February 14-17, 2018; Vienna, Austria; Full Report – Draft

This report includes our coverage of the 11th Annual ATTD conference. Immediately below, you’ll find our eight top themes from the meeting, followed by highlights in the following categories: (i) Automated insulin Delivery; (ii) CGM; (iii) Pumps and Infusion Sets; (iv) Digital Health; (v) Insulin Therapy and Diabetes Drugs; (vi) Beyond A1c and Additional Topics; (vii) ATTD Yearbook; (viii) Startup Showcase; (ix) Exhibit Hall.

This report adds and expands a few talks not covered in our daily reports; these talk titles are denoted with blue highlighting.

Enjoy! We already cannot wait for ATTD 2019 in Berlin, Germany from February 20-23.

Themes

1. Automated insulin delivery (AID): pivotal studies for Tandem PLGS, 670G pediatrics; Roche first to commit to JDRF’s open protocol; Insulet, Beta Bionics move ahead

• ATTD 2018 shared positive results for two (!) AID pivotal studies – Tandem’s predictive low glucose suspend (Basal-IQ) and Medtronic’s MiniMed 670G hybrid closed loop in 7-13 year-olds. Tandem’s Basal-IQ showed a 31% reduction in time <70 mg/dl, meeting its primary endpoint in a very well-controlled study population. As of March 1, Basal-IQ had been filed with FDA, with expectations maintained for a summer 2018 US launch. Medtronic 670G pediatric (7-13 years old) pivotal results were also a major highlight, resembling the adult data we saw at ADA 2016: compared to a two-week open-loop run-in period, 670G drove a 0.4% reduction in A1c in the pediatric population (baseline: 7.9%); time-in-range (71-180 mg/dl) improved from 56% to 65% (a strong +2 hours/day); and time <70 mg/dl declined from 4.7% to 3.0% (-24 mins/day). Medtronic filed the expanded indication with FDA in January, and the 2-6 year old trial is completing soon. Following ADA two years ago – where we first saw the 670G adult/adolescent pivotal results – it was notable to see two (!) pivotal studies for commercial products at this year’s ATTD.

• We also saw encouraging AID studies of Insulet’s Omnipod Horizon, Tandem’s TypeZero-Dexcom G6 hybrid closed loop (at ski camp), and Beta Bionics’ Bionic Pancreas with Zealand’s liquid-stable glucagon. It is outstanding to see commercial products from all of these companies moving forward, which should provide a variety of form factors, levels of user burden, and choices for patients. It was particularly notable to see normally-stoic Dr. Boris Kovatchev (University of Virginia) visibly excited about the Tandem/Dexcom/TypeZero integration: the system drove a six-hour improvement in time-in-range (!) at ski camp, along with quite seamless connectivity. See our updated automated insulin delivery competitive landscape for a rundown of products and recent timing.

• Roche became the first company to openly support JDRF’s initiative to accelerate “Open Protocol” AID systems, meaning that it will provide seamless, secure, interoperable connectivity with other devices and smartphone apps (e.g., Bluetooth). We’ve since learned that people in the DIY community have been invited to meet with Roche in Europe in light of the initiative. Roche’s commitment is a big statement for the field and a move we hope other companies will follow – particularly via the new integrated CGM (iCGM) FDA pathway that came with clearance for Dexcom’s interoperable G6. While it will still take some time, the field is hopefully moving towards an interoperable ecosystem where AID system components can be swapped in and out – without requiring separate regulatory approvals or partnership contracts.

2. Clinical decision support regulatory milestones: DreaMed Advisor Pro CE Marked for Pump Settings, Glooko MIDS FDA-cleared for basal titration

• DreaMed’s Advisor Pro, which recommends specific pump settings adjustments based on CGM trends, received a CE Mark during ATTD, is slated for a soft European launch this summer, and has been submitted to FDA – a major milestone for the company. The software gives healthcare providers detailed pump basal, insulin:carb, and correction factor adjustment recommendations based on CGM data – the user experience on the Glooko web-based Population Tracker looks great. A seven-center, n=112 Helmsley-funded study is ongoing in the US, Europe, and Israel, with results expected by the end of 2018.

• Glooko CEO Mr. Rick Altinger also announced that the company’s Mobile Insulin Dosing System (MIDS; basal insulin titration) was cleared by the FDA after a ≥nine-month review. MIDS analyzes patients’ fasting blood glucose levels and recommends insulin dose adjustments based on the provider’s pre-configured treatment plan. No launch details have been shared at this point. Glooko engaged in 18 months of design and development, invested “tens of millions of dollars” in the system, and did many rounds of user experience design reviews, human factors studies, pre-market programs, and feedback sessions. We look forward to watching this launch in Glooko’s platform, which is now used by >7,000 providers and >1.5 million people with diabetes.

• We’re thrilled to see this area expanding and look forward to seeing how decision support reduces provider hassle, freeing up physicians to spend more time on the issues that truly matter to their patients. There will certainly be an education process to convince providers that decision support makes a difference –  particularly early adopter clinicians who might quip, “That’s great for PCPs, but I already know how to adjust insulin doses.” (This is not speculation, either – we heard remarks like this from some clinician attendees in the DreaMed workshop.) We also wonder how much of a barrier fee-for-service reimbursement will be here, as physicians currently get paid for seeing people face-to-face and occasionally reviewing their data. That said, we continue to hear about providers feeling quite burned out, so any software tools that make them more efficient and effective should be welcome additions. Hopefully, providers will be incentivized (at every level of healthcare) to minimize time spent on tasks that a computer could do near-instantaneously, and to maximize time spent working through pain points with patients. In one scenario, we could even imagine decision support propelling a shift toward a value-based system if it grants providers and payers greater confidence in clinical care.

• What are the different varieties of patient-facing decision support, and how do they compare in terms of effectiveness? This question was raised by a poster authored by investigators from Lilly’s Cambridge Innovation Center and Joslin Diabetes Clinic, in which patients were given FreeStyle Libre plus real-time contextual prompts from an app. Following a glycemic excursion, the app encourages users to enter the suspected cause, be it food, insulin, etc. At 14 weeks, mean A1c dropped 0.5% (baseline: 8.0%); importantly, changes in insulin doses were not responsible for the improvement. Might simply prompting users to reflect on the cause of an excursion improve self-management behaviors? Is there a group of patients for whom this is the optimal form of support? How much more effective is this real-time reflection than that encouraged by weekly retrospective email summaries from Dexcom Clarity? How does the strategy compare to more explicit instruction, such as insulin dose advice, and retrospective tips based on patterns (such as Medtronic’s Sugar.IQ; “you tend to go low when you eat tuna on a Sunday afternoon”). We’d argue that real-time CGM data is the dominant focus for most users, leaving a huge untapped potential in retrospective CGM data. There is serious behavior change value in shrinking the gap between retrospective insights and real-time decision making. For example, how can a retrospective pattern – “you go high on Tuesday mornings after your 8am high-intensity exercise class” – be delivered automatically and closer to the point of decision making (i.e., right before the class or right after it)? We think Medtronic/IBM Watson’s Sugar.IQ has made nice progress on this front, but more is needed from everyone in the field.

3. Next-gen product updates: Unomedical/Medtronic Mio Advance set; Dexcom G6 no-cal allows for optional cals; Metronom’s stealth CGM

• Unomedical’s all-in-one, fully hidden-needle Mio Advance infusion set inserter debuted with distribution partner Medtronic – what an awesome improvement! It’s difficult to imagine a more user-friendly device: The MiniMed Mio Advance is ready-to-use upon unwrapping, inserts with the single push of a button, hides the needle the entire team, and can even be inserted one-handed for difficult-to-reach areas (see the demo here). It looks great for pediatric patients and elderly patients who may struggle to insert their infusion sets independently. Unomedical shared that it’s available in Europe, the Middle East, and Africa. The rep told us it’s been the “best feedback ever” about an infusion set, a major win for Unomedical and certainly very, very strong competition to BD’s yet-to-relaunch FlowSmart set. Mio Advance has undergone a limited launch in the UK, Italy and the Netherlands, with Canada, Hong Kong and certain Europe/Middle East/Africa launches expected by the end of April. Availability in other countries is expected later in 2018.

• Ahead of the earlier-than-expected FDA clearance in March, we got a comprehensive Dexcom G6 update at ATTD – including news that an optional calibration can be entered into the factory calibrated sensor (e.g., in the occasional case of an inaccurate sensor). The product continues to look outstanding and will update every aspect of Dexcom CGM – some very meaningfully, like the new sensor and inserter. We also learned that a two-hour warmup is expected for the no-cal version, a big improvement over Abbott’s 12-hour no-cal warmup in the US. The G6 accuracy data shown at ATTD was from “a combination of recent clinical studies” – overall MARD 9.0%, 94% of points within 20/20, a Day 1 MARD of 11.2%, and 94% within 20 mg/dl in hypoglycemia. Mr. Leach also confirmed in Q&A that direct-to-Apple-Watch connectivity is not under FDA review, contrary to what the New York Times reported in December.

• In the exhibit hall, stealth CGM startup Metronom shared plans to submit a CE Mark in 2Q19 for its 14-day wear, optical-based, factory calibrated CGM. Notably, the technology includes a durable transmitter that sends data via Bluetooth to phone and watch apps, and perhaps most intriguingly, the company intends to print the sensor like a test strip, enabling lower expected cost of goods.

4. Rising Beyond A1c discussion: Medtronic + AGP? Dr Roy Beck on “GMI” and Dr. Danne on the “Death Star” (A1c)

• Calls for outcomes beyond A1c grew even louder at ATTD, signaling continued momentum for the movement. We learned that Medtronic became the last major CGM company to adopt the standard one-page AGP report, Dr. Rich Bergenstal proposed the use of CGM in all CVOTs, Dr. Thomas Danne dipped into his Star Wars fandom to liken A1c to the “Death Star,” and Dr. Roy Beck gave a comprehensive overview on CGM outcomes beyond A1c at diaTribe Foundation-sponsored event. Many of the remaining questions on the movement were posited during the course of Dr. Beck’s outstanding lecture (see his slides here): (i) Now that the field has agreed on glycemic ranges, what are “acceptable” benchmarks of time to spend in those ranges?; (ii) How can FDA’s drug division be convinced that CGM metrics matter, particularly time in hypoglycemia <70 and <54 mg/dl?; and (iii) the fate of “estimated A1c” on the AGP report. On the latter, Drs. Beck and Bergenstal have been talking to the FDA about the right terminology to replace “eA1c,” which currently confuses some patients and has been removed from Dexcom Clarity. The winning rebrand so far is “Glucose Management Indicator” (GMI) – we like it!

5. HypoDE: CGM reduces severe hypo in MDIs with impaired awareness (HypoDE), building evidence base further

• With the HypoDE study presented at ATTD and simultaneously published in The Lancet, there’s now excellent evidence supporting CGM’s efficacy in patients using MDI with hypoglycemia unawareness. In the six-month, 12-center trial, CGM significantly reduced hypoglycemia incidence (≤54 mg/dl for at least 20 minutes) by 72%. Severe hypoglycemia was nearly halved with CGM, a major win for cost-effectiveness. Hopefully, the data will help improve the case that CGM should be standard of care in people with hypoglycemia unawareness – the technology still only got a grade of C-level evidence in the 2018 ADA Standards of Care! HypoDE adds to the growing list of studies published in the past year-and-a-half supporting the use of CGM in specific populations: pregnancy (CONCEPTT), MDI users with both type 1 and type 2 diabetes (GOLD and DIaMonD), and pump patients with impaired hypoglycemia awareness (IN CONTROL). We look forward to additional studies in special populations, such as SENCE (CGM in children under eight years old), CITY (CGM in adolescents), and WISDM (CGM in the elderly).

6. Real-world big data: FreeStyle Libre in 250,000+ users; Dexcom G5/Clarity in 50,000 users; MiniMed 670G in 14,000+ users

• We’re elated to see real-world outcomes data becoming more common at diabetes conferences, which could be a driver of reimbursement and adoption. At ATTD, we saw encouraging real-world results from Abbott FreeStyle Libre (>250,000 users), Dexcom G5/Clarity (50,000 users), Medtronic MiniMed 670G (~14,000 US users), Sanofi Toujeo (10,458 type 2s), Medtronic Guardian Connect (2,541 users), and Cellnovo (n=599) – all demonstrated the value of characterizing how people are doing at scale in real life. Within diabetes technology and digital health, we’ll be interested to watch how the field of evidence unfolds in the coming years – how should companies balance between randomized controlled studies and real-world evidence? The field is certainly moving too fast for traditional pharma RCTs, and devices/apps arguably have too many use cases for long-term trials to give true indications of real-world effectiveness. (Plus, it’s typically not possible to have a double-blind study, as it is in drug studies). That said, RCTs are of course still important, especially in an age where it’s easier to collect real-world user data, but much of it is from uncontrolled studies. We’d love to know how large payer bodies and physicians are thinking about real-world data + RCTs, and how they take them into account for coverage and prescribing decisions.

7. Cost-effectiveness of diabetes technology: Irl Hirsch on the CVOT era, Diabeter learning, pumps in type 2, G5 vs. SMBG

• There was a greater emphasis on cost and health economics at this year’s meeting than we’re accustomed to, a trend that is likely to continue. In this report, we highlight Irl Hirsch’s musings on cost effectiveness in light of positive CVOTs, Diabeter’s estimated $75,000 in cost-savings per patient over a lifetime, a Medtronic analysis of the cost-effectiveness of pump therapy, and a CGM poster showing the incremental cost-effectiveness ratio for G5 Mobile vs. SMBG. In parallel with the diabetes technology field, it’s terrific to see ATTD has matured to discussing cost-effectiveness– the pressure is only rising for companies to show excellent value. Plus, as more tech and drug and combination solutions become available, showing cost-effectiveness will give products a substantial competitive advantage.    

8. Insulin pen dose capture: growing number of competitors, but no commercial environment (yet)

• We saw/heard four dose capture devices for insulin pens at ATTD. Still, this is far from a commercial market at this stage – will this change by ATTD 2019? Three of the products, including Insulclock, Diabnext, and Biocorp, were in the exhibit hall and completely new to us, while we also covered a second Common Sensing/Joslin poster (the first being at ADA). Companion Medical’s InPen (durable, reusable) is on the US market now, and Common Sensing’s GoCap is in a gradually-expanding beta program in the US. There has never been more interest or discussion of this area, but it’s still not at a commercial stage – much like automated insulin delivery’s state 3-5 years ago. Though all of the insulin players have invested here, nothing has launched at this stage – will we see more movement by ATTD 2019? We certainly hope so, given the huge potential to improve outcomes. See our smart pen and cap competitive landscape.

Detailed Discussion and Commentary

1. Automated Insulin Delivery

Tandem PLGS pivotal: 31% drop in <70 mg/dl (-19 mins/day), no increase in 180 mg/dl, no nuisance alarms; well-controlled users; FDA submission this quarter (1Q18), summer launch

Dr. Bruce Buckingham presented positive results from the pivotal trial (PROLOG) of Tandem’s predictive low glucose suspend device with Dexcom’s G5 – the system drove a 31% reduction in mean time <70 mg/dl, meeting its primary endpoint. Dr Buckingham praised how the suspensions occur without alarms, operating in the background – yes! Tandem expects an FDA submission this quarter (1Q18) and launch is still slated for summer 2018, pending approval – with these results, this timeline feels very reasonable, given the product’s low risk, obvious benefit, and how quickly Tandem has moved this program ahead (the feasibility study was shared at ADA 2017, and this study only started last August). The algorithm, now branded “Basal-IQ” and embedded in the t:slim X2 pump, was tested in a randomized crossover, home pivotal study that included two weeks of baseline data collection, followed by three weeks of PLGS vs. three weeks of sensor-augmented pump (SAP) therapy with t:slim X2/G5 (or vice versa). The primary outcome was time <70 mg/dl, and the study enrolled 103 participants in a wide age range (6-72 years; mean age: 24 years) and very engaged in their diabetes (baseline A1c: 7.3%, 83% pump user, 84% CGM user). Unlike other PLGS studies, this study was not enriched for hypoglycemia, nor did it include an in-clinic hypoglycemia induction.

• Mean time <70 mg/dl declined from 4.5% during SAP to 3.1% with PLGS, a 31% reduction (-19 minutes/day; p<0.001). Though the absolute reduction was small, we’d point out these rates of hypoglycemia were quite low, and the comparator arm was using Dexcom G5/t:slim X2, already experienced with pump and CGM, and came with baseline time-in-range at 64%. The median reduction in time <70 mg/dl was smaller: from 3.2% during SAP to 2.6% during PLGS (-9 minutes/day). Interestingly, more benefit from PLGS came during the day: -14-minutes vs. -9 minutes at night.

• For those experiencing >5% time <70 mg/dl at baseline, the improvement with PLGS was bigger – a 40% reduction in hypoglycemia from 6.7% during SAP to 4% with PLGS (-39 minutes/day). This group was just under 30% of the study population, explaining the smaller overall effect size. For those experiencing <5% in hypoglycemia at baseline, PLGS took hypoglycemia from 2.7% to 1.9% (-12 minutes/day). Other subgroup analyses by high/low baseline A1c and adult/pediatrics revealed the system was equally effective.

• Time-in-range improved very slightly from 64% on SAP to 66% on PLGS (+29 minutes/day; p<0.001) – again reinforcing how well this study population was doing at baseline. Mean glucose did not change – 159 mg/dl on both SAP and PLGS.

• Suspensions of insulin delivery occurred on 91% of days, with a mean of 5.7 suspensions per day. The mean duration of suspension was only 18 minutes, but that still meant a cumulative total suspension time of 104 minutes per day. For a group with more hypoglycemia, we’d imagine the suspension data and time <70 results would be more dramatic. The study had one severe hypoglycemia event in SAP and none on PLGS. 

• The study had a 99% completion rate, ~95% CGM usage, and strong system usability ratings: >88% of participants agreed/strongly agreed that they would like to use the system frequently; thought the system was easy to use; felt very confident using the system; did not need the support of a technical person to use the system; and did not need to learn a lot before getting going with the system.

• As described at ADA 2017 (when the first feasibility data was shared), the Tandem Basal-IQ (PLGS) algorithm is very straightforward: it uses the last four sensor glucose values to predict the sensor glucose 30 minutes into the future. Insulin delivery is suspended if the predicted glucose is <80 mg/dl OR the observed sensor glucose falls below 70 mg/dl. Insulin delivery resumes when the sensor glucose is rising OR if suspension exceeds 120 minutes (to prevent rebound hyperglycemia).

