr. Ly argued that the biggest challenge Medtronic’s MiniMed 670G faces is managing expectations (“This is not going to cure you. That will be their biggest problem”). She also noted that MiniMed Connect doesn’t work with the 670G right now (and Bluetooth is not built in), and the lack of an adjustable glucose target needs to improve. On the bright side, she noted that the 670G is a very nicely integrated system and the pivotal trial is complete, putting it first in line to market. Dr. Ly said some of the next challenges for closed loop systems include user interface and human factors: “These will not last on the market if we don’t see improvement in user interface and how a person interacts with the system.” Totally agree there, and this is where a multitude of companies selling products is going to drive innovation and better all-around user experiences. Dr. Ly also highlighted room for improvement in fail-safe modes – “going back to pump mode with preset settings is not necessarily safer.

System Strengths and Challenges

 

Medtronic MiniMed 670G

UVA / TypeZero

Cambridge

Harvard

BU

Strengths

Integrated system

124 patients, three-month pivotal trial

Six-month data, n=13

Remote monitoring

Software updates

Pump agnostic

Three months, n=33

Lots of clinical data

Run-to-run optimization currently being tested

N=48 over 12 days

Integrated, system

Adjustable set-point (“really important”)

Meal adaptation

Challenges

Managing expectations

Need remote monitoring (won’t work with MiniMed Connect)

Adjustable set point

Moving to commercial platform

Connectivity

Set-point may be too high during day

No commercial partner

No remote monitoring

System not integrated

No commercial partner (different algorithm from Insulet/Mode AGC)

No remote monitoring

Need longer studies

Glucagon – long-term effects

Design being worked out – IOB

Need longer studies

  • Initialization Parameters: BU’s Bionic Pancreas has the clear advantage here, requiring only weight to start closed loop, and then it adapts over time. Initialization could play an important role in who these systems appeal to (current pumpers vs. MDIs) and how hard they are to train providers and patients on.

 

Medtronic MiniMed 670G

UVA / TypeZero

Cambridge

Harvard

BU

Parameters to Start

TDD

Basal

I:C

ISF

Sensor for 48 Hours

 

TDD

Basal

I:C

ISF

Weight

 

TDD

Basal

I:C

ISF

Weight

 

TDD

Basal

I:C

ISF

Weight

  • Setpoint (Glucose Target): Cambridge, Harvard, and BU have the most aggressive targets; UVA/TypeZero is notably conservative during the day (160 mg/dl).

 

Medtronic MiniMed 670G

UVA / TypeZero

Cambridge

Harvard

BU

Setpoint

120 mg/dl

Day: 160 mg/dl

Night: 120 mg/dl

Treat-to-target: 104-131 mg/dl

Optional individual setpoint

Day: 80-140 mg/dl

Night: 90-140 mg/dl

Insulin and Glucagon setpoint is 100 mg/dl

Adjustable by user up to 130 mg/dl

Exercise

Temp target: 150 mg/dl

Safety: no more than usual basal

Exercise-specific setpoint

 

 

  • Automated Component: Most of the systems dose every five minutes, and most use MPC. It’s hard to know how meaningful these algorithm differences are before seeing them head-to-head in clinical trials.

 

Medtronic MiniMed 670G

UVA / TypeZero

Cambridge

Harvard

BU

Algorithm

PID-IFB

Control to Range

MPC

MPC

MPC: Insulin
PD: Glucagon

Dosing

Microbolus, 5 minutes

Basal: 5 mins

Correction: 1 hr

Insulin infusion rate: 10 mins

5 mins

5 mins

System-calculated meal dosing

#OpenApS and the Drive to DI