MiniMed 670G pivotal in 7-13 years: A1c drops 0.4% (baseline: 7.9%), +2 hours/day in-range (56%->65%); submitted to FDA last month

Dr Bruce Buckingham presented long-awaited, positive pediatric (7-13 year-old) data on the MiniMed 670G/Guardian Sensor 3 hybrid closed loop. Medtronic announced during ATTD that it was submitted to FDA in January, which would expand the 670G indication from 14+ years to 7+ years. The single-arm, three-month, 105-participant peds study showed similar outcomes to the adult/adolescent study presented 20 months ago – compared to a two-week open-loop run-in period, 670G drove a 0.4% reduction in A1c in the pediatric population (baseline: 7.9%); time-in-range (71-180 mg/dl) improved from 56% to 65% (a strong +2 hours/day); time <70 mg/dl declined from 4.7% to 3.0% (-24 mins/day); and time >180 mg/dl improved from 39% to 32% (-1.7 hours/day). The A1c endpoint and all CGM metrics were highly statistically significant in favor of the 670G (p<0.001) – we only wish Medtronic had reported with the consensus definitions for time-in-range and hypoglycemia! (Perhaps the study was already underway…) The percentage of patients with an A1c <7.5% improved from 36% at run in to 51% at study end; the higher the baseline A1c, the more pediatric patients benefitted from the 670G. In line with the A1c improvement, mean glucose improved from 169 to 162 mg/dl, with a slightly bigger benefit overnight – 166 to 155 mg/dl (p<0.001). Coefficient of variation improved slightly, from 40% to 39% (p=0.01). The modal day plots we saw in the adult/adolescent study were nicely replicated here, showing a tightening of glucose levels at all times of day on the 670G, and especially overnight. Notably, patients gained ~5% of their body weight during the three-month study (+5 lbs from a baseline of 94 lbs), along with adding 2.8 units/day to their daily dose on 670G (baseline: 36 units) – we wonder how kids’ eating patterns changes on the device! There was no DKA or severe hypoglycemia, and patients were in Auto Mode 80% of the time – with the average age at 11 years, we’d guess parents were likely managing a lot of the 670G interaction. Overall accuracy for Guardian Sensor 3 was higher than in prior studies: MARD of 11.9% (n=3,271 paired points), and only 1% of the paired points were <70 mg/dl; the number of daily fingersticks was not reported, but was presumably at least four/day and perhaps more. Dr Buckingham concluded that “the judge of these systems is whether you continue to use it” – notably, 97% of pediatric participants enrolled in the 670G continued access phase, notably higher than the “>80%” that continued in the adult/adolescent study. There is an ongoing study in 2-6 years, which would be a big win for many parents experiencing many sleepless nights.

• Dr. Buckingham was quite excited about these pediatric results, and his comparison to the adult and adolescent pivotal data (shared at ADA 2016, published in JAMA and DT&T) was one of our favorite slides in the talk. As the table below shows, Auto Mode Use and time-in-range varied a bit between the age groups, while A1c reductions were very much in line (0.4%-0.6%). Overall, it’s very positive to see the consistent improvements across ages, especially the more challenging pediatric and adolescent groups.

	Auto Mode Use	A1c Change (Baseline)	% 70-180 mg/dl Baseline –> 3 Months
Adults	88%	-0.5% (7.3%)	69% -> 74%
14-21 years	76%	-0.6% (7.7%)	60% -> 67%
7-13 years	81%	-0.4% (7.9%)	56% -> 65%

• The single-arm, three-month, multicenter study occurred at nine centers (8 US, 1 Israel), mimicking the adult/adolescent study design – including home, in-clinic, and hotel portions. Children had to be 7-13 years, A1c <10%, pump therapy for >6 months (with or without CGM), and a minimum total daily dose of >8 units per day.

Questions and Answers

Q: How were the gain (aggressiveness) settings adjusted?

Dr. Buckingham: They are adjusted each night at midnight based on total daily dose and glucose values. The adjustment is automatic and takes into account data from the previous six days. Once on the system, it continues to update at midnight. Some of these kids started out on the system several years ago, and now they’ve gone through puberty – they’ve had dramatic changes in insulin requirements, and the settings and the system cope with that.

Dr. Roman Hovorka (Cambridge): It’s great to see data moving into younger populations. I might be difficult here... I love these technologies to work, but this was a single arm study – before/after. We know very well if people enroll in a study, their glucose control will improve. How much of the benefit was due to the 670G? Can we really reliably say these improvement can be attributed to the device?

Dr Buckingham: I’d make two points: the data Dr. Fran Kaufman presented for the commercial use of the system in a non-study environment showed similar improvements, which continued over time. There is also a randomized trial being conducted, but it will take a while to get results completed.

Dr. Hovorka: But can we say the 670G reduces A1c and increases time-in-range? Can we reliably say so based on this study?

Dr Buckingham: We can only say it reduced from baseline.

Dr Hovorka: I agree. 

Dr. Fran Kaufman Real-World 670G Data From ~14k Patients Broken Down by Age; Medtronic’s “Best Practices” for Glycemic Goals, Time in Auto Mode, and Time Wearing Sensor

Medtronic Diabetes CMO Dr. Fran Kaufman presented the latest set of real-world 670G data uploaded voluntarily to CareLink by 13,906 US patients (of a possible “over 25,000” now using the system). The user base in the US has been augmented by ~5,000 in the past ~three months, up from 20,000+ in November. As we’ve come to expect, the system’s real-world performance continues to largely resemble that in the pivotal, particularly in adults. Across all ages (7+; presumably the 479-patient 7-13 age group represents off-label use), auto mode time in 70-180 mg/dl was ~71%, time <70 mg/dl was ~2%, time <54 mg/dl was 0.49%, and time >180 mg/dl was ~27%. The largest divergence from the pivotal study was the ~96 minutes fewer per day spent in auto mode in the real world (from 87% in the three-month pivotal to 80% in real-world use). Unsurprisingly, the pediatric and especially the adolescent groups had lower time in range than the other age groups, but still fared significantly better on hybrid closed loop – 7-13 year olds and 14-21 year olds saw time in range increase from 52% to 65% (+3.1 hours/day) and from 53% to 63% (+2.4 hours/day), respectively. In this cohort, people ≥60 years old stayed in auto mode for the longest, at ~20.4 hours per day, and also spent the most time in range, at ~75% (up from baseline of 68%). These data suggest that 670G consistently improves glycemia across all age ranges, and supplements the pivotal data in 7-13 year olds presented by Dr. Bruce Buckingham on the same day (see above). As for the 2-6 year-old cohort, Dr. Kaufman said that a seven-site, n=50, three-month study is in the process of wrapping up. We wonder if we might see this data later this year, perhaps at ADA?

• Based on observations from this real-world data set and the pivotal studies, Medtronic came up with “best practices” for times in ranges, in auto mode, and wearing the sensor. The picture below details the following recommendations: Time between 70-180 mg/dl at >70%, time 50-70 mg/dl at ≤3%, and time <50 mg/dl at ≤1%. In order to achieve these, Medtronic’s analytics team recommends staying in auto mode >80% of the time and wearing the sensor >85% of the time. We thought this relatively simple analysis was helpful, as it gives providers and patients some specific goals to aim for. The difficulty with targets, of course, is that they need to be individualized (e.g., should they be different for adolescents?), and they could lead to feelings of failure if they are not achieved. On the other hand, having an idea of where the “typical” patient falls and how that correlates with outcomes and behaviors (including something as simple as sensor wear time) is valuable and needed to help guide therapy and identify problem areas. We wonder how glycemic goals should/would change for type 1s using different device combinations and type 2s on various device and drug combos.

Roche First Company to Join JDRF Initiative to Accelerate “Open Protocol” automated insulin delivery, big interoperability win!; Value-Based, Integrated Diabetes Care Update

While displaying a slide that read, “Shaping the future of diabetes with JDRF,” Roche Global Head of Diabetes Care Mr. Marcel Gmünder announced that his company has “decided to join the JDRF effort for an open DIY artificial pancreas environment.” Roche is the first company to publicly disclose participation in JDRF’s initiative to accelerate “Open Protocol” AID systems, meaning that it will provide seamless, secure, interoperable connectivity with other devices and smartphone apps (e.g., Bluetooth). This is a major interoperability win from one of the largest device players in diabetes, and it represents the first domino to fall in JDRF’s plan to facilitate an open AID ecosystem. Ultimately, it could drive a whole new paradigm of device innovation, where companies supply components/algorithms and patients can mix and match the devices/software they like best. Roche is currently developing a 180-day AID system with Senseonics’ implantable Eversense XL sensor and a TypeZero algorithm, and may also have plans in store for automating delivery from the Solo patch pump (expected to launch in the EU this year). It’s impossible to know how quickly, but we hope other companies will follow Roche’s plunge – Tandem and Insulet seem well positioned for this initiative, as both have Bluetooth-enabled pumps (t:slim X2 is out, Omnipod Dash is under FDA review). Patients will win in a plug-and-play ecosystem, meaning industry should too – the ecosystem has potential to add far more value to devices than each company on its own. There are still questions pertaining on regulatory, liability, and postmarket surveillance, but JDRF has said it will coordinate with regulators and legal advisors to develop a predictable FDA pathway and frameworks. FDA’s Drs. Courtney Lias, Stayce Beck, and team have made it clear that AID component interoperability is a big goal – we can’t wait to see how quickly it happens and which companies drive the most innovation in this new paradigm. We firmly believe in this direction, given the pace at which CGM and algorithms are moving, the impressive efforts in the DIY community, and how hard it has been for others besides Medtronic to push commercial AID systems over the finish line. We’re elated to see Roche take the first plunge!

• Roche’s value-based, device-agnostic, integrated diabetes care offering with coaching and provider decision support is starting to resemble some other emerging programs (e.g., Onduo, Virta, Diabeter), which all take on patient care and sell outcomes to payers and employers. The slide below shows how Roche intends to market the mySugr bundle (already reimbursed by major German payers and with US payers to come online in 1H18) as device agnostic – the slide depicts Medtronic, Dexcom, Abbott, and Roche devices – and with insights for population management and EHR integration. The presentation also didn’t mention A1c once, but focused on “True relief” and more time-in-range – nice! On the healthcare provider side, Roche VP Mr. Tim Jürgens introduced the professional platform, a “hub to drive decision support and therapy efficiencies” set to launch later this year. A short walk-through displayed features including: (i) pattern detection; (ii) “meaningful” graphs (data download for different devices; AGP has been licensed); (iii) connectivity (one single hub for all devices); (iv) communication (more intensive monitoring of patients between face-to-face visits); and (v) population management (patients prioritized based on critical situation; real-time tracking of test strip consumption). We remain optimistic about this new-look, innovative Roche, though spinning up the business models is where the real test will be. As different companies and programs develop and iterate new care models, what best practices will surface? How will traditional modes of healthcare delivery adapt?

  • “We need to give tools to healthcare providers. We need to move toward outcomes-based models, demonstrate that we are actually improving outcomes. Bringing relief to patients, which is the ultimate outcome, because with relief, you can be sure that the medical outcome is coming as well.”

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    “We are a firm believer in bringing partners together. No company has all answers and tools for a patient. We are able and willing to bring those things together.”

  • “We cannot have a situation where payers are not able to pay for the relief that is needed.”

• Enthusiasm for mySugr, which now has over 1.4 million users (higher than the ~1.2 million users shared by Mr. Anton Kittelberger on day #1) bubbled over in Roche’s presentations. Mr. Gmünder called the app “our main interface and basis for interaction with patients” and “an engaging and intuitive tool,” and Mr. Jürgens added that it is “the leading management platform” and “basically a little clinic in the hands of the patient.” Wow! So great to hear and we salute again the creators …

Dr. Kowalski on DIY AID: “Just Do It!...Don’t be Scared. It’s Time to Move to a New World of Diabetes Treatment. It Works.”

A fired-up Dr. Aaron Kowalski (JDRF) made an extremely compelling call for patients and providers to “cross the chasm” and take up hybrid closed loop: “Many are on other side of the chasm. People are there saying, “it’s far, it’s scary.” But I’m over here, and let me tell you, it’s beautiful … To take a line from Nike, just do it! Come on guys, it’s time. Don’t be scared. It’s time to move to a new world of diabetes treatment. It works. You’ve seen the presentations here. We can do this. Your patients need this. It’s safe. It’s going to happen. What are we waiting for?” “People ask, ‘is it dangerous? Unregulated?’ My answer is this train has left the station. If this community [DIY] is driving, innovating, and meeting patient needs, then we as an industry, clinicians, and scientists, need to find a way to make this as safe as possible and how to learn from it.” To ensure that the audience could trust that he was putting his money where his mouth is, Dr. Kowalski proceeded to display his personal Dexcom Clarity AGP featuring his past three months on Loop: The profile was flat, with a mean glucose of 145 mg/dl, time-in-range of ~72%, time <70 mg/dl of 4.4%, and time >180 mg/dl of 24%. He pointed out, “overnight control with a hybrid closed loop is absolutely stunning. It is powerful.” We truly appreciated this assertive, open move, and heard audible gasps from the audience as the JDRF’s Chief Mission Officer so directly and personally endorsed the DIY movement (while backing it up with strong glycemic data) – Adam and Kelly and many others have seen similar outcomes (though we point out this does require using old pumps – Kelly’s is broken, with no way she knows of to fix, while she waits for another closed-loop trial). Importantly, Dr. Kowalski emphasized that JDRF will not waver in its support of “traditional” industry development of closed loop systems – the DIY systems are, no doubt, driving innovation. He also discussed JDRF’s Open Protocol initiative, possible consequences of automated insulin delivery in the clinic, how the field should learn from CGM’s evolution, and payer considerations/remaining hurdles. He concluded the impassioned talk similarly to the way he opened it: “Think about the need for automated insulin delivery. We have to do it.” We heartily agree and are especially impressed with not only the far lower percent of time in hypoglycemia that 670G closed loop and DIY patients are experiencing, but also the “soft landings” that we hear about and beautiful night-time traces in particular.

• On JDRF’s initiative to accelerate “open protocol” automated insulin delivery, Dr. Kowalski said: “JDRF is trying to chart how to make an open platform more accessible. I call it bringing it above the table. Right now, it’s below the table. We have already retained experts to help us with the legal and regulatory changes – let’s be honest, this is totally outside the box. But I think there’s an opportunity here. The DIY community has blazed a trail that we hadn’t anticipated, and it’s great.” We were delighted that in the very next talk, Roche Diabetes management announced that it would be JDRF’s first industry partner to sign on to the open protocol initiative (see above) and we expect many more.

• Dr. Kowalski pointed out that conversations in the clinic change when the patient is on automated insulin delivery: “With my doctor, the discussion is different than it used to be. There’s a lot of conversation around meal-time issues. I personally think you’ll see many more people taking up pump therapy. I’ve personally had many friends move from MDI to pump to go onto 670G or a DIY system. The benefit of pumps now that we’re automating insulin has gone up dramatically. I think you’ll see a large increase in pumpers, which could cause a challenge for some clinics.” We agree with Dr. Kowalski and have been calling AID the killer app for pumps (and CGM) for some time (see ADA 2013, as one example!). It is true that some centers may not specialize in or have the capabilities for high-volume pump training, but we ultimately view increased pump adoption (particularly with automated insulin delivery) as a huge positive. Providers should be able to spend less time discussing abstract A1c numbers, guessing at patient behavior and glycemia, and manually adjusting insulin doses, and be able to spend more time fine-tuning food/exercise responses and discussing issues that really matter to patients (therapeutic, technological, psychosocial and beyond).

• Dr. Kowalski astutely noted that we can learn from CGM’s evolution – while a lot of people gave up on CGM after early issues with accuracy and on-body burden (and general clunkiness, we would add), they have advanced to the point that they speak to phones/watches, are smaller, more accurate, easier to operate and wear, and implantable versions are coming down the pike. “We can knock barriers down.” This lesson – along the lines of the famous sentiment that we overestimate change that will happen in two years and underestimate change that will happen in 10 – illustrates Dr. Kowalski’s optimism that hurdles to optimal automated insulin delivery, such as insulin kinetics, on-body burden, biologic variability, exercise, etc., will be cleared.

• Despite positive early reimbursement of the 670G in the US, Dr. Kowalski urged for additional demonstrations of efficacy (through larger RCTs) and greater appreciation of outcomes beyond A1c on the payer side. He noted that Medtronic is already conducting an n=1,500, one-year outcomes study with 670G, which we hope will be a driver of greater reimbursement for all systems. He also posited, “what is the value to the payer of sleep?” It is crucial to quantify the benefits of outcomes metrics such as time-in-range and other PROs/quality of life of metrics in order to more clearly define the value proposition of hybrid closed loop. 

Questions and Answers

Q: Any challenges that you experience, things that may be challenges for patients on DIY automated insulin delivery?

Dr. Kowalski: I think building the system is not that difficult. You need to appreciate that you’re still in control of your diabetes. My system modifies basal rates, so even if you forget your phone, the worst you’ll get is basal rate running above or below where it should be for 30 minutes. My rate of hypoglycemia and area under the curve is dramatically reduced – it takes much less treatment, this isn’t anything we haven’t shown in trials, but living it for 15 months is pretty exceptional.

Q: What is the greatest bottleneck to achieve good control?

Dr. Kowalski: I certainly appreciate that insulin action is too slow. Faster-acting insulin is a big JDRF focus and it’s hard. I’ve been experimenting with Afrezza and closed loop, and I’ve found it pretty effective. Sensors are not a problem. The other thing is carbs, if you’re eating you’ll go high with sub-cutaneous insulin. My challenges are around mealtime insulin. I like to eat carbs, what can I say?

Omnipod Horizon: 75%-85% time-in-range in 54-hour meal and exercise studies; 74% time-in-range in interim 5-day hotel results (n=11)

Between an appearance at a corporate symposium and an oral presentation, Stanford’s Dr. Bruce Buckingham shared the results of four Omnipod Horizon feasibility studies, including: (i) a 54-hour study with meal bolus challenges; (ii) a 54-hour moderate intensity exercise study with variable setpoints in adults; and (iii) a 5-day/4-night study across age groups including patients on MDI (preliminary data). As the slide shows below, mean glucose and time-in-range data has been strong in the adult cohort across the board, with mean glucose ranging from 136-155 mg/dl, percent time 70-180 mg/dl ranging from 73%-85%, time <70mg/dl ranging from 0.6%-1.8%, and time >180 mg/dl ranging from 14%-26%. The summary slide only includes data from adults, but Dr. Buckingham emphasized multiple times how much he appreciates that Insulet is investigating its system in adults, adolescents, and pediatrics from the very beginning. Indeed, Horizon has just been tested in 4-5-year-olds, and 2-4 year olds will be studied soon – whoa! At JPM 2018, Insulet guided for a “probably 2020 timeframe” for launch of Horizon, on the later side of 3Q17’s “end of 2019”/“early 2020” expectation. Given the impressive study progress to date, this timing feels doable – perhaps even conservative. All in all, well over 100 patients with type 1 diabetes have undergone >7,700 hours of hybrid closed loop therapy with Horizon running on a tablet thus far. Longer terms studies are underway, evaluating the MPC algorithm under free-living conditions with extended use in patients of all ages. We assume once the hotel study wraps up, a pre-pivotal will commence, paving the way for pivotal (perhaps in 2019?) Dr. Buckingham sang the praises of former protégé (now Insulet VP) Dr. Trang Ly and the Insulet clinical team throughout his talks, concluding that “they did really well.” Read on for details from the presented studies, plus intent to bring the Insulet-Glooko partnership to Europe.

• A five-day/four-night hotel study is underway, and topline outcomes were alluded to in a summary slide: mean glucose of 150 mg/dl, ~74% time-in-range, ~2% time <70 mg/dl, ~25% time >180 mg/dl, and ~5% time ≥ 250 mg/dl. These are consistent with prior studies in more supervised settings – great news for Insulet. We’re not sure about the demographics of this tested cohort yet, though a summary slide indicated that the study would be conducted across age groups and include MDI patients. The latter point is big, as it’s Insulet’s target market (~80% of new users) and the most important area to demonstrate benefit for market expansion. 

• The new 54-hour meal study (n=12 T1Ds) tested Omnipod Horizon over three meals (30-90 grams of carbs) with a 100% bolus compared to various real-life scenarios: missed bolus, 130% bolus, and extended bolus (50% upfront and 50% extended over four hours for a high-fat dinner). Overall, the system coped well with uncertainty: mean glucose was 153 mg/dl over the 54-hour study (134 mg/dl at night); time-in-range (70-180 mg/dl) was 76% overall and 93% at night; and time <70 mg/dl was only 0.6%. Since Omnipod Horizon does not issue automatic correction boluses, it did take some time to recover from the missed lunch bolus: 3.8 hours to get back to <180 mg/dl vs. 1.5 hours with a 100% bolus. Average glucose rose to 192 mg/dl with no bolus vs. 141 mg/dl with the 100% bolus (time >250 mg/dl: 0% vs. 10%). That said, this is to be expected of any hybrid closed loop fully reacting to an unannounced meal, and it’s notable that no hypoglycemia was experienced when the bolus was missed. This was also the first we can recall seeing an extended bolus used in a hybrid closed loop study, an important test since this strategy is often used in pediatrics – when kids’ eating habits are unpredictable, it’s safer to give an extended bolus that can be cancelled if all the food is not eaten. Horizon coped well with the extended bolus and the 130% bolus, providing a roughly similar average glucose and time-in-range as the 100% bolus. Overall, this was a solid showing for the algorithm as it moves to being stress tested in real-life meal conditions.

• The Omnipod Horizon system performed well in response to exercise, with an average time-in-range (70-180 mg/dl) of ~85%. The entire study (n=12) took place over the course of 54 hours in a supervised hotel setting and featured two 45-minute sessions of moderate-intensity exercise with setting adjustments 90 minutes pre-exercise. On day one, the adjustment consisted of a setpoint adjustment (raised from ~110 mg/dl at start to ~150 mg/dl 90 minutes pre-exercise), and on day two, the adjustment consisted of a basal rate reduction (down to 50% 90 minutes pre-exercise). For the duration of the 54-hour study, mean glucose was 136 mg/dl, with ~85% time-in-range, just 1.4% <70 mg/dl (0% overnight; impressive for an exercise study), ~14% >180 mg/dl, and ~2% ≥250 mg/dl. Temporary reduction in basal rate and raised blood glucose setpoint strategies performed well in terms of mean glucose during and after exercise, but there is a visual difference in the glycemic traces (below): With basal rate reduction, there is a slight drop followed by rebound hyperglycemia, while with setpoint adjustment, participants went a little lower initially, but then had less pronounced hyperglycemia later. Seven subjects required carbs during the setpoint adjustment, while just four did with the basal rate reduction – a reminder of how hard exercise is for AID. Of course, the exact adjustments could be further refined, personalized, and tweaked based on individual differences and type/duration of exercise, but this preliminary study shows the algorithm is safe during physical activity. Noted Dr. Buckingham, “This was actually pretty good exercise. One guy in the group, in college, he ran a four-minute mile. So he wanted to run six-to-seven miles in the 45 minutes. The device was on tablet, and I didn’t have a team that could keep up with him carrying tablet, so we put a guy on a bike that followed him around as he ran laps around a lake. There were pools of sweat around these people. We really worked these people.” We initially reported on this topline data at Keystone and ADA.

• Horizon’s 36-hour safety and feasibility study was published in DT&T (Buckingham et al.) on February 12^th. In all age groups, the system performed very admirably with respect to primary endpoints of time <70 mg/dl and time ≥250 mg/dl, ranging from 0.7%-2% and 4%-7%, respectively. Time in range also hovered in the 70%-73% range, on par with performance of the Medtronic MiniMed 670G in its pivotal trial and the real-world setting. Glycemic profiles were generally flatter throughout the day with hybrid closed loop, though high overall mean glucose and postprandial highs (see adult graph below) have presumably been areas of focus in subsequent algorithm refinement. Preliminary results from this paper were presented a year ago at ATTD 2017.

Glycemic Outcomes	Adults (n=34)	Adolescents (n=12)	Pediatrics (n=12)
Mean glucose (mg/dl)	155	~153	~157
% time <70 mg/dl	0.7%	2%	2%
% time 70-180 mg/dl	73%	~73%	~70%
% time >180 mg/dl	~26%	~25%	~28%
% time ≥250 mg/dl	~4%	~5%	~7%

• Following a presentation on real-world Omnipod use trends and data obtained through Glooko, Medical Affairs Director Dr. Jennifer Layne said, “we look forward to having more data to present to you in the near future and hopefully bringing Glooko to the EU.” As of EASD 2017, Insulet-provided Glooko was in 2,800+ US clinics, with over 50,000 users uploading. The partnership will remain an important asset over time, helping Insulet keep up with the likes of Medtronic’s CareLink. An entrance into Europe makes sense as Insulet looks to go direct beginning on July 1, and Glooko and Insulet both stand to benefit – Glooko through sheer penetration, and Insulet through data collection and evidence generation.

Dr. Boris Kovatchev on Major AID Trials and Excitement over Dexcom G6/Tandem X2/TypeZero; Dramatic New Ski Camp Results

Dr. Boris Kovatchev shared updates on a number of UVA/TypeZero studies using Dexcom’s G6 and Tandem’s t:slim X2 with the embedded Control-IQ algorithm. The clear headline was a ski camp study from January, showing a 6-hour/day improvement in time-in-range. More broadly, we were struck by (i) Dr Kovatchev’s excitement over the Dexcom G6/Tandem t:slim X2/TypeZero combination, which seems to be quite reliable on the connectivity and durability fronts; and (ii) how big of a win this is for Tandem, who is now in some very major closed loop studies outside of the iDCL pivotal. Remarkably, the UVA team has tested variants of the TypeZero algorithm over 14,500 days in over 450 clinical trial participants (30 clinical trials) at 15 research sites on four continents. Dr. Kovatchev emphasized throughout that the algorithm automates correction boluses, and tightens basal modulation as the night goes on – separating it from other systems.

• A new AID ski study wrapped up in January, testing the integrated Tandem X2/Dexcom G6/TypeZero system in 13-18 year olds (n=25) – over 48 hours of skiing, time-in-range (70-180) increased from 50% on SAP vs. a remarkable 73% on Closed Loop, translating to 6 more hours per day in range (p=0.01)! Average glucose declined 35 mg/dl (baseline: 179 mg/dl; p=0.03). Time <70 mg/dl increased from 0.8% to 3.1%, but it was not statistically significant (p=0.7). The G6 CGM was connected 97% of the time, and closed loop was active for 95% of the time (99% excluding warmup) – very strong connectivity in extreme conditions. Dr Kovatchev showed the impressive picture below of someone doing a snowboard jump while on the integrated system – nice! The next phase of the trial will test the system in skiing 6-12 year olds.

• Several long-term studies of closed loop control are going on now or starting soon, including:

  • Project Nightlight (ongoing), testing 24/7 closed loop control vs. overnight only in 110 participants over 10 months. The trial has been using Dexcom G4 and a Roche pump, but is now transitioning at the midpoint to the Tandem t:slim X2 and Dexcom G6 system with Control-IQ. Outcomes include A1c, risk for hypoglycemia, and preference for overnight vs. 24/7 closed loop control. 84 participants have been recruited out of 110. The data looked so strong from the initial tests that it helped give FDA confidence in moving to the pivotal iDCL trial.

  • The international closed loop (IDCL) pivotal trial testing the t:slim X2 with Control-IQ and Dexcom G6. 150 participants will be randomized 2:1 to closed loop vs. SAP, with main efficacy outcomes as time-in-range (70-180 mg/dl). Per January’s update, a two-week, at-home study at seven sites was expected to start enrollment this quarter (1Q18), followed by the pivotal trial this year in preparation for a 1H19 launch.

  • The FreeLife Kid AP Study in France. The trial will begin this summer in France and use the Tandem/G6/Control IQ system. It will enroll 120 children over six years old, first testing overnight only and then moving to 24/7 closed loop. “We believe this will be a landmark pediatric study of a size and duration that has not been done before.”

  • The Virginia hypoglycemia safety project, which will test closed loop in young children 5-10 years old and older adults 65+ years! The goal is to prevent extreme blood glucose events. Usual care for three weeks will be compared to three weeks of closed loop (Tandem/Dexcom/TypeZero) in a crossover design. Notably, the study will include lots of neurocognitive testing.

• Dr. Kovatchev also briefly covered CGM-based MDI decision support with the inControl Advice app paired with Dexcom CGM. The system includes six advisory modules design to work in concert: exercise advice, sleep advice, smart bolus calculation, hypoglycemia prediction, estimated A1c, in silico therapy simulation. As we heard at DTM, Novo Nordisk is supplying an NFC-enabled NovoPen Echo and a connected Tresiba pen for this ongoing study.

Bionic Pancreas with Zealand’s dasiglucagon: non-inferior to reconstituted Lilly glucagon; moving to bridging study in iLet device

Dr. Steve Russell (MGH) presented encouraging safety results (n=10) comparing Zealand’s pumpable, stable dasiglucagon vs. reconstituted Lilly glucagon in the iPhone-driven Bionic Pancreas (Tandem pumps). The random order, crossover, in-clinic, eight-hour study intentionally induced hypoglycemia via excess basal insulin and postprandial exercise, stressing the algorithm to test Zealand’s glucagon. Time <60 mg/dl was 13% with dasiglucagon vs. 18% with Lilly glucagon (not significantly different), while time in 70-180 mg/dl was 71% with dasiglucagon vs. 66% with Lilly glucagon (not significantly different). Mean glucose (110 mg/dl vs. 101 mg/dl) and total glucagon dose (0.69 mg vs. 0.86 mg) were also not significantly different. Dr. Russell noted how the glucagons were really tested here – outpatient studies typically use about 0.5 mg per day of glucagon, while this study used ~25% more than that in just eight hours. The most common adverse events were hypoglycemia and nausea, which were comparable between the study arms. Transiently elevated white blood cell count was noted at the end of both visits, but this is reportedly expected with glucagon dosing – and will be key to observe over a longer period in the bihormonal pivotal study. Zealand’s glucagon was dosed without occlusions or infusion set reactions, though obviously the bridging study will provide a better test of that over more days of wear. The team still has many steps left before commercialization – successfully testing dasiglucagon in the commercial iLet device, pivotal studies (next year – April start for insulin-only, June start for bihormonal), manufacturing, human factors, FDA submission, etc. – but this feasibility data certainly green lights dasiglucagon as a viable path forward for the bihormonal configuration of the Bionic Pancreas.

• Dr. Russell showed the bihormonal configuration of the iLet Gen 4 device (first unveiled at Friends for Life 2017), which will be the commercial device used in the pivotal studies (slated to start next year). Dr. Russell confirmed that the 1.6 ml insulin cartridge will have both manual fill and NovoRapid PumpCart (prefilled) options, while the Zealand glucagon cartridge will only come in a 1 ml prefilled format (4 mg of glucagon) – assuming 0.5 mg of glucagon are used per day, this means it would last 5-6 days or possibly more. The infusion set tubing and site will be packaged separately, enabling patients to keep the same cartridge/tubing, but change the site out every 2-3 days.

• The study design to induce hypoglycemia was clever: patients wore the bionic pancreas, in addition to remaining on their own pump. To induce hypoglycemia, the basal rate was doubled on a patient’s own pump, unknown to the bionic pancreas. Participants then ate lunch and received a full bolus through their own pump (also unknown to the bionic pancreas). When glucose started to rise, the Bionic Pancreas would dose additional insulin on top of the hidden bolus. Participants then cycled after lunch, causing hypoglycemia.

NIH-Funded AID Study Updates: FLAIR Medtronic Advanced HCL Simulation (TIR 83%), iDCL Protocols, Beta Bionics Study Timing, Dan05 (Hovorka) Recruitment on Hold

NIDDK’s Drs. Guillermo Arreaza-Rubin and Andrew Bremer chaired a crowded session during which PIs of the four major NIH-funded closed loop trials provided status updates. While the FLAIR study (Medtronic Advanced Hybrid Closed Loop vs. 670G) will not commence until later this year, Dr. Rich Bergenstal showed a trace depicting the potential of automatic correction boluses to blunt postprandial hyperglycemia (no surprise there). He also showed data from 40 simulated patients on advanced hybrid closed loop, where time-in-range was a strong 83%. This trial is running well behind the original plan to start in late 2017, perhaps as Medtronic gets the device ready. Dr. Boris Kovatchev gave timing and study design updates on all four iDCL study protocols (including protocol 4, which will investigate Harvard’s enhanced MPC algorithm on a mobile system with Dexcom CGM and either a t:slim or Omnipod pump). Dr. Steve Russell provided a very granular timing update for Beta Bionics’ insulin-only (bridging study beginning in May, pivotal beginning in April 2019) and bihormonal (phase 2b study with dasiglucagon beginning in July, pivotal to begin June 2019) systems – these are also a bit back of the previous plan to start the trials at the “beginning of 2019.” Finally, Dr. Hovorka shared that his Dan05 pediatric closed loop study has enrolled two subjects, but recruitment is currently on hold. It is great to see all of these progressing following their announcement just over a year ago. Dr. Bremer also announced a slew of type 1 diabetes funding opportunities – just released February 15 and enabled by the hard-won Special Diabetes Program – that may be of interest to the ATTD community, including “clinical, behavioral, and psychological research testing current and novel closed loop systems,” “treating diabetes distress to improve glycemic outcomes in type 1 diabetes,” and more. Read details below on each study:

• The Prof. Moshe Phillip-Dr. Rich Bergenstal co-PI’d FLAIR study comparing the 670G to “advanced hybrid closed loop” (670G + Fuzzy Logic including automatic correction boluses) will begin “later this year when all of the systems are built and ready to go” – back from the original plan to start in late 2017. In preliminary simulations of 40 patients, advanced hybrid closed loop has reduced mean glucose by ~10 mg/dl (152 to 142 mg/dl), lifted time between 70-180 mg/dl to ~83% (up from 76%) largely by shaving off the highs (time >180 mg/dl decreased from~24% to ~16%) and with little impact to lows (a similar ~0.6% with 670G vs. ~0.7% with advanced hybrid closed loop). These improvements were conferred by an average of 10+ auto correction boluses per day. Not only does the advanced hybrid closed loop provide earlier and automatic correction boluses, but a slide also laid out that it “liberalizes constraints on algorithm parameters,” and uses sensor glucose values non-adjunctively – we’d assume Medtronic will need to use a next-gen sensor for this system, as Guardian Sensor 3 is only approved adjunctively. And while it is ambitious to take on the 670G as a comparator (unlike the other NIH-funded studies, which don’t compare their systems to existing automated insulin delivery options), there is a fair amount of space for improvement, particularly in curbing postprandial highs. Dr. Bergenstal showed an “n of 1” trace (provided by Dr. Thomas Danne) in which advanced hybrid closed loop cut the duration of a postprandial high after an unannounced meal in half, from six hours to three hours, while also diminishing its amplitude. We’d guess this product is still more than a year from market, and it could be on roughly similar timing to Tandem’s Control-IQ system with TypeZero’s automatic correction bolus feature (launch in 1H19).

• Dr. Boris Kovatchev broke the International Diabetes Closed Loop (iDCL) trial down into its component parts, with the most details we’ve ever heard on the setup for protocol 4 (Harvard’s mobile closed loop system), data from the training protocol, and a slew of timing updates. See this table for a detailed reminder of all of the protocols – it is difficult to keep track of all of the moving pieces.

  • Protocol 4 with Harvard’s “Enhanced Control-to-Range (eMPC)” will be PI’d by Sansum’s Dr. Jordan Pinsker and commence at the “end of this year.” The algorithm will be on a mobile device, controlling either Tandem’s t:slim X2 or Insulet’s Omnipod (TBD), with input from Dexcom CGM. The three-month study will enroll 126 subjects, randomized 1:1 to closed loop and SAP, at seven US sites: UVA, Harvard/Joslin, Mount Sinai, Mayo Clinic, Barbara Davis Center, Stanford, and Sansum. Like all of the NIH-funded AID trials, protocol 4 will be coordinated by the Jaeb Center. Primary outcomes are superiority in time <70 mg/dl and non-inferiority in time >180 mg/dl.

  • The results from the n=40 iDCL training protocol were presented in poster form at ATTD, and Dr. Kovatchev highlighted the 73% time-in-range, 76% time-in-range overnight, and 0% median time <50 mg/dl. While there were no differences in system performance with the Roche Spirit Combo or Tandem pumps, there was a notable difference in pump connectivity with peripheral devices, so the iDCL team opted to proceed with the Roche pump in protocol 1 (Roche Spirit Combo pump, Dexcom G5 CGM, TypeZero algorithm), for which the last completer (of n=106) is expected on July 1^st.

  • Dr. Kovatchev shared that protocol 2, the EU pivotal trial of the Roche-Senseonics-TypeZero 180-day closed loop system is expected to begin soon. It was previously slated to begin in 1Q18, wrap up later this year, and support a CE mark. This study’s design was also featured in an ATTD poster.

  • Dr. Kovatchev said the iDCL study group hopes to begin the pivotal study of the Tandem t:slim X2/Dexcom G6/TypeZero Control IQ embedded system (protocol 3) this May, conclude at the end of this year, and continue on with the extension phase. We were not previously aware of an extension phase, but Tandem has most recently projected for a 1H19 launch, suggesting that FDA approval will hinge on the phase that occurs this year. In the protocol 3 pilot (pre-pivotal study of the Tandem/Dexcom embedded system), n=5 participants spent a “very good” ~87% time in 70-180 mg/dl overall, with 94% time-in-range overnight. Time in hypoglycemia was “minimal,” with ~3% overall and just 1% overnight. Notably, there was no time spent >250 mg/dl, and time >180 mg/dl was limited to 5% overall. Wow! Dr. Kovatchev was extremely excited about this system in Dexcom’s symposium on Day #2, a major win for the companies – we have high hopes for this product and pivotal trial.

• MGH’s Dr. Steve Russell gave very specific timing updates for Beta Bionics studies moving forward, headlined by an insulin-only pivotal trial beginning in April 2019 and a bihormonal pivotal study to begin in June 2019 – both are back from the previous plan to start at the “beginning of 2019.” The insulin-only pivotal will be followed by an expected 4Q19 PMA submission, which should allow for what has previously been set at a 1H20 launch. Launch timing for the bihormonal system is more up in the air, as timing of the PMA submission depends on the length of the dasiglucagon exposure study required by FDA. While the effects of chronic exposure are still a question mark, Dr. Russell is excited by the drug’s acute performance and safety: “One of the problems with dual hormone is we don’t have a stable pumpable glucagon, or I should say, we didn’t have a stable pumpable glucagon. Dasiglucagon is stable for more than a month at 40 degrees in a pump. It behaves comparably to reconstituted Lilly glucagon. Now we have a stable pumpable glucagon we can take forward into pivotal trials.” (See the early data above testing dasiglucagon in the iPhone drive system.) Prior to the start of the pivotal studies, an insulin-only bridging study is expected to commence in May (using the iLet integrated device, and the group’s first type 1 diabetes study closed loop study enrolling MDIs as well as pumpers), and the Zealand bihormonal phase 2b study will begin in July (first use of the iLet integrated device in bihormonal mode). The team has pushed back trial and submission timelines several times, so we are surprised to see them providing such granular projections; on the other hand, that could mean the path ahead is more lined up, especially on the hardware development side. We are excited that dasiglucagon is a viable candidate and could make the bihormonal vision a reality. Plus, it will be terrific to see how the single and dual hormone systems compare in the pivotals.

• Dr. Roman Hovorka’s six-month, n=130 Dan05 study of closed loop (modified Medtronic 640G, Enlite 3 CGM, and Cambridge control algorithm on Android phone) in children and adolescents with type 1 diabetes has recruited two subjects, but recruitment is now on hold as investigators await manufacturing of the study device. Dr. Hovorka’s fingers are crossed that the study can start this coming May and wrap up August 2019, but he specified that this is “contingent on a few things coming together.” The comparator arm is pump therapy with or without CGM, though FreeStyle Libre Pro will be used to capture glucose data in the control groups when necessary. Notably, secondary outcomes of psychosocial impact and health economics will be performed at Stanford and UCLA, respectively, with the latter aimed at supporting reimbursement. 

Questions and Answers

Dr. Guillermo Arreaza-Rubin: What are the advantages and disadvantages of embedded (i.e., in the pump) vs mobile (i.e., on a phone) systems?

Dr. Kovatchev: Embedded are simpler, more compact, and faster to commercialization. Mobile provides the option of component interoperability if you run from a phone, devices can be interchangeable…that’s more in the future, but we’re working towards it as well.

Dr. Russell: Of course connectivity can be a problem. You’re always going to have connectivity to the CGM to worry about. One of nice things with fully-integrated systems is you lose the issue of connectivity with a pump. But the disadvantage is you need a fully-integrated system, and in our case, building that has taken time.

Dr. Hovorka: In principle, a mobile system can be more flexible to update if the app is on the App Store. Some of these aspects are possible advantages, but I agree that, especially for children, integrated is beneficial.

Dr. Bergenstal: Not much to add, but I will just say that the phone is not always with you, and if you use pumps to deliver your insulin, your pump is always with you.

Q: In your experience, why do you think people prefer bihormonal to insulin-only?

Dr. Russell: They like that they have even less hypoglycemia than with insulin-only. They also take less carbs; with insulin-only, they occasionally take carbs, and they have to take very few that are medicinal (low correction) with bihormonal. And they just feel a greater sense of confidence that they are not going low, for things like exercise, particularly.

Q: Is there a plan to use new insulins in these systems?

Roman: It’s an interesting question whether these systems will need a new regulatory pathway or new trials if they include new insulins. I think the algorithms are flexible enough to deal with faster insulins and there would be no need to change them – there is so much more variability between people than there is due to a ten-minute shift in insulin speed.

Dr. Russell: Our system has a built in PK parameter, so it makes assumptions about insulin absorbance and clearance. Because of between-people variability, we need to make a conservative estimate. It would be advantageous if didn’t have to adjust it for people – if it did, and the patient switches to slower-acting insulin, then you have a problem. But if you do have to adjust it, then you have to think about an auto-detection method, and that adds complexity.

Dr. Hovorka: In our system, we also have a system that adapts and learns the PK. For those with long PK, the system knows it and can be more conservative and vice versa.  

Harvard’s Dr. Frank Doyle III on the Next Frontier in AID Algorithms: Adaptation Based on Multiple Zones and “Trust Indices”

Harvard’s Dr. Frank Doyle III tested the audience’s technical knowledge in his review of what’s to come in automated insulin delivery algorithms: (i) novel adaptation algorithms using multiple zones and (ii) different modeling strategies depending on degree of confidence in the current state (“trust index”). Taking multiple zones allows the system to go beyond a one-size-fits-all algorithm with a gain multiplier depending on distance from the target value, employing a different glucose-normalizing strategy if a patient is euglycemic, slightly elevated, very high, etc. His group has already begun testing multi-zone adaptations based on glucose and rate of change in the UVA/Padova simulator, and shown improvements in time in range, mean glucose, hyperglycemia, and hypoglycemia vs. SAP This data, which “further raises the bar of what has already been a very robust system,” will be presented at the American Control Conference this Spring. To explain the philosophy behind the “trust index,” an estimate of the quality of the system’s predictions based on changes in physiology, external challenges, sensor accuracy, etc., Dr. Doyle drew an analogy to the stock market: At the end of December, when the market’s volatility index was low, an analyst made a bold 15-year prediction for the S&P. Now that the volatility index is astronomical, the same analyst probably wouldn’t be as comfortable making such a projection, or at least the error bars would be significantly greater. When the model seems to be accurate, it can be more aggressive; when lower confidence, aggressiveness should be dialed back. Running an algorithm adjusted to modulate aggressiveness and strategy based on trust in legacy data pushed time in range all the way up to 91% in one analysis! The trust index work has even made it into the clinic (with a Dexcom G4 and Omnipod at Sansum in a 48-hour study), and a manuscript is currently under review. In the study, time in range (70-180 mg/dl) reached 88%, and time <70 mg/dl was just 1.5%. These data are early and in the clinic, but Dr. Doyle claimed that this level of time in range may set a “new high water mark” for his own work. He wrapped up his talk with the simple conclusion: “Adaptation and our ability to not just stick with a fixed algorithm has to happen. We have to be responsive to changes in patient, sensor, and perhaps the demands that patient and doctor will put on themselves.” The potential for even smarter AID algorithms has not been discussed in the past few years as much as faster insulins and additional sensor inputs, but we’re very optimistic about the potential here – given 42 factors that affect blood sugar, there is a lot of variability that algorithms might be able to model!

AID Poster Highlights

Title	Importance
Exploratory Analysis for Selected Patients with Dawn Phenomenon During the MiniMed™ 670g Hybrid Closed-Loop Pivotal Trial	In the three-month 670G pivotal, 82 of 124 patients were identified as having had dawn phenomenon (defined as elevated average sensor glucose or elevated basal rate from 3-6 am). Those with dawn phenomenon had improved time-in-range (70-180 mg/dl) during the hybrid closed loop phase compared to the run-in phase from 12-6 am (77% vs. 68% in-range) 12-3 am (73% vs. 67% in-range), and 3-6 am (82% vs. 69% in-range). From 12-6 am, that’s an ~30-minute improvement. Hybrid closed loop is an obvious win overnight for all type 1s, though this study could suggest those with dawn phenomenon may benefit even more. Of course, given the unpredictability of overnight basal needs in type 1 diabetes, we’d expect most type 1s would benefit from automation.
Does a Hybrid-Closed Loop System Reduce Overnight Alarms in Patients with Type 1 Diabetes?	In n=27 5-20-year-old type 1s enrolled in a study at Stanford, 670G reduced overall number of alarms by 27% (2.3/night vs. 1.7/night) vs. open loop. The number of alarms requiring an intervention was reduced by 45% (0.98/night vs. 0.54/night), largely driven by 73% reduction in hypoglycemia alarms. Study participants did see an 85% increase in pump alarms (from 0.05/night to 0.34/night) mainly indicating auto mode exit and minimal insulin delivery. Though the MiniMed 670G does tend to be an alarm-heavy device, this shows that it still reduces overall alarm fatigue relative to a CGM worn in open loop. We hope to see Medtronic improve on alarms, Auto Mode exits, and pump alarms in the next-gen 670G.
Performance of Omnipod Personalized Model Predictive Control Algorithm with Moderate Intensity Exercise and Variable Setpoints in Adults with Type 1 Diabetes	54-hour hotel study of Insulet’s Omnipod Horizon. Data was presented by Dr. Bruce Buckingham in a symposium, covered in our days #3-4 report: Overall mean glucose: ~136 mg/dl; with ~85% time 70-180 mg/dl Temporary reduction in basal rate and raised blood glucose setpoint strategies both performed well in terms of mean glucose during and after exercise. With basal rate reduction, there was a slight drop followed by rebound hyperglycemia, while with setpoint adjustment, participants went a little lower initially, but then had less pronounced hyperglycemia later.
Withdrawal of Remote Real-Time Telemetric Monitoring Increases Hypoglycemia During Usual Care but Not During Automated Glucose Management with an Insulin-Only or Bihormonal Bionic Pancreas	Helmsley-funded Beta Bionics study showing that remote monitoring has no effect on hypoglycemia with the bionic pancreas; the poster concludes that remote monitoring can be “safely omitted” from future studies. As expected, remote monitoring slightly improved hypoglycemia in the usual care (no automation) arm – 1.32% <60 mg/dl with remote monitoring vs 1.95% without remote monitoring. These data also imply that remote monitoring in control groups improves outcomes. In other words, studies using remote monitoring in the control group may be underestimating the benefits of automation.
The International Diabetes Closed Loop (IDCL) Trial: Planned Pivotal Trials of Closed Loop Control on an Embedded System and a Mobile System	Details on the pivotal trials of the Roche-Senseonics-TypeZero (EU) and Tandem-Dexcom G6-TypeZero (US) closed loop systems. The TypeZero algorithm is embedded in Tandem’s pump, and will run on a mobile phone in the Roche/Senseonics trial. Both pivotal trials are expected to begin enrollment in early 2018. These are multi-center investigations randomizing 2:1 to AID vs sensor-augmented pump for three months. Participants will be age 14-75 years currently treated with an insulin pump. Co-primary outcomes include: (i) superiority in CGM-measured time below 70 mg/dl; and (ii) non-inferiority in CGM-measured time above 180 mg/dl.
Real-World Assessment of Former MDI Patients’ Experience on the Medtronic MiniMed™ 670g Hybrid Closed-Loop System	47 former MDI patients responded to a Medtronic survey reporting high satisfaction with the MiniMed 670G during the Customer Training Phase. Participants had used the system for eight weeks. Most reported that the system met/exceeded expectations with respect to overall health (98%), perceived better A1c (98%), improved blood glucose control (96%), more time in range (96%), overall system expectations (91%), and fewer lows (91%). It is important to note that this analysis could be highly subject to selection bias. Still, the results suggest 670G will be valuable for some MDI users, a definite market-expansion opportunity for Medtronic.
Can an Automated Closed Loop System Improve Outcome in Adolescents with Poorly Controlled Type 1 Diabetes? The Spidiman 02 Study	Randomized, crossover study details: EU Framework 7 Programme-funded trial conducted by Luxembourg and Cambridge groups. Participants with type 1 diabetes (12-18 years, A1c ≥ 8.0%) will wear closed loop for 4 weeks vs. sensor-augmented pump for 4 weeks. Randomization started in July 2017, and 12 patients are expected to complete in March 2018. Outcomes: Time-in-range (primary); quantity and quality of sleep (measured via Actigraph sleep monitor); acceptance of parents to allow adolescents (12-18 years old) to take responsibility in diabetes management.
The Impact of Short-Term Artificial Pancreas Use on Daily Physical Activity Levels in Individuals with Type 1 Diabetes: Pilot Study Results	No impact of single or dual hormone on energy expenditure in 23 type 1s (mean age: 38 years old). Bionic Pancreas collaboration with Elizabeth Mayer-Davis (UNC), David Maahs (Stanford), and Michael Riddell (York). Study also found that wrist-worn accelerometers have a tendency to overreport step count; therefore, the location of wear may need to be modified in future studies (i.e., worn at the hip).

2. CGM

Dexcom G6 Update: No calibration, 2-hr warmup expected, but will accept a cal if a user chooses; Updated app: urgent low “soon” alert, alarm profiles; Direct-to-Apple Watch is NOT under FDA review

In one of Dexcom’s strongest symposiums ever, SVP Jake Leach shared the most comprehensive G6 feature update we’ve seen – including the no-calibration plans, accuracy data from recent clinical studies, sensor and app updates, and new branding. The product continues to look outstanding and will update every aspect of Dexcom CGM – some very meaningfully, like the new sensor and inserter. We detail all the new learning below, especially news that G6 will indeed be no-cal, but will have the ability to accept calibrations if a user chooses. Mr. Leach mentioned that a two-hour warmup is expected for the no-cal version – if approved, that would be a huge improvement over Abbott’s 12-hour no-cal warmup in the US. The G6 accuracy data shown today was from “a combination of recent clinical studies” (not clear if this included the never-before-seen pivotal data), and it continues to be on par/improved vs. G5 in terms of all accuracy metrics – overall MARD 9.0%, 94% of points within 20/20, a Day 1 MARD of 11.2%, and 94% within 20 mg/dl in hypoglycemia. Mr. Leach also confirmed in Q&A that direct-to-Apple-Watch connectivity is not under FDA review, contrary to what the New York Times reported in December – this is not too surprising to us, as Dexcom has been vague in recent months about the timing here. Moving to the Watch as a standalone primary display device is a big deal and will presumably require a lot of development effort. Combined with Dr. Boris Kovatchev’s compelling talk on AID (see above), along with Dr. Nick Oliver on the iHART CGM study (Libre vs. G5; see our coverage), we thought this was one of Dexcom’s most exciting conference symposia in some time. Editor’s Note: Following ATTD, Dexcom’s G6 was cleared by FDA with no calibrations, a two-hour-warmup, 10-day wear with mandatory shutoff, and under a new integrated CGM (iCGM) pathway– see our complete coverage of the clearance here and analysis of the new iCGM pathway with Special Controls here.

• Like JPM, today’s talk made it clear that G6 will be a no-calibration-required system. But in new news, Mr. Leach mentioned G6 will accept calibrations if a user would like to enter one. A two-hour warmup was also mentioned, which had not previously been confirmed for the no-cal version. Mr. Leach made it clear that G6 is “truly designed to be a no-cal system,” and Dexcom will recommend patients do not calibrate it with fingersticks – each sensor will be calibrated in the factory. However, optional calibration will be advantageous in the “very rare” case where a sensor is off – quite smart to add, as some key opinion leaders have criticized FreeStyle Libre on this front (i.e., when Libre is reading inaccurately, there is no way to correct it). The two-hour G6 warmup will be a huge advantage over FreeStyle Libre’s current 12-hour warm-up in the US.

• Mr. Leach showed new G6 accuracy data today combining data from recent clinical studies – Dexcom has maintained/improved on G5’s accuracy, even with the move away from calibrations. It was not clear how many patients/paired points were included in the slide below, and if this dataset included the main G6 pivotal (on which we’ve never seen data). Regardless, the accuracy looks very much on par with G5, but eliminating calibrations. Mr. Leach later said that G6 features a 40% improvement in sensor variability (less manufacturing variability) and a 10x improvement in signal:noise ratio (more glucose signal, less background signal) –which “significantly drives performance,” especially in the low glucose range.

• G6 will have a slightly updated app, maintaining the same general look as the G5 app, but moving the menus around and using up more of the screen. The events and settings now appear below the trend graph, possibly to make entering “food” or “exercise” events and accessing alarms more top of mind. The ability to calibrate from the app’s home screen has now been removed, in line with the move for factory calibration; instead, a user will have to go into settings to calibrate, a smart design change to discourage fingerstick calibration except when it’s really warranted. As a reminder, the current user experience puts Events, Share, and Meter Calibration as icons across the top, with settings accessed in a side menu.

• We finally got to see the finalized G6 predictive “urgent low soon” alerts, a feature Dexcom has long talked about adding. This more intelligent low alert notices when glucose is dropping rapidly and is expected to cross the low threshold – e.g., “55 mg/dl within 20 minutes.” Mr. Leach emphasized it does not issue increase the nuisance factor, given the 93% detection rate. We’d guess it can be toggled on/off, similar to the rise/fall rate alarms.

• In a long-needed update, G6 will also add alert schedules within the app, allowing patients to set glucose alarm settings for different times of day. Like basal profiles, this will allow different glucose thresholds to be set at night vs. during the day, for instance. The G6 app will also add more alarm/sound customization options.

• The new G6 applicator continues to get rave reviews in Dexcom’s tests: 98% of pediatric subjects rated the new applicator as “very easy” or “somewhat easy” vs. 59% for G5; 76% rated the new applicator as “didn’t feel anything” vs. 30% for G5. This is going to be a major upgrade to the current syringe-like inserter.

• Other notable features that were new and/or confirmed:

  • Indicated for 2+ years old, well ahead of Abbott (18+ years) and Medtronic’s Guardian Sensor 3 (14+ years) in the US.

  • Wear time of 10 days, with 14 days potentially coming with the first-gen Verily disposable.

  • A 20-feet Bluetooth transmission range, plus a 50% improvement in the stability of the sensor signal. Dr Kovatchev later raved about the consistent G6 connectivity with the Tandem t:slim X2 pump. We’ll be interested to see if this has improved over G5 in real-world use, since Bluetooth dropout is still an issue with G5 even at very short distances.

  • The new ~30% smaller G6 transmitter will maintain the three-month life. The key change here will come with the disposable Verily gen one sensor. (It will complete development this year, but the 4Q17 call did not share a specific launch timing update.) Reordering transmitters remains a weak point of the current G5 system, so the move to disposable will be a welcome upgrade.

  • The sensor geometry minimizes the wound healing response. The insertion needle is the same size as G5 at 26 gauge. Combined with the new applicator data, however, the pain seems to be smaller.

  • Acetaminophen blocking, which we’ve long known about. We’ll be interested to see if this allows G6 to enter the hospital.

• Dexcom’s partners slide now lists just two pump companies (Insulet, Tandem), one smart pen player (Lilly), and six AID partners (including University of Cambridge and Imperial College London) – we cannot recall seeing the latter two before, though perhaps they were shown because of the EU location of ATTD.

• Direct to watch connection remains “under development,” but Dexcom did not provide specific timing. Both Apple Watch and Fitbit Ionic were shown on this front, confirming the Fitbit partnership is also striving to do go direct-to-watch. We continue to hear from parents that moving the watch to a primary display will be very welcome, as use with the Series 3 Apple Watch (with cellular) would allow kids to be remotely monitored without having to carry a smartphone.  

• Dexcom aims to bring the public API and Clarity mobile app outside the US soon, but no specific timing was shared. These have been warmly received in the US, especially the notifications in the Clarity mobile app.

HypoDE Study: CGM Reduces Hypoglycemia in MDI-treated Type 1s with Impaired Hypoglycemia Awareness by 72%; Another Win for CGM in MDI!

In the very first randomized controlled trial to examine the efficacy of real-time CGM in MDIs with type 1 diabetes and impaired hypoglycemia awareness, CGM significantly reduced hypoglycemia incidence (≤54 mg/dl for at least 20 minutes) by 72% (p<0.0001). Severe hypoglycemia was nearly halved with CGM (p=0.02), a major win for cost-effectiveness. The Dexcom-funded HypoDE study (n=141 completers), conducted by Dr. Lutz Heinemann et al. and published in The Lancet during ATTD, was a six-month, 12-center trial in which participants were randomized to receive either 22 weeks of real-time CGM (Dexcom G5; n=75) or continue with SMBG (n=66). CGM results were collected over an additional four-week follow-up phase, during which the control participants wore the masked Dexcom G4 system. (All participants wore masked Dexcom G4 over a four-week baseline phase.) Study participants were eligible if they (i) had type 1 diabetes for at least one year and (ii) had experienced at least one severe hypoglycemia event requiring third-party assistance in the previous year or reported a score ≥4 on the Clarke assessment. The graphs below depict the primary outcome, with controls in panel A and the RT-CGM group in panel B: Mean number of hypoglycemia episodes per 28 days fell from ~11 to <4 in the CGM group, while staying largely flat at 14 in the control group. Mean nocturnal hypoglycemic events per 28 days also fell from 2.3 to 1.0 in the CGM group, while climbing from 2.4 to 2.7 in the controls. Regarding overall glycemia, time ≤54 mg/dl significantly decreased in the CGM group, falling from 1.7% to just 0.3% (-20 minutes per day) as compared to the control group, which saw a non-significant decrease from 2.5% to 2.3% (-3 minutes per day). Time spent ≤70 mg/dl in the CGM group also dropped significantly from 4.9% to 1.6% (-47 minutes per day), while the control group saw a non-significant decrease from 6.9% to 6.4% (-7 minutes per day). The incidence of severe hypoglycemia events requiring third-party assistance in the control group (1.18) was roughly twice that seen in the CGM group (0.64; IRR 0.36), with 39 events recorded in the control group and 24 in the CGM group – this reached statistical significance (p=0.02), is a major win for cost effectiveness, and confirms the severe hypoglycemia findings from IN CONTROL (EASD 2016). Importantly, the hypoglycemia improvements were not achieved at the price of hyperglycemia, as no significant changes were observed in A1c for CGM (-0.2%; baseline: 7.6%) or the control group (-0.1%; baseline: 7.4%). Glycemic variability measured by coefficient of variation (CV) improved quite significantly from 39% to 34% in the CGM group, while the control group remained flat at 41%. (Dr. Rich Bergenstal frequently cites CV ≥36% as an unstable CGM profile, consistent with Dr. Louis Monnier’s 2017 publication in Diabetes Care.) Despite this improvement, the CGM group did not see a meaningful increase in time between 71-180 mg/dl (58% to 59%) as time >180 mg/dl increased ~3% (absolute increase) in both groups. Aligning with previous work, there were no significant differences in the self-reported hypoglycemia unawareness score between study groups – oddly, both groups improved by ~40%.

• Dr. Rich Bergenstal wrote a stirring article accompanying the study’s publication in The Lancet, noting that “this is the type of study needed to expand the indications for use of CGM in populations with a strong need to improve HbA1c and reduce glucose variability and hypoglycemia.” In the 2018 ADA Standards of Care, CGM indication for those with hypoglycemia unawareness was graded with C-level evidence – we’re hopeful that the HypoDE results will serve to increase the strength of this important recommendation. In the comment, Dr. Bergenstal also pointed to CGM indications as an adjunct to pump therapy/in closed loop, in type 1 patients on MDI, in pregnancy (CONCEPTT), and more and more in type 2 diabetes (see Onduo and Unitedhealthcare/Dexcom’s n=10,000 type 2 CGM pilot), pointed to CGM as a useful instrument in cost-effective telehealth, and said it “might be the best example of diabetes precision medicine widely available today.” Wow! We have certainly seen evidence for CGM's efficacy in a number of populations come a long way, and hope to see the user base follow.

 

**Panel A depicts the control group without RT-CGM, while Panel B depicts the experimental group with RT-CGM

• Patient-reported outcomes indicated a positive effect of CGM on hypoglycemia-related distress and satisfaction with CGM in this population. Fear of hypoglycemia dropped from a mean score of 55 to 42.2 on the HFS for patients in the control arm (~23% change) vs. 53 to 37 for patients in the CGM arm (~30% change). Although this just missed the threshold for statistical significance with p=0.07, Dr. Norbert Hermanns noted that CGM showed an “impressive reduction in the burden caused by hypoglycemia fears.” (And minimizing these fears is not at all trivial, given that 79% of type 1 patients lower their insulin dose after a severe hypo, pushing further away from optimal diabetes management.) Overall diabetes distress dropped from a score of 2.5 to 2.1 among control participants (16% improvement) and from a score of 2.6 to 2.0 among CGM participants (23% improvement) on the DDS scale (non-significant p=0.203). Dr. Hermanns also presented findings on the various DDS sub-scales, however, highlighting a meaningful difference between CGM and SMBG when it came to hypoglycemia-related distress, specifically (score of 3.0 at follow-up with SMBG vs. 2.7 with CGM, p<0.05). The Glucose Monitoring Satisfaction Survey was administered for all HypoDE participants. Mean score improved from 3.7 to 4 among SMBG patients (~5% change) and from 3.7 to 4.3 among CGM patients (~16% change), revealing a statistically significant benefit to CGM (p<0.01).

  • The fact that there were eight dropouts in the control arm and none in the experimental arm also suggests strong satisfaction and quality of life with CGM. This seems beyond a statistical anomaly, and one of the strongest indicators that type 1 MDIs with impaired awareness of hypoglycemia enrolled in this study liked wearing CGM. A crossover design would’ve been icing on the cake in answering this question, but the study is quite convincing as is.

• The positive results of the HypoDE trial add to the mounting evidence demonstrating CGM’s benefits in MDI. Dr. Hans DeVries, who provided independent commentary on the study, noted that HypoDE’s “important results” might influence reimbursement – we certainly hope so. Although the GOLD and DIaMonD studies of CGM in MDI likely excluded patients with hypoglycemia unawareness, use of CGM was linked with significant decreases in hypoglycemia in those treated with MDI. The IN CONTROL study presented at EASD 2016, which specifically investigated CGM in those with problematic hypoglycemia (but did so in a mixed population of MDI and pump users) found CGM significantly reduced severe hypoglycemia (14 events vs. 34 events; p=0.03). As the HypoDE publication mentions, since the majority of those with type 1 diabetes are treated with MDI, the HypoDE findings combined with these prior results have both clinical and health-economic implications. The now-repeated finding that MDI plus CGM yields very strong clinical benefits is exciting, especially given the cost-effectiveness of this approach relative to a pump without CGM. We’d love to see a head-to-head study comparing CGM plus MDI with decision support vs. automated insulin delivery with a pump/CGM – would there be a major difference in outcomes? How would payers assess the cost-benefit? It would also be interesting to investigate the role alarms and smarter retrospective analytics play in the reduction of hypoglycemia – e.g., will insights like “You are likely to be low today” have additional benefit over current threshold alarms?

• Despite the significant difference in severe hypoglycemia “requiring third-party assistance,” a sub-category showed no difference: the incidence of severe hypoglycemia requiring “medical intervention” (3 in control group vs. 5 in CGM group; p=0.59). However, given that these events are quite rare (e.g., paramedics coming), it’s likely the study was not powered to detect such differences. King’s College London’s Dr. Pratik Choudhary raised this question during Q&A: Sensor-detected hypoglycemia that the patient experiences (and overcomes) at home doesn’t overtly cost the payer anything, so did HypoDE “just miss the mark” on relevance to payers by not accumulating enough data on hospitalizations? Dr. DeVries responded with notable optimism, explaining that reimbursement is driven by a whole host of data and other factors (not one study alone), and arguing that “some form of CGM” is eventually going to become standard of care for all patients with type 1 diabetes. “Even if there are people who will go to great lengths to dismiss all available data, at some point, someone is going to make the right decision and say now we have enough evidence.” Indeed, an EASD poster from Belgium estimated a cost reduction of €345,509 (€911 saved per person) with reimbursement for 515 CGM users (type 1 pumpers) – the body of evidence supporting CGM, for patients, providers, and payers, is growing. 

Dexcom Clarity: data from 50,000 users; EHR integration live at CHLA; mobile app launching OUS in 2018; insulin, meal, exercise data coming

We got a slew of updates on Dexcom Clarity in its first major oral presentation and dedicated corporate symposium: real-world usage/outcomes from 50,000 users (more monthly logins is associated with more time-in-range, less hyperglycemia, and a lower average glucose); EHR integration screenshots (piloting now at Children’s Hospital LA); early Clarity screenshot concepts that add insulin, meal and exercise data; adoption of the mobile app; and clinic uptake. The data management platform is now available in 13 languages and 25 countries, with the greatest usage in the US. Notably, the new Clarity mobile app has made a big difference for usage: 30% of registered Clarity users logged in to the website quarterly vs 50%+ of registered users who have engaged with the mobile app in the past 30 days. The Clarity mobile app is expected to launch outside the US in 2018. Impressively, almost 19,000 people have signed up for the new Dexcom Clarity mobile app/email notifications (see our coverage) – no surprise there since it really reduces hassle and changes the paradigm of diabetes data (passively collecting and sending trends automatically every week). Dexcom is also building out the app to add all the capabilities available on the website. It was a bit unclear how large the Clarity user base, though it’s certainly over 83,800 accounts in the US, 48% of whom are sharing data with their clinic.

• Dexcom’s Dr. John Welsh presented the first Big Data analysis from Dexcom Clarity – web login trends vs. glycemic data from 50,000 US G5 iPhone users in August 2017. As we’ve come to expect with diabetes data, 59% of these users did NOT log in to Clarity last August, 16% logged in once, 13% logged in 2-3 times, and 13% logged in 4+ times. The most impressive trend was for time-in-range (70-180 mg/dl), which ranged from 55% in those who did not log in to Clarity to 64% in those who logged in 4+ times last August (p<0.0001). (The average time-in-range in this 50,000-patient cohort was 57%.) The linear trend was also true of mean glucose (176 mg/dl with 0 logins vs. 161 mg/dl with 4+ logins; p<0.0001) and time in hyperglycemia (41% with 0 logins vs. 32% with 4+ logins; p<0.0001). Notably, there was not much of a signal between Clarity logins and time <70 mg/dl, which makes sense to us – most of the ability to avoid time-in-hypoglycemia comes from the real-time alerts. Dr. Welsh emphasized that these are associations and not an assertion of causality, a point we’d strongly echo – it’s likely Clarity logins are a good marker of diabetes motivation, engagement, familiarity with technology, comfort with data, etc. Still, the results parallel Dexcom’s separate ATTD poster on screen views and glucose outcomes, a positive. While Abbott and Medtronic have been faster to share real-world data (on FreeStyle Libre and 670G, respectively), we’re elated to see Dexcom adding to the discussion. This data will be very important for getting a pulse on how patients are doing in the real world.

• Dexcom’s Dr. Nate Heintzman show a screenshot of the EHR-integrated Clarity experience, now live at Children’s Hospital LA – “clinicians there love it.” A clinician “orders” Dexcom data within the EHR, just like ordering a lab test. Cool! There is no extra log in on the Clarity website, a huge win for time-stressed clinicians. The data appears directly within a patient’s EHR profile. Dr. Heintzman said he is very focused on this project this year, with hopes to bring it to other clinical sites.

• We saw the first-ever early concept designs of Dexcom Clarity with insulin, meal, and exercise data – these may change during human factors, but it’s great to see these are well along in development. The insulin and meal data are displayed in histograms above the modal day plot and time bucketed across the day. No timing was shared on a launch. Seeing these data streams in Clarity will be fantastic (especially insulin), though managing the complexity and data overload will rise with the number of streams coming in – otherwise it can be easy to get lost in reports and difficult to piece together what is driving what. Luckily small toggle switches on the bottom of the graph will allow users to turn insulins, exercise, and meals on/off. Plus, decision support will hopefully be layered on top pull out clear patterns.

• Dexcom’s Gary Cohen also showed Clarity use on the clinic side – 83,800 “newly created patients,” of which 84% were invited to share their data with the clinic (70,099) and 48% are currently sharing their data (40,132 acceptances). This has seen a nice uptick in the past year. The Clarity OUS base seems to be ~10-fold smaller, with 8,668 users created in clinics – part of this relates to the smaller Dexcom OUS user base and the shorter time that Clarity has been available OUS. As we understand it, the number of “newly created patients” understates the total Clarity user base, since an account can obviously be created outside the clinical setting.

• Dr. Heintzman shared an update on Dexcom’s public API, which now has more than 500 registered third party developers that have created over 400 prototype apps. Dexcom’s data partners have launched ten apps that use the API, including One Drop, Glooko, Tidepool, Nutrino, and Rimidi – for a complete current listing of Dexcom Data Partner apps, see the App Gallery here. Dr. Heintzman showed how easy it is to set up for a user – from the Glooko app, for instance, a user goes to settings, taps on the Dexcom account, logs in to Dexcom (via OAuth2), and authorize Dexcom to send data to the partner app. We hope to see this public API generate a thriving CGM data app ecosystem, especially as it hopefully moves to real-time data. For a complete current listing of Dexcom data partner apps, click here.

• “Sometimes you miss some things when you just look at AGP. You need to look at 2-3 reports to find everything.” Dexcom’s Keri Leone made this point with an example: a pattern of hypoglycemia that was not noticeable in AGP, but was very clear in Dexcom’s more brightly color-coded modal day plot. We like that mantra – HCPs and users should look at a few reports (if possible) to triangulate views on what’s going on.

Medtronic Last Major CGM Company to License Ambulatory Glucose Profile (AGP) Report, According to IDC’s Dr. Deborah Mullen

Medtronic has reportedly licensed the one-page standard Ambulatory Glucose Profile (AGP) report, according to IDC’s Dr. Deborah Mullen – hooray! With this news, Medtronic joins Abbott, Dexcom, Glooko/Diasend, and Roche as the fifth major player to offer AGP to patients and providers – notably the last of the major CGM companies to do so. As a reminder, Dexcom was the most recent company to license the glucose data visualization report last June for integration into Dexcom Clarity, which is already live on the web and mobile app versions. We’re glad to see Medtronic now on board, a win for the field. We have heard murmurs that, even though companies have licensed the AGP, they still may have different specs that could confuse users. For example, the margins around the median trace may be the intended 25%/75% and 10%/90% for one company, but different for another. As noted above, it’s also going to be important for companies to continue innovating on reports, as AGP shares a lot but the single graph won’t catch everything.   

• During her presentation, Dr. Mullen highlighted the value AGP has in the clinic: ~90% of patients and providers say it helps them see new patterns, and almost 98% say it lets them find new opportunities for improving glucose management. She also shared plans to make the AGP visualization “a little bit prettier” over the next few months – we’re excited to see what they come up with, as better and easier-to-use visuals could be a big plus for engagement and usability.

Abbott Orals Detail Use of FSL in Belgium (Natl Reimbursed Market) and in At-Risk Individuals Over Six Months

Dual Abbott oral presentations detailed use of FreeStyle Libre in Belgium (where the system has been fully nationally reimbursed since mid-2016) and the longitudinal impact on “high-risk” patients, respectively. Of note, Abbott’s Dr. Tim Dunn foreshadowed both of these analyses at DTM, and also suggested that further analyses could identify strategies of Libre usage (around hypoglycemia, pre/post-meal, insulin dosing, and exercise) that beget glycemic success. We were impressed by these two orals, but are especially looking forward to that around strategies – what are the best practices for FreeStyle Libre usage to derive the most glycemic benefit with the least amount of effort/burden?

• Dr. Tim Dunn compared FreeStyle Libre use behavior and glycemic trends in Belgium (16,000 readers, 43 million monitoring-hours, ~5,000 patient-years of use) with that of all countries (~238,000 readers), finding similar results. Daily scans per reader were roughly on par, with Belgian users averaging 10 scans per day, and all countries averaging 13 scans per day. Belgium’s curves of daily scans vs. eA1c and time >180 mg/dl were nearly identical to the overall user base, but curiously, time-in-range and time ≤54 mg/dl vs. scan frequency curves were somewhat offset (see below). For some reason, the degree of improvement per scan (the slope, per sé) was roughly the same, but the Belgian cohort consistently spent 30-45 minutes per day less in-range at each scanning level, and 10-15 minutes more per day ≤54 mg/dl at each scanning level. Overall the results are not drastically different and support full reimbursement of FreeStyle Libre, but it would be interesting to dig deeper into the time-in-range and hypoglycemia discrepancies. Is it that baseline diabetes care in Belgium is worse than that in other FreeStyle Libre markets? Are there dietary or other cultural factors at play? Are there high levels of stigma sometimes preventing patients from taking action when they see (trending) out-of-range glucose values? Could there be incentives dynamics related to having zero out-of-pocket costs (unlikely, since scanning frequency is similar)?

  • This analysis immediately reminded us of a compelling EASD 2017 poster sharing 12-month healthcare outcomes from a national Belgian reimbursement study of CGM in 515 insulin pump users. Most notably, the percentage of patients experiencing a hypoglycemia/DKA hospitalization declined by a striking 75% following CGM initiation, and CGM drove a 64% decline in the percentage of patients experiencing a work absence. This sort of study would be a significantly bigger lift for Abbott, but we’d love to see broader outcomes, including health economics, included in these data sets, which would also make for a much more compelling story to pitch to payers.

• Shortly after Dr. Dunn’s talk, Abbott’s Dr. Sujit Jangam followed with a presentation of FreeStyle Libre data from high-risk individuals using the system over six months. The data set was populated by ~6,800 readers, ~67,000 sensors, and 21 million monitoring hours between September 2014 and May 2016. High-risk individuals were defined as individuals in the highest tertile of time >180 mg/dl (high hyperglycemia risk), and the same criteria was used for time <70 mg/dl and time ≤54 mg/dl to define high hypoglycemia risk. In all groups, scanning frequency started at ~20/day, and by two months, had decreased to ~15/day, which was sustained for the duration of the six months. In individuals with high risk of hyperglycemia, time >180 mg/dl decreased from ~54% of the day to ~50% of the day (-1 hour/day); Most of the changes occurred during the first two weeks of use and were sustained out to six months. The improvement was more drastic in higher- and medium-frequency scanners than in low-frequency scanners: high-frequency scanners saw a ~90-minute/day improvement in hyperglycemia vs. low-frequency scanners who saw a 45-minute/day improvement. Time <70 mg/dl in those at high hypoglycemia risk dropped from 14% of the day to 10% of the day (-45 minutes); Again, most of the improvements occurred in the first two weeks and were sustained out to six months. Interestingly, the improvement was similar between higher- and lower-frequency scanners. Last, time <54 mg/dl in those at high risk for hypoglycemia decreased from 6% to 4%, a 22-minute improvement that largely occurred within the first two weeks of use and was sustained to six months – we’d guess Abbott’s next-gen system with continuous communication (and presumably alarms) will further reduce what is still fairly significant dangerous hypoglycemia. Similar to previously-presented data showing scan frequency to be correlated to time ≤54 md/dl, the improvement was more marked in individuals that scan with higher frequency. The most surprising revelation from the analysis is that time <70 mg/dl is improved similarly in people at high risk of hypoglycemia regardless of scanning frequency.

Questions and Answers

Q: What is the least number to scan to have good results? We can say to the patient at least one per hour?

Dr. Dunn: In that eight to ten range, as with typical plateauing of relationship. But there’s a lot of variability, some people are more effective than others. Yes, one per hour would be pretty great.

Q: Any data regarding exercise?

Dr. Dunn: In theory, we don’t have that data yet. The device does have a logbook for insulin, food, and exercise, so we hope to address that.

Q: Does distribution of scanning throughout the day matter? If someone clustered in morning, compared to someone scanning every three hours, maybe adjust for that?

Dr. Dunn: Yes that falls in the category of more personalized analysis, what is working…we need to do that analysis, but overall we see people scanning mostly during the day, maybe one or two overnight.

Q: What is the cause of reduction in scanning over time?

Dr. Jangam: As with any new system, there’s a lot of excitement as people figure out the right mode of operation for them, but in our data, even though we start with 20 per day, even by six months, they’re still at 14-15 scans per day, which is still a lot of scans.

FDA’s Dr. Stayce Beck on Advances in CGM, device interoperability (“key to patient choice”), label claims, and accuracy

FDA’s Dr. Stayce Beck shared valuable perspective on Advances in CGM technologies, including product claims, accuracy, and interoperability. The latter was a focus of the talk, reiterating FDA’s vision to have interoperable components that would allow plug-and-play AID systems. “The anticipated pace of AID innovation challenges the current regulatory framework for medical devices. Every time one of the components is modified, it has to come to FDA with a new submission. Users can’t mix and match systems that meet their needs…” She highlighted how lack of device communication and partnership contracts (e.g., between pump and CGM companies) have really slowed down the field – something FDA hopes to address with more interoperability. Dr. Beck added that “the key to patient choice is interoperability” and “interchangeability of AID components with an AID system would enable innovation and more rapid AID commercialization.” There’s no question FDA is sold on this concept, but the specific path forward remains a bit fuzzy, now 1.5 years after Dr. Lias first introduced this idea at the 2016 D-Data Exchange. Dr. Beck did allude to some possible progress: “we think we’re at a point where there is a technical solution to help with this” and “FDA is working on facilitating active discussion to openly solve these challenges.” These could imply a public meeting will happen at some point, a set of communication standards that will be recommended, or both. This would be amazing for patient choice, in line with JDRF’s open protocol initiative. As noted above, Roche announced it is IN on this JDRF initiative, a lead we hope other companies follow. Other insights from Dr. Beck:

• “We don’t care how the device works, we just care that it does work and it does what it claims to do. We look at inputs and outputs, meaning it can be a black box.”

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  “FDA is agnostic on device claims – we want advancements so that the American public can benefit. We even want to help you get there.”

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  “How do I get to say that my device can do ___? Do a risk analysis, design a study to show that your device can do ___. Complete the study in the population who will use your device. Have data to support that your device can do ___. Submit to the FDA.”

• “Risk analysis: what are the potential failures? What could go wrong, in an imperfect world, from both a tech and user perspective? What is the root cause of these failures? What are the potential effects of the failure? For instance, if I want CGM data to go to a phone, what happens if get a call? What if I close out of the app? What if I’m playing a game? What happens if a person thinks it is working? What happens if the phone is on mute, and they thought they would still get alarms from CGM? What can be done to mitigate the risks or prevent the failures?”

• In terms of CGM accuracy, FDA focuses on “agreement.” Compared to the lab based comparator method, what percentage of CGM data points are within 15% or 20% of reference? Dr. Beck showed the Dexcom G5 label as an example, where 93% of points are within 20%. FDA gets concerns when the values are very different and could be dangerous – for instance, when the CGM reads 40-60 mg/dl and the lab comparator reads over 300 mg/dl. “This means 7-8 times in this study, the CGM indicated the person was low, but in fact was very high. In those situations, we’d investigate further. Was this only one person, or did this happen to multiple people? We use all that information to decide how to approve a device.”

  • Dr. Beck encouraged developers to look at approved devices’ Summary of Safety and Effectiveness Data” (SSED) for a good sense of what FDA really cares about.

Guardian Sensor 3 Pediatrics (2-18) Accuracy Trial: 2-Cal MARD 10.9%, 3-4-Cal MARD=10.1%

Medtronic CMO Dr. Fran Kaufman’s talk was so rich with new data that we had to split it into two highlights: In this edition, she briefly presented a pediatric Guardian Sensor 3 accuracy trial (initially shared by Dr. Jennifer Sherr at ISPAD) that found twice-daily calibration MARD to be 10.9% (YSI/SMBG unclear). The trial enrolled 145 patients ages 2-18 who underwent a six-hour frequent sample test on day one, three, or seven. It will be key to get a pediatric label in the US, given how fast peds CGM penetration is rising in the US! With 3,102 paired points, two calibration MARD was 10.9%, but with larger-than-expected error bars (10.7%). 2,890 paired points for 3-4 calibrations (reflecting the current recommendation for adults) yielded a slightly improved MARD of 10.1%, plus/minus 9.3% on either end. In the 670G pivotal trial for 7-13 year olds, the sensor and I-STAT instruments showed fairly high agreement, with 68% of sensor readings and ~66% of I-STAT readings falling between 70-180 mg/dl. As noted elsewhere in this report, the percentage of points in hypoglycemia was quite low at 1% in this trial. Guardian Sensor 3 is undoubtedly a major accuracy improvement for Medtronic, but still has some catchup to play on calibration and form factor to Dexcom’s G5 (MARD 9.0%, two cals/day), Abbott’s FreeStyle Libre (US MARD: 9.7%, no-cal), and the upcoming no-calibration G6 (MARD of ~9.0%, see above; expected in the US in 2H18). Notably, we learned today that the Dexcom G6 will be indicated for 2+ years old, ahead of Abbott’s US FreeStyle Libre (18+ years; currently recruiting for US pediatric trial) and Medtronic’s Guardian Sensor 3 (currently 14+ years but likely to change with this pediatric submission and that for the 670G).

Real-World Medtronic Guardian Connect Data Shows Predictive Alerts to Reduce Glycemic Excursions; Integration with Android “a Number One Priority”

Medtronic Diabetes Medical Affairs Director Dr. Ohad Cohen presented real-world data uploaded to CareLink by 2,541 patients on the Guardian Connect standalone mobile CGM. Notably, predictive alerts reduced glycemic excursions for hyperglycemia and hypoglycemia by 39% and 60%, respectively. Hyperglycemic and hypoglycemic excursions were defined as ≥three consecutive sensor values (≥15 minutes) beyond the high (210 mg/dl) and low (70 mg/dl) thresholds. The window of evaluation for excursion start times was 60 minutes following the alert, as predictive glucose alerts can be set to notify users 10-60 minutes prior to a predicted low or high glucose excursion. Not only did predictive alerts help users to avoid excursions, they also significantly reduced the number of excursions lasting more than 60 minutes. This study shows the power of predictive, prospective alarms and analytics in diabetes – in addition to preventing dangerous and uncomfortable glycemic events, it provides a learning opportunity without the classical “punishment.” Data were collected from users with ≥five days of sensor data from January 2, 2017 – January 2-2018. We’re not sure how much of a read on the user base this data set is – Medtronic has never shared how many Guardian Connect users there are worldwide.

• In today’s presentation, Dr. Cohen noted in response to an audience member’s question that integration with Android devices is a “number one priority.” Guardian Connect is available on iPhone in the EU and Australia and was FDA approved in March (limited US launch in May-July with Sugar.IQ). How will Medtronic’s iPhone app compare to Dexcom’s G5 app? When will Abbott be in the US with FreeStyle LibreLink on iPhone and Android? How far away is Medtronic’s Android in the US and globally?

• Dr. Cohen shared separate real-world data from 258 patients using Guardian Connect for at least nine months. Strong time-in-range (70-180 mg/dl) was apparent immediately (in the first month) and persisted throughout the period – as Dr. Cohen highlighted, not seeing a decline here is promising, though obviously consistent with the benefits of real-time CGM. It’s unclear what the baseline time-in-range was (pre-Guardian CGM), which prevents conclusions about relative efficacy. On average, users spent 61% of the time in range, 35% of the time in hyperglycemia (>180 mg/dl) and 4% of the time in hypoglycemia (<70 mg/dl).

• Dr. Cohen detailed real-world data from 3,263 patients collected over January 1, 2017-January 15, 2018, showing the high sensor glucose alert to be by far the most commonly utilized alarm – on average, this alarm sounded three times/day. Low sensor glucose and low predictive glucose alerts tied for second, averaging twice/day. Following them were notifications for high predictive glucose (once/day), falling glucose (once/day), and rising glucose (less than once/day). Dr. Ohad emphasized that these alerts are highly customizable, as users not only can select specific alarms and choose distinct thresholds, but also can adjust the alarms’ individual timing, ranging from 10-60 minutes prior to an event. Like Dexcom Share, CareLink Connect users for remote monitoring can also customize alarms; one audience member gave an example of a parent using predictive and sensor glucose alarms, while the child uses only sensor glucose alarms.

Abbott: Real-world FreeStyle Libre data in 250,000+ users, including longitudinal data from sub-group of n=6,802 over six months

Dr. Ramzi Ajjan showed more real-world FreeStyle Libre data from 251,875 readers, including a fascinating longitudinal six-month analysis in 6,802 people. Interestingly, over the six-month period, users reached the same reduction in time in hypoglycemia regardless of scanning frequency – those with a higher scanning frequency just achieved it faster. However, scanning frequency affected time in hyperglycemia to a greater extent - lower frequency scanners never reached the same reductions in hyperglycemia as higher frequency scanners over the entire six-month period. See the slides below, which segment the user base by scanning frequency and show hypoglycemia (left) and hyperglycemia (right) outcomes on a per-sensor basis over six months – very cool! Interestingly, separate slides showed that the majority of reductions in time in hypoglycemia occur within the first two days of using the sensor! Talk about real-time data having an impact quickly…

Ascensia: BGM and CGM – Is There Only One Future?

A well-attended Ascensia symposium tackled the fascinating topic – what will glucose monitoring look like in the foreseeable future? How will BGM and CGM co-exist? The session included market insights from our own Adam Brown, MGH’s Dr. Steve Russell on use of BGM in automated insulin delivery, and accuracy talks from Drs. Guido Freckmann (Institut für Diabetes-Technologie) and Marc Breton (UVA). Highlights below!

• Adam Brown used dQ&A data to illuminate what’s happening in the US and Europe with glucose monitoring – download his slides here. He started with a summary of fingerstick frequency in type 1 and type 2 diabetes in the dQ&A panels, which remains low – 59% of type 1s in the US panel take fewer than five fingersticks per day, while 66% of type 2s take fewer than three fingersticks per day. The connected meter penetration data was also striking: in the dQ&A US panel (4Q17), only 8% of people are on a connected meter! (On the plus side, of newly acquired meters in 4Q17, the majority have Bluetooth.) Adam also touched on what drives patient choice of device – in the US, meter choice still comes down to insurance coverage (#1 in both type 1 and type 2), followed by a long tail of other reasons (it came with my pump or CGM, accuracy, smartphone integration). In Europe, the #1 driver of CGM choice is insurance coverage (60% said it had a big influence, the top of the list), but is closely followed by recommendations from doctors (59%), diabetes educators (51%), online reviews (48%), and other people with diabetes (43%). In terms of CGM growth/penetration, Adam showed the strong user base growth for both Dexcom (270,000+ users worldwide as of 4Q17) and Abbott (~450,000 users worldwide as of 4Q17); however, CGM is still reaching a slim 24% of people in the T1D Exchange (the best US centers), ~1%-3% of insulin users worldwide, and <0.5% of the global diagnosed diabetes population. Last, his slide on endocrinologist preferences was fascinating – prescribers in the dQ&A endo panel have strong preferences amongst the various glucose monitoring options. The vast majority of endos (62%-78%) prefer CGM with alarms for type 1s, while FreeStyle Libre was the most preferred device for type 2s on insulin (53% of endocrinologists). “Glucose sensors not needed” was the most preferred option for type 2s not on insulin (50% of endocrinologists). Download Adam’s slides here for all the data and dQ&A insights, and contact dQ&A CEO Richard Wood for more details.

• Dr. Steve Russell gave an outstanding talk on the importance of accurate BGM for automated insulin delivery, sharing his pyramid of diabetes tech with BGM at the bottom, CGM above it, and automated glucose control on top – without accurate BGM, the whole system breaks down. Indeed, he noted that in MGH’s studies, meters have varied in accuracy quite widely: Nipro’s sidekick had a MARD of over 20%, with the best meters coming in at an MARD of ~5%-6% MARD (e.g., Ascensia’s Contour Next). Dr. Russell recognizes the benefit of factory calibrated CGM systems like FreeStyle Libre, but he doesn’t believe they are currently ready for prime-time use in automated systems. “Libre doesn’t have the same accuracy as CGM. Worse, when it is off, there is nothing you can do about it. It cannot be calibrated.” Dr. Russell astutely noted that in automated control, users are spending a lot of time near hypoglycemia. If the CGM is miscalibrated with an inaccurate BGM, it could lead to quite dangerous situations. BGM accuracy “may not be as critical if people are floating high all the time” – e.g., the average blood glucose in adults with type 1 diabetes in the US is around ~200 mg/dl (reflecting an A1c of ~8%) – but with the Bionic Pancreas, the average glucose often comes in around 115-130 mg/dl. “[With automated control] there is almost no margin for error anymore.” Last, he noted that in systems requiring less fingerstick calibration, each BGM measurement becomes that much more important. Great points, and ones we’ll be fascinated to follow as Dexcom’s no-cal G6 is used in automated systems (with the option to enter a calibration in cases where the sensor may be off).

• Meanwhile, scientific talks from Drs. Guido Freckmann and Marc Breton touched on accuracy, emphasizing that MARD is an incomplete measure of CGM accuracy – both are fans of adding %20/20 and %15/15 as additional metrics to characterize accuracy, especially because MARD misses outliers. Noted Dr. Breton, “MARD hides fairly broad differences.” Interestingly, a MARD of 10%-12% has the “widest predicted range of % 20/20 performances. “MARD by itself,” said Dr. Breton, “is likely insufficient for accuracy characterization, and in fact may obfuscate significant differences, potentially leading to erroneous conclusions.” (FDA has moved in this direction in a big way with the new special controls focused on the accuracy of “integrated CGM” (iCGM). For now, only Dexcom’s G6 is cleared in this way, but we expect others will follow.)

9.5% One-Cal MARD for Senseonics Eversense in PRECISE II US Pivotal; Eversense Now Remote Monitoring App Cleared for Use in EMEA

During Roche’s symposium, Senseonics CMO Dr. Lynne Kelley shared an unpublished sub-analysis from the US PRECISE II pivotal study of the Eversense implantable CGM: Solid MARD of 9.5% vs. YSI, compared to 8.8% vs. YSI with two calibrations per day. The excellent two-cal accuracy in hypoglycemia (≤80 mg/dl) of 9.6 mg/dl is also largely maintained, with MAD rising just to 10.2 mg/dl with one-cal. Excluding hypoglycemia, MARD is 8.2% with two calibrations per day and 8.9% with one calibration per day. No zero-calibration data was broken out, though we’d be curious to see it, particularly since the sensor has 90 days during which the signal could potentially drift. Importantly, with just one calibration per day (as many users would certainly use it), Eversense still meets the much-publicized ~10% MARD recommended by Kovatchev et al. for non-adjunctive use. Eversense is now in 14 countries (13 in the EU) and still under FDA review, following the unanimously positive FDA Advisory Committee vote one month after ATTD. Notably, some patients in the real world are now on their seventh 90-day sensor and there have only been “single-digit numbers of complains of skin reactions in the commercial launch.”

• In a study conducted at LMC Healthcare in Toronto (n=36), an impressive 78% [CI: 65%-93%] of the 180-day Eversense XL sensors made it the full six months without having to be extracted. As can be seen in the Kaplan-Meier survival curve below, 95% of sensors were working at 90 days and 94% of sensors were working at 120 days – what presenter Dr. Alex Abitbol called “fairly robust performance.” Of the eight sensors that were removed prior to 180 days: One participant withdrew consent one day after insertion; One participant’s sensor was removed at 93 days due to connectivity issues; and there were a number of early sensor replacement alarms after day 130 (one on day 136, one on day 142, three on day 146, and one on day 165). For a first-to-market long-term implantable sensor in the real-world, this is a very strong performance, and we imagine it will only improve. According to Dr. Kelley, people actually forget they’ll need to change out their sensor, so Senseonics has added a phone notification at 150 days to remind patients it is time to make an appointment to change their CGM – talk about reduced burden!

• Dr. Abitbol wasn’t at liberty to share accuracy data from the LMC study in the form of MARD, but he could share the consensus grid error analysis (below). Compared to YSI, the sensor performed very well, with ~93% of readings falling in Zone A and ~6% in Zone B.

• CE Mark for Eversense Now, an app enabling remote monitoring, came in during ATTD. Eversense users in EMEA markets now have the option to invite up to five others to remotely view their real-time glucose readings and alerts. This feature will be a huge plus and will help appeal to the pediatric cohort. The updated Eversense app and the Eversense Now app will both be available for free on the App Store later this month (development for Android is in progress)

• Endocrinologists have now been trained on the insertion procedure at over 375 centers. Dr Steve Russell shared his early positive views last December at IDF. Each insertion, done by endocrinologists with little advanced procedural training, reportedly takes just 5-10 minutes and it generally takes one to three tries for a doctor to become comfortable with the procedure. This aligns with what we have heard from KOLs in the field who have complimented the simplicity and accuracy of Eversense. Scaling manufacturing will be key for the company to demonstrate – our sense is the launch is still fairly limited.

Extended iHART CGM: Nearly Two Hours Less Time <70 mg/dl Per Day in FreeStyle Libre Users Who Switched to Dexcom G5 for Eight Weeks

Imperial College of London’s Dr. Monika Reddy presented extended data further supporting the results from the head-to-head iHART CGM study comparing the Dexcom G5 and Abbott FreeStyle Libre in type 1 adults with impaired hypoglycemia awareness. Following the eight-week trial randomizing patients to receive either the G5 or FreeStyle Libre, all participants were given the option to continue with the Dexcom G5 for an additional eight weeks. 16 patients originally on the G5 and 20 patients originally on FreeStyle Libre chose to continue with the G5. Results showed that those who switched from FreeStyle Libre to the G5 significantly decreased time <70 mg/dl from 11% to 4% (-1.7 hours/day), while those initially on the G5 showed no significant difference in time in hypoglycemia, decreasing slightly from 6% to 5% (-11.5 minutes). Those who switched from FreeStyle Libre also reported significantly improved time-in-range, increasing from 60% to 67% (+1.8 hours/day). Again, those who were originally on the G5 did not show significant changes in time-in-range. There were no significant changes in A1c over the extended eight-week period for either group, indicating that glycemic control was not ceded for the hypoglycemia improvements. The data serve to further confirm the results of the original iHART CGM study, suggesting that for those with impaired hypoglycemia awareness, G5’s alarms can be incredibly beneficial in reducing hypoglycemia and improving time-in-range. As we noted in our initial coverage of the eight-week study results, head-to-head device trials like this are very valuable and will help the field determine recommended devices in sub-populations, especially as great CGM options continue to proliferate.

MDT’s ADJUST Prelim Results: Through 8 Months, Intermittent Use of Blinded iPro2 Pro CGM Confers 1.0% A1c Drop (Baseline: 9.4%)

Diabetes Portugal’s Dr. Rogerio Ribeiro presented highly encouraging preliminary results from the (uncontrolled) ADJUST study of Medtronic’s blinded iPro2 professional CGM in 102 people with insulin-treated type 2 diabetes and A1c ≥7.5% (at this point, 92 people have completed eight months of the study). Through eight months of a regimen of one professional CGM every four months (three CGM sessions thus far), A1c in the study population fell 1.0% (baseline: 9.4%). Mean glycemia and percent time >180 mg/dl significantly improved after eight months – actual numbers weren’t provided, but it appeared based on graphs that mean glycemia dropped from ~185 mg/dl at baseline to ~175 mg/dl at eight months and that percent time >180 mg/dl dropped from ~45% at baseline to ~40% at eight months (a little over +1 hour/day improvement). Importantly, these changes were achieved without an increase in the frequency of or percent time in hypoglycemia, though participants’ baseline time <70 mg/dl was already a fairly low ~1.3%. Time >180 mg/dl even dropped overnight (~40% to ~25%; -54 minutes, assuming a six-hour nighttime period) without a concomitant increase in hypoglycemia. Researchers have kept close tabs on therapeutic decisions, with interesting findings: After the first iPro2, 73% of patients had pharmacological and behavioral parameters adjusted. This number shrinks after the second (40%) and third (28%) iPro2, indicating that repeated use helps patients and providers zero in on the causes of hyperglycemia (or hypoglycemia). Patients in the study reported roughly the same treatment satisfaction after eight months, though they do perceive slightly better outcomes with respect to hypoglycemia and hyperglycemia. Qualitatively, participants said mostly positive things such as “It helped me understand my disease, and my behaviors,” “It got me to do physical exercise,” and “It seems that I began to trust more the healthcare team.” Administering healthcare providers also reported overwhelmingly positive experiences: “Contributed to better therapeutic relationship and positive results on metabolic control” and “the patients themselves understood how they had to improve and why they improved.” These early data look terrific and are highly encouraging for the use of intermittent CGM in type 2s, especially those with high A1cs. We look forward to seeing the complete set after 12 months! We consistently hear similar enthusiasm regarding Abbott’s FreeStyle Libre Pro, and hope to see both Medtronic and Abbott and others drive CGM in a big way into primary care and non-intensive diabetes management. We’d love to see greater awareness and use of professional intermittent CGM (blinded or unblinded, depending on the scenario), as it should be more cost-effective than 24/7 real-time CGM and could be very useful in titrating or changing medication and influencing behavior change.

• Medtronic’s booth touted the iPro2 CareLink pattern snapshot feature, which provides the top three trends identified over the six-day period, along with possible causes. Possible patterns can include hypoglycemia at night, glycemic variability at night with hypoglycemia, and so forth, and they are presented in order of clinical importance. (This Pattern Snapshot launched back in November 2015 and we believe it is among the strongest CGM analytics in diabetes.) In one example, a patient’s number one trend was variable sensor glucose from 11 pm-6 am); three days, glucose was between 50-100 mg/dl in that window, one day it fell below 50 mg/dl, and six days it rose above 150 mg/dl. The software then offers a number of suggestions: Oral medication(s) too high or incorrectly timed? Basal insulin injection in evening(s) too high or missed? Pre-meal insulin in prior evening(s) incorrectly timed or incorrect dose? Inconsistent food intake day before? Inconsistent exercise schedule day before? Alcohol consumed in prior evening(s)? CareLink does not integrate with the EMR at this point, precluding suggestions that leverage other clinical data, meaning the provider has to parse through some suggestions that may not pertain to the patient at hand. We still think this is an awesome feature that could make providers’ jobs easier and help them and health systems quickly figure out which patients need the most immediate assistance.

• In a Medtronic symposium, Dr. Robert Vigersky suggested that only three days of CGM may be necessary to derive actionable information about a patient with type 2 diabetes, adding that he doesn’t think there is any evidence for longer than six days. This was an interesting perspective, since many in the field are converging on 14 days as the ideal CGM period to get a sense of overall glycemia over three months – this is more focused on type 1 diabetes, however. The distinction is likely in the language: Three days of data could almost certainly provide a lot actionable data, but the Hawthorne effect is also a concern over such a short time period (i.e., people alter their behavior when they know they are being watched). When Dr. Vigersky polled the audience on the same question, 50% agreed that three days is sufficient, ~38% voted for 10 days, and ~13% voted for six days.

  • This is a key question for the field: when should intermittent CGM be deployed in type 2 diabetes, and how often? What is the minimum frequency for maximum benefits? When do returns start to diminish?

UVA BGM Accuracy Study: Least Accurate Meters Cost System Additional ~$433 Per Patient Per Year

UVA’s Dr. Enrique Campos-Nañez presented a fascinating analysis of the costs of inaccurate BGM, concluding that the least accurate meters on the market cost the system an additional 306 pounds (~$433) per patient per year compared to the “ideal BGM.” The most accurate BGM, he said, only costs 64 pounds (~$90) extra per patient per year. He and his team plugged accuracy data from 43 real meters into the UVA/Padova simulator, derived an A1c and hypoglycemia estimation, input that into the A1c translator, and then calculated costs based on country-specific cost data. All results were compared to the “ideal meter,” which brought simulated patients to an A1c of 8.75% with a severe hypoglycemia rate of ~1.5 events per six months (of course, these are still unacceptable figures for “ideal”). Instead of presenting costs for each meter individually, the group cleverly broke them down into groups based on whether they meet ISO 2003 and ISO 2013 BGM accuracy standards. For those meters that fell in the top half for performance of the cohort that surpassed the ISO 2013 bar, costs were 64 pounds (~$90) higher per person per year; for those meters that fell in the lower half of this cohort, added costs were 79 pounds (~$112) per person per year; for those meters that meet ISO 2003 standards but not the 2013 update, average added costs were 216 pounds (~$305) per person per year; finally, for those meters that met neither criteria, added costs per person per year were estimated to be 306 pounds (~$433). The absolute worst meter reviewed costs 597 additional pounds (~$844) per person per year! To summarize, the simulation estimated that system costs are ~80% lower with an accurate vs. inaccurate BGM! Based on results from the DTS BGM Surveillance Program where 12/18 meters failed to meet DTS standards, many patients are using inaccurate meters, not only putting themselves in danger, but also driving system costs. To illustrate our point, a quick calculation last year suggested that ~68% of Medicare mail-order BGMs in 2016 did not pass DTS standards! Our other big question is where CGM fits into the mix, cost-wise? How would it compare to the ideal BGM in terms of cost per patient per year, and what are the net savings relative to SMBG (since SMBG is cheaper)?

Selected Questions and Answers

Dr. Rolf Hinzmann (Head of Global Medical & Scientific Affairs Glucose Monitoring and Science, Roche): BGM is used to calibrate CGM as well, so when you have a poor meter, you carry forward a wrong-measuring CGM until the next calibration. Do you think it’d be possible with your model to demonstrate that if you use poor BGMs to calibrate CGM, you have higher healthcare costs?

A: We have done such a study, showing that calibrating with an inaccurate meter has similar relationships, though that was not carried all the way out to healthcare costs.

CGM Poster Highlights

Title	Details and Implications
Insights from Big Data (1): Viewing of Real-Time Continuous Glucose Monitoring Data and Its Impact 0n Time in Range	Dexcom poster showing anonymized G5 Mobile app viewing behavior and time-in-range (70=180 mg/dl) from 50,000 users who uploaded data in August 2017 Users viewed their G5 app screens ~9 times per day on average. Higher screen viewing was associated with more time-in-range, with diminishing returns (5 views/day: ~57% in-range; 10 views/day: 60% in-range; 20 views/day: 63% in range) This is reminiscent of Abbott’s real-world data showing correlations between scanning frequency and lower A1c, less time in hyperglycemia/hypoglycemia (most recent at ATTD, DTM) Dexcom presented a similar analysis of monthly Clarity logins vs time-in-range – see above.
Cost-Effectiveness of Real-Time Continuous Glucose Monitoring (RT-CGM) Compared with SMBG In Type 1 Diabetes (T1DM) Adults Using Multiple Daily Injections (MDI) From the Italian Perspective	The base-case incremental cost-effectiveness ratio (ICER) for G5 Mobile vs. SMBG was €18,409 per QALY – a huge benefit for G5 and well under the ~€50,000 threshold used  This type of evidence could help CGM gain even more payer traction, especially in MDI users
CGM Use With 0r Without Remote Monitoring During Pregnancies Associated with Type 1 Diabetes (T1D)	BDC study showing remote monitoring (Dexcom Share) during pregnancy improves glycemic outcomes with lower insulin use and improves neonatal hypoxemia vs. CGM alone The CONCEPTT RCT (presented at EASD 2017) demonstrated that CGM is very efficacious in pregnancy, even without remote monitoring and with an older Medtronic sensor We’d love to see this trial (remote monitoring vs. no remote monitoring) repeated in seniors! As it stands, Medicare still won’t allow remote monitoring of therapeutic CGM data in the US, despite its documented benefits in various populations – now including pregnant women. At Keystone, Dexcom alluded to soon-to-be-published data on Dexcom Share in seniors, though we’re not sure if it is out yet. The ongoing six-month Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) trial (n=~200) aims to provide evidence for CGM in those ≥60 years old. The study page does not mention remote monitoring, though it is using Dexcom CGM and might include it.
Different CGM Effects Of GLP-1 Receptor Agonist: Liraglutide Vs. Lixisenatide	It’s excellent to see CGM-based analyses comparing drugs head-to-head! Only liraglutide conferred a reduction in high glucose excursion frequency and area under the curve >180 mg/dl. Glycemic variability also improved among liraglutide users (n=50). Lixisenatide users (n=50) saw a decrease in area under the curve <70 mg/dl. This proof-of-concept study lends itself to Dr. Rich Bergenstal’s argument that CGM should be used in every CVOT (and every study, we would add). What can CGM tell us about drugs, specifically which individuals would derive the most benefit from which drugs? Medtronic CGMS Gold blind retrospective CGM was used… would a more accurate sensor reveal even more nuanced differences between the two drugs?
Sustained Reductions in Severe Hypoglycaemia with Continuous Glucose Monitoring: Real Life Clinical Experience	Retrospective analysis (n=75) from Drs. Pratik Choudhary, Stephanie Amiel, and colleagues. With CGM, mean severe hypoglycemia rate in type 1s dropped from ~7.7 events prior to CGM to ~1 event after one year of CGM use. Remarkably, the benefit was sustained for up to seven years, and the study had a median duration of follow-up of 46 months.
CareLink Analysis for Real-World Non-Adjunctive CGM Insights	Medtronic poster showing that boluses based on sensor glucose values (i.e., non-adjunctive bolusing) resulted in significantly less hyperglycemia/hypoglycemia than boluses based on SMBG alone. The data was retrospectively collected from 11,367 MiniMed Veo pump users. With 670G in US patients’ hands and going international shortly, plus the Guardian Connect standalone CGM still with FDA, an insulin-dosing claim is surely top of mind – especially because the Guardian Sensor 3 is more accurate than Medtronic’s previous sensor in the Veo.
Long Term Implantable Continuous Glucose Monitoring (CGM) System Demonstrates Benefits in Glycemic Control with Wear Compliance	Senseonics poster (n=51) linking high sensor usage to improved time-in-ranges. E.g., times-in-target (70-180 mg/dl) for those with >85% wear-time vs. <85% wear-time were 68% and 62%, respectively.

3. Pumps and Infusion Sets

Unomedical/Medtronic’s New MiniMed Mio Advance Insertion Set: Single Button Push, Fully Hidden Needle, Major Insertion Upgrade

In an interactive workshop, we were pleased to get our hands on Unomedical/Medtronic’s new MiniMed Mio Advance – an all-in-one, fully disposable insertion set with a hidden needle. It’s difficult to imagine a more user-friendly device: The MiniMed Mio Advance is ready-to-use upon unwrapping, inserts with the single push of a button, and can even be inserted one-handed for difficult-to-reach areas (see the demo here). It looks great for pediatric patients and elderly patients who may struggle to insert their infusion sets independently. According to workshop leader Dr. Carine de Beaufort, the MiniMed Mio Advance works with any insulin pump with a luer-lock connector, though it is only compatible with 6mm teflon tubing to date (other variations are on the horizon). Developed by Unomedical, we saw the set for the first time at ATTD 2017, and this year’s ATTD marked the initial launch in the UK, Italy and the Netherlands; Canada, Hong Kong and certain Europe/Middle East/Africa launches are expected by the end of April. The patient feedback has been quite positive: In a UK-based pilot launch test (n=24), 92% of participants claimed that the product is better than their current infusion set, 87% were “extremely” or “very” satisfied with the product, and it exceeded customers’ expectations for eight out of ten users. We’re glad to see a more intuitive and less intimidating insertion device, which looks even friendlier than BD’s MiniMed Pro-set (on which Medtronic is the exclusive partner). Given the debut in Medtronic’s session/booth, the set is clearly not launching in an exclusive partnership with a Luer Lock pump, as Unomedical told us last year.

Pickup Meta-Analysis Shows ~0.4% A1c Benefit and ~24 Units/Day Insulin Dose Benefit with Pump vs. MDI in Type 2s; Greatest Benefits in Type 2s with High Baseline A1c/Insulin Dose

Dr. John Pickup reviewed findings from his now-published meta-analysis on pump therapy in type 2 diabetes (Diabetes Care, May 2017), showing favorable reductions in A1c (~0.4%) and insulin dose (~24 units/day) as compared to MDI. These final results build on the preliminary data shared at last year’s ATTD, which was comprised of five studies randomizing 590 patients in total on MDI to either continue MDI or switch to an insulin pump. Mean A1c treatment difference was ~0.4% in favor of pumps (95% CI: 0.86%-0.05%), though Dr. Pickup underscored that the greatest benefit appears in people with higher baseline A1c. In the OpT2mise trial (n=331), mean A1c at baseline was 9%, and individuals in the pump arm experienced 1.1% A1c decline over six months vs. 0.4% in the MDI arm (estimated treatment difference of 0.7%, p<0.0001). In contrast, baseline A1c in Raskin et al. and Herman et al. was only 8.1% and 8.3%, respectively. In Raskin et al., A1c dropped 0.6% with pump vs. 0.5% with MDI after six months; in Herman et al., A1c dropped 1.7% with pump vs. 1.6% with MDI after one year, for a similar estimated treatment difference of ~0.1% (noticeably smaller than the 0.7% difference in OpT2mise). Dr. Pickup further highlighted the A1c optimization period in OpT2mise, which ensured that only people poorly controlled on MDI (A1c between 8%-12%) were randomized – these individuals thus experienced minimal additional benefit from continuing MDI and likely contributed to the larger estimated treatment difference. In RCTs without optimization, participants randomized to MDI continued to see some A1c-lowering over the course of the study. Mean insulin dose in Dr. Pickup’s meta-analysis was reduced by 0.25 units/kg with pump vs. MDI (95% CI: 0.31-0.19), and by 24 units/day (95% CI: 30.55-17.45). Once again, switching to pump therapy produced greater benefits in people with higher baseline insulin dose. Dr. Pickup described a ~21 units/day treatment difference between pump vs. MDI for a baseline insulin requirement of 90 units/day, which he said grows to a ~36 units/day treatment difference – “a tremendous improvement” – for those with a baseline insulin requirement of 150 units/day. He pointed out that most diabetes care providers probably do see a high proportion of type 2 patients with insulin requirements around 150 units/day, suggesting that there are many good candidates for pump therapy in the real-world type 2 diabetes population. There were no significant differences in body weight or BMI across all five studies in Dr. Pickup’s meta-analysis. The overall estimated treatment difference on body weight was 0.08 kg (0.18 lbs) with pump vs. MDI (95% CI: -0.33 kg-+0.48 kg), and for BMI was 0.00 kg/m² (BMI data was only available from four RCTs, not including Wainstein et al.).

• Dr. Pickup also showed how pump therapy is cost-effective compared to MDI for people with type 2 diabetes and high baseline A1c. He pointed to a study conducted in The Netherlands, which reported an ICER of 18,610 euros for a pump vs. MDI in a patient with A1c of 10%. ICER rises to 35,837 euros for someone with A1c of 9.5%, and to 62,895 euros for someone with A1c of 9% (more expensive than the typical 50,000 euro per QALY threshold endorsed by many payers). We found this to be quite compelling sub-population analysis, and in terms of expanding access to insulin pumps for the type 2 patient population, we have to start somewhere – pumps should be duly considered for individuals with higher starting A1c/insulin dose, who not only stand to benefit the most from switching to pump therapy, but also likely contribute the most to healthcare costs. That said, Dr. Pickup emphasized that various health systems around the world will approach the cost of insulin pumps in type 2 differently. How will the more cost-conscious healthcare systems view pump reimbursement, and will pumps be covered indefinitely or only until patients achieve some target A1c where cost-effectiveness may diminish? For now, this remains an open question. Cheaper disposable (yet fully-featured) pumps developed for the type 2 population like Insulet/Lilly’s U500 and U200 Omnipods as well as BD’s Swatch patch pump may help make a dent in costs while retaining benefits like connectivity. The type 2 pump market is severely underpenetrated, with other type 2 pumps/patch insulin delivery devices like Valeritas’s V-Go, Cequr’s PAQ, and J&J’s bolus-only OneTouch Via slow to roll out (the latter two haven’t launched at all, despite many years of development). Competitive pricing, outcomes, and cost analyses will continue to be key in getting insurance companies on board.

• The meta-analysis covered Raskin et al., Herman et al., Wainstein et al., Berthe et al., and Reznik et al. (OpT2mise).

Pump Therapy Has ICER of 47,834€/QALY for Type 2 Patients in Finland (Based on OptT2Mise)

Medtronic’s Dr. Alexis Delbaere presented fascinating results from a simulated cost analysis study determining the cost-efficacy of pump therapy for type 2 diabetes patients in Finland. With a 0.32 improvement in QALY, the incremental cost-effectiveness ratio of pump therapy was shown to be 47,834€/QALY, allowing pump therapy to just squeak in under the bar for cost-effectiveness in Finland, which reports an acceptable willingness to pay of ~50,000€/QALY. The IQVIA Core Diabetes Model was used to calculate diabetes-related complication incidence and associated costs, including treatment and productivity, for pump and MIDI users. Clinical data were derived from the randomized controlled trial OpT2mise (n=331), which showed pump therapy (n=168) to result in a significantly greater A1c reduction of 1.1% (baseline: 9.0%) at six months as compared to MDI (n=163), which resulted in an A1c reduction of 0.4% (baseline: 9.0%). Diabetes-related complication and intervention costs were sourced from Medtronic (the MiniMed 640G pump was used) and from published and official tariffs specific to Finland. Not surprisingly, the cost analysis revealed pump therapy to be roughly twice as expensive as MDI, with higher annual direct costs partially offset by savings due to expected reductions in diabetes-related complications. Direct treatment cost for pump therapy totaled 3,749€ in the first year of use, decreasing slightly to 3,494€ in the following years due to reduced need for patient training. MDI annual costs were estimated to be stable at 1,806€. Compared to MDI, pump users saw estimated cumulative incidence reductions after five years for eye diseases (-24%), renal diseases (-28%), ulcers/amputations (-17%), and cardiovascular diseases (-5%). In fact, average lifetime costs/patient for complications and management totaled 51,000€ for pump users and 60,000€ for MDI patients – a 15% reduction. We find such cost analyses incredibly important, especially in the type 2 population, and we wonder if they will serve to convince payers to expand pump reimbursement in type 2s with high baseline A1c’s – particularly given the monthly cost of expensive type 2 diabetes drugs. This observational type of study raises the question of whether or not the type of patient who would end up on a pump would have similarly low costs had he/she stayed on MDI – ultimately, this is a question for RCTs and crossover studies to answer, though they are not without their pitfalls too.

Immediate Pump Therapy Initiation Results in 1.1% Lower A1c in Four-Year Observational Study

Ms. Deborah Foskett (Insulin Pump Angels, Australia) presented compelling data indicating significant A1c reductions in children that initiate pump therapy within one month of their type 1 diabetes diagnosis (n=38) as compared to those who waited one year (n=37). At the end of the 48-month study, early initiators reported significantly lower A1c (6.8%) as compared to late initiators (7.9%). Specific baseline A1c values were not provided, but from the graph below, it appears the early initiators demonstrated substantially higher baseline A1c values, which very likely impacted the subsequent decrease. Still, given that the results were maintained over four years, Ms. Foskett makes a good point that immediate initiation of pump therapy offers tremendous potential value in children with type 1 diabetes. We wonder how the results would look for CGM or AID initiated within month of diagnosis! There were no differences in the rate of severe hypoglycemia events between groups, nor were there significant differences in quality of life between groups, with both early and late adopters reporting high satisfaction. Of course this study is not free from confounds – i.e., what kind of patient/family waits to initiate pump therapy vs. starting right-off-the-bat – but it is a useful data point.

Real-World Data Shows Cellnovo System Reduces Hypoglycemia Events per Week by 29% in Adults and 39% in Adolescents; 0.5% A1c Reduction

Cellnovo’s Dr. Olivia Hatier-Suply shared real-world retrospective data (n=599) showing that use of the Cellnovo System in type 1 diabetes significantly reduced the number of hypoglycemia events per week by 29% in a sub-cohort of adults (n=143; p<0.00001) and 39% in a small sub-cohort of adolescents (n=7; p=0.05). Over a median follow-up period of one year, the retrospective analysis included a total of 166 patients who had used the pump for at least six months and had recorded their BG at least three times a day on average. The mean number of hypoglycemia events per week decreased from 3.4 to 2.4 in adults and 3.8 to 2.3 in adolescents. Children (n=16) saw a non-significant downward trend, decreasing from 3.7 to 3 events per week. The retrospective study was recently published in European Endocrinology. (Neither the publication nor the ATTD presentation provided the definition of a hypoglycemia “event” used in the study, but presumably it was a single measured blood glucose value under ~70 mg/dl.) Changes in average blood glucose were only found to be significant in the adult sub-cohort, increasing slightly from 163 mg/dl to 169 mg/dl (p=0.01). Strangely, in a separate sub-cohort of 30 adults with A1c measurements more than 90 days apart, A1c actually decreased by 0.5% (baseline 7.7%) after a mean follow-up of 10 months. 70% of these patients reported A1c improvements, with those reporting higher baseline values unsurprisingly observing greater reductions. It is odd to see a slight increase in average glucose in adults at the same time A1c declined, though the cohort sizes were different.

4. Digital Health

DreaMed Demos CE Marked Advisor Pro Decision Support for Pump Settings – Great User Experience on Glooko Population Tracker; Summer 2018 Soft Launch in Europe; Submitted to FDA

To a standing-room-only audience, DreaMed demoed its CE Marked Advisor Pro clinical decision support software for optimizing pump settings, which gives HCPs specific pump basal, insulin:carb, and correction factor adjustment recommendations based on CGM data – the user experience on the Glooko web-based Population Tracker looks great (see pictures below), and the company is here in the exhibit hall looking for early adopter clinics. A press release went out during ATTD sharing that the decision support software has received a CE Mark, and a soft launch will occur this summer in Europe. Great news! The product has also been submitted to FDA, a big milestone and major progress in the past year. Once a provider approves the dose changes on the Glooko web app, they can send them to a patient electronically. A seven-center, n=112 Helmsley-funded study is ongoing in the US, Europe, and Israel, with results expected by the end of 2018. The aim of the study is to assess the ability of Advisor Pro, as compared to diabetes experts, to adjust blood glucose levels within a predefined range and to prevent hypoglycemic events during a six-month intervention period. We’ll hear more from DreaMed later in the week.

• We really like the specificity of the insulin dose recommendations, and if a provider does not like what the algorithm specifies, the parameters can be edited. From the cases we saw, Advisor Pro tends to expand the number of time segments for a given setting (e.g., instead of three basal time segments throughout the day, it might expand to six), and also fine-tune parameters at a more nuanced level than most humans would (e.g., 28 mg/dl). We found the “diabetes management tips” to be fairly generic – e.g., “Many of your highs may be avoided. Delivering an insulin bolus for every meal and snack may help you get better outcomes.” However, the insulin dose recommendations look very strong, and even fairly basic diabetes management tips will certainly help some patients.

• From what we saw, there’s no question that this decision support is better than current standard of care, but convincing providers will be the key step to success – will they use clinical decision support? Will they pay for it? DreaMed positioned this as a more efficient way to crunch data, a way for providers to spend more time talking to patients in clinic, and a tool to support communication in between appointments – all great points.

Glooko’s MIDS Basal Insulin Titration System Receives FDA 510(k) Clearance; 18 Months Collaboration with Experts, $10s of Millions Invested to Deliver MIDS

Glooko CEO Mr. Rick Altinger announced that the company’s Mobile Insulin Dosing System (MIDS; basal insulin titration) has been cleared by the FDA after a ≥nine-month review. See below for the second and most up to date screenshots of MIDS (see the first from ATTD 2016) – the interface appears to be very intuitive, as we’ve come to expect from Glooko. This news comes after substantial back-and-forth with the Agency, and makes Glooko the seventh (by our count) basal titration system to have received FDA clearance – see the others here. We’re excited to see how quickly the number of products has increased, and now it’s about go-to-market, business models, and getting providers on board to prescribe these products. According to the press release announcing FDA clearance, Glooko engaged in 18 months of collaboration with experts around the world to design and develop MIDS. Mr. Altinger noted in his presentation that Glooko has invested “tens of millions of dollars” in the system – far more than we would have guessed. User experience design reviews, human factors studies, pre-market programs, and feedback sessions all contributed to the ultimate delivery of MIDS. At DTM 2017, we saw encouraging data from Glooko’s 14-day MIDS feasibility study (n=14 type 2s): average blood glucose dropped 18 mg/dl (baseline 164 mg/dl), the proportion of in-range readings (80-180 mg/dl) increased by nine percentage points (baseline 64%), and the proportion of hyperglycemic readings (>250 mg/dl) decreased by 11 percentage points (baseline 14%). In today’s presentation, Mr. Altinger did not mention the larger clinical study currently underway investigating MIDS in 240 type 2 patients with Novo Nordisk’s Tresiba. The 16-week study is still listed as recruiting on CT.gov, with an expected completion date of November 2018. As a reminder, MIDS analyzes patients’ fasting blood glucose levels and recommends insulin dose adjustments based on the provider’s pre-configured treatment plan.

• Glooko is currently used by 7,000 providers and over 1.5 million people with diabetes, resulting in over 8.5 billion data points – wow! Glooko is compatible with 180 devices and is now available in 24 countries (up from the most recent update of 23 countries) and in 15 languages.

Roche: mySugr has ~1.2 million registered users, ~50% type 2; Accu-Chek View weight loss results

At a Roche symposium, mySugr said that it now has ~1.2 million registered users, half of which are type 2! We were very excited to hear this on the type 2 front. In the same session, a German GP shared encouraging weight loss results from an RCT of Roche’s Accu-Chek View, calling it  “one of the best developments over the last months and years,” and, crucially, that “the effort we put into these patients is minimized compared to usual care.” This is the most we’ve ever heard on the Accu-Chek View prevention program, and are excited to know that it leverages PCPs while also reducing their burden – this could be a recipe for scale, and it is notable that the program is already supported by statutory health insurance in Germany.

Medtronic’s Diabeter Update: ~2,500 Patients and Counting; $75,000 est, Savings per Patient Over Lifetime; Cool Ther@pyMail Feature

Diabeter’s visionary founder Dr. Henk Veeze provided an update on the Medtronic-owned chain of Dutch clinics with an advanced integrated care model that delivers value-based medicine. During the course of the rapid-fire talk, he shared news of an expanded user base, detailed Diabeter’s superb outcomes, cost per-patient, and move to bundle-based payments, introduced the access-anytime Ther@pyMail service, and offered a number of quotes about Diabeter’s value proposition. Spoiler, our favorite is: “If you have $1,000 to spend, you better invest in diabetes care, because you get far more than on best day in stock market.”

• Diabeter now takes care of nearly 2,500 patients, up from just 200 a decade ago, and is beginning to take care of adults (past the age of 25) who don’t want to age out of the Diabeter model. Dr. Veeze’s clinic has now hired three internists, and the group is seeing solid growth and distribution across the Netherlands. We believe patient advocacy – people who were a part of Diabeter but refuse to leave upon turning 25 will not only drive growth, but also indirectly make the rest of the health system want a piece of Diabeter’s model.

• As depicted in the image below, Diabeter’s patients have lower A1cs compared to other clinics in the Netherlands, and even relative to the T1D Exchange. These improved outcomes, according to Dr. Veeze’s model of complications and costs, could save a system with 30,000 type 1s (A1c=9%) $2.2 billion over a child’s lifetime ($75,000 per patient). ~$41,600 of these savings come from complication reduction, while ~$33,000 come from improved productivity. Regarding bundled payments, Diabeter teams up with Diabstore to provide medical devices and hospital care, but is also responsible for 100% of all costs, including other healthcare providers, other suppliers, and pharmaceuticals; any profits in the case of a same or lowered bundled costs are shared.

• Ther@pyMail is an on-demand email report that patients can receive after uploading their data. Within five minutes, they receive the report, which includes a color-coded heat map of their recent blood glucose values, insulin dosing advice, bolus recommendations, comparisons to “patients like me,” and more. WOW! We still have a long way to go on this front across the world, even in tech-savvy clinics. We love this feature, and according to the below graph below, so would payers – upon introduction of the email service, the percentage of patients with an A1c <7.5% went through the roof, though it soon came back down considerably. Perhaps it drove early engagement, which tailed off once the novelty wore off.

• Quotable Quotes

  • “If you have $1,000 to spend, you better invest in diabetes care, because you get far more than on best day in stock market. We are a reverse pension fund, you pay something now and save money later.”

  • “With a hospital, you talk with payers about budgets. With me, you talk about patients.”

  • “I have to deal with seven insurance companies every year. I show them data every year. But I never discuss prices until at the very end…they agree quickly at the end, because the Diabeter model is cheaper. They ask us to do more because it’s to their advantage. Total cost of patient comes in our bundle, if save on cost, they hand over the money.”

Digital Health Poster Highlights

Title	Important details
Use of Mobile-Based Technologies Improve Diabetes Self-Management Behavior	Authors from Lilly’s Cambridge Innovation Center and Joslin Diabetes Clinic (including Dr. Elena Toschi) 30 CGM-naïve T1D subjects were given FreeStyle Libre plus real-time contextual prompts from an app (following a glycemic excursion, the app prompted users to enter the suspected cause – food? Insulin?) and web-based nutrition education. At 14 weeks, mean A1c had dropped 0.45% points (baseline: 8.0%). No change in time-in-ranges was provided, though the data is presumably on hand since FreeStyle Libre was used. Notably, changes in insulin doses did not account for the improvement; further investigation is underway to identify “meaningful changes” in disease management behavior. We wonder how significant respective contributions of nutrition education and contextual prompts were. Also, could A1c simply have improved because patients were enrolled in a trial? Various control groups would be nice to see in the future. This poster is interesting in two respects: (i) It may show that simply prompting someone to reflect on the cause of an excursion (in a less-chastising and panic-causing manner than an alarm) could improve self-management behaviors; and (ii) it gives a glance into some of the patient decision support work ongoing at Lilly’s Cambridge Innovation Center.
Use of Gocap to Evaluate Appropriateness of Bolus Insulin Dosing to Achieve Target Glucose Levels in Patients on Basal Bolus Regimen	The second Common Sensing-Joslin Diabetes Center poster (first one at ADA 2017); Common Sensing’s Bluetooth-enabled Gocap insulin pen cap records and communicates injection data Gocap was used to evaluate the impact of bolus dosing on three-hour post-injection blood glucose in 24 MDI patients; 12 young (18-35 years-old), 12 older (>65 years-old) “Out of 1,343 doses, 701 doses (52%) resulted in glucose levels above target, 521 doses (39%) resulted in glucose levels at target, and 121 doses (9%) resulted in glucose levels below target.” Injection history gives a whole new view into the black box of glucose response, frequently making issues related to insulin dose magnitude and timing obvious – they are currently invisible. This study serves as another reminder of how important smart pens/caps are going to be for the field, and for HCP/patient decision support.
How Do We Adjust Insulin Dosing for Patients with Type 1 Diabetes Using Sensor Augmented Pump? – Variations Among Countries and Physicians	The DreaMed Expert Physician Study: 25 physicians from different centers (Europe, Israel, South America) were asked to adjust insulin dosing based on uploaded CareLink Pro data from 15 patients, including CGM, BGM and insulin pump data over three weeks. Advice for insulin dosing adjustments varied greatly across centers and even within a center! Full agreement between physicians on the direction of insulin adjustments (basal, CR and CF plans) were 41%, 45% and 45%. The agreement was almost identical between the physicians and the Advisor Pro: 42%, 48% and 44%. This is a major win for DreaMed’s Advisor Pro clinical decision support software, which is now-CE-marked. As noted in our day #1 report, it is also currently under FDA review.
Beyond Glucose: Healthcare Professional (HCP) Perceptions of the Value of Capturing Insulin Dose Data to Support Diabetes Management. A Targeted Literature Review	A meta-analysis (of 76 articles) spearheaded by BD suggesting that HCPs perceive value in capturing insulin dose, though clinical guidelines don’t yet recommend it. Neither of these findings are surprising: Insulin dose history is anecdotally and scientifically valuable in a provider’s toolkit, but there is not enough experience – or devices! – to have established best practices to include in guidelines.
GoCARB Accuracy on Carbohydrate Estimation Versus Visual Estimations By Dietitians	AI meal recognition/quantification software performed similarly to dietitians in terms of error magnitude. There are many such systems in development or already launched (LoseIt, CalorieMama), which could very well enhance (and facilitate) meal-time bolusing. Those these aren’t perfectly accurate in all circumstances, they are likely as good or better than people guesstimating carbs randomly. We are big believers in photo-logging of meals, paired with pre-post glucose data, especially as computer vision improves to count carbs more quantitatively. Still, we also see tremendous value in the more basic Meal-Memory-like feature – where users can tag CGM traces with meal photos to see the direct glycemic impact of certain foods.
Blood Glucose Improves Among People 'At Risk' Using One Drop | Premium or Plus On iPhone And Apple Watch	Uncontrolled, retrospective analysis of 12-week glycemic changes in people deemed “at-risk” using the One Drop app (on iPhone or Apple Watch), Chrome Bluetooth-enabled BGM, and 24/7 CDE Coach Comparing week 12 to week 1, average blood glucose dropped from 226 mg/dl to 179 mg/dl (-48 mg/dl; eA1c -1.6%); percentage of high blood glucose readings was 26% lower and in-range blood glucose readings 25% higher.

5. Insulin Therapy and Diabetes Drugs

Sanofi’s Real-World LIGHTNING Study: Toujeo Significantly Reduces Severe Hypoglycemia by >60% vs. Lantus and Levemir, On Par with Tresiba

Results from Sanofi’s real-world LIGHTNING study were presented on a poster and during a corporate symposium at ATTD. The company’s next-gen basal insulin Toujeo reduced severe hypoglycemia risk by more than 60% vs. Lantus (p=0.009) and vs. Levemir (p=0.002), while severe hypo rates were similar with Toujeo vs. Novo Nordisk’s next-gen Tresiba (p=0.370). LIGHTNING analyzed electronic medical records of 10,458 patients with type 2 diabetes who switched from one basal insulin to another. After propensity score matching, the mean estimated event rates of severe hypoglycemia per 100 patient-years were 3.6 for Toujeo vs. 9.7 for Lantus (p=0.009), 3.6 for Toujeo vs. 15.1 for Levemir (p=0.002), and 3.4 for Toujeo vs. 5.3 for Tresiba (p=0.370). A1c-lowering was similar across all three comparisons, ranging from -0.50% to -0.89% (baseline 9.1%-9.2%), indicating that reductions in hypoglycemia did not occur at the expense of greater hyperglycemia. Our key takeaway from this data is that the hypoglycemia benefit associated with next-generation basal insulins (both Toujeo and Tresiba) translates from RCTs to the real world – this is exciting for patients, and should hopefully be compelling to payers as well. During Sanofi’s accompanying symposium on basal insulin, UCSD’s Dr. Jeremy Pettus commented that real-world studies add confidence to the scientific vigor of RCTs, demonstrating that clinically-meaningful outcomes are maintained outside the structure of a randomized controlled trial. Dr. Pettus expects to be seeing more of these studies, and indeed, Sanofi has launched a robust real-world evidence campaign around Toujeo, which we learned about in-depth at EASD 2017. The company issued a press release at the beginning of ATTD to call attention to this real-world read out.

• LIGHTNING hints that Toujeo has real-world impact comparable to Tresiba, although head-to-head RCTs reporting later this year will shed additional light on the relative advantages/disadvantages of the two advanced basals. From a baseline 9.2%, A1c declined by a mean 0.8% for people switching to Toujeo vs. 0.89% for people switching to Tresiba (p=0.591), and hypoglycemia frequency was similar at 3.4 events/100 patient-years vs. 5.3 events/100 patient-years, respectively (p=0.370). Sanofi’s BRIGHT study compares Toujeo vs. Tresiba head-to-head in a randomized controlled setting, and thus far has shown a similar proportion of patients (~50%) reaching A1c goal <7% after 24 weeks (baseline A1c 8.6%-8.7%). The hypoglycemia findings from BRIGHT aren’t yet available, but we’ll be looking for these at ADA 2018. Novo Nordisk has its own head-to-head RCT ongoing with hypoglycemia as the primary endpoint, and this trial is expected to complete in October 2018. Of note, Tresiba commercially outperformed Toujeo by a fair margin in 2017 (Novo Nordisk’s product sales growing 80% YOY to $1.1 billion, Tresiba’s product sales rising 26% YOY to $926 million). We’ve heard some thought leaders endorse Tresiba as a flatter basal insulin vs. Toujeo overall, with greater flexibility around missed doses, based on their clinical practice. Regardless, we want to emphasize that both these next-gen products offer substantial advantages to patients above and beyond what was available before, as evidenced by Toujeo’s highly-significant hypoglycemia benefit vs. Lantus and Levemir in this real-world trial.

• As with any real-world study, there are some limitations to LIGHTNING, most notably that previous basal dose and reasons for switching weren’t available from the Humedica database. Data was gathered on patients between April 1, 2015 to December 31, 2016 from >50 healthcare systems. LIGHTNING defined severe hypoglycemia as inpatient or emergency room visits due to low blood glucose (≤70 mg/dl or coded ICD-9 or 10). These results corroborate DELIVER-D findings, from a smaller (n=1,620) real-world study that looked at patients switching from Lantus specifically to Toujeo or Tresiba.

Novo Nordisk’s Fiasp Shows Postprandial Efficacy vs. NovoLog in 472 Pump Users with Type 1; Equivalent A1c-Lowering and Hypoglycemia in 16-Week Data from Onset 5

Dr. David Klonoff presented results from Novo Nordisk’s Onset 5 study of Fiasp (faster-acting insulin aspart) vs. NovoLog (insulin aspart) in pump users. After a four-week run-in period, adults with type 1 diabetes on a pump (n=472) were randomized to Fiasp or to NovoLog for 16 weeks. A1c-lowering was non-inferior for Fiasp compared to NovoLog, dropping from a baseline 7.5% to 7.44% with the next-gen and from the same baseline to 7.35% with the first-gen (p<0.001 for non-inferiority). Dr. Klonoff reported an estimated treatment difference of 0.09% for A1c (95% CI: 0.01%-0.17%). Fiasp did show significant benefit over NovoLog on a one-hour post-meal test, with an estimated treatment difference of 16.39 mg/dl for postprandial increment at week 16 (95% CI: -25.73 mg/dl to -7.06 mg/dl, p=0.001). The improvement in postprandial glucose with Fiasp vs. NovoLog at one hour post-meal was supported by significantly lower post-meal plasma glucose levels at 30 and 120 minutes, and by 0-1 hour and 0-2 hour ISF glucose increments as measured by CGM and by postprandial SMBG testing. Hypoglycemia data was resoundingly neutral across groups, with an estimated treatment ratio of 1.00 (95% CI: 0.85-1.16). Dr. Klonoff explained how this figure encompassed severe hypoglycemia as well as blood glucose-confirmed symptomatic hypoglycemia. Looking only at severe glucose-confirmed events, hypoglycemia appears to be more frequent with Fiasp vs. NovoLog (21 vs. 7 episodes), but excluding three participants who all experienced severe hypoglycemia during the run-in (and who all happened to be randomized to the faster-acting aspart arm), these values fell to 11 vs. 7 events. Dr. Klonoff reviewed nearly equivalent adverse event rates for Fiasp-treated and NovoLog-treated patients in the study. He concluded that Fiasp is safe and effective for CSII, an important finding, as Novo Nordisk’s advanced prandial insulin is currently approved for use in pumps in Europe but not in the US or Canada. Fiasp was just launched in US pharmacies earlier this month, at parity pricing to NovoLog, which is a huge win for patients.

One-Year Onset 1 Results Confirm Fiasp’s Safety/Efficacy in Type 1 Patients on MDI; Modest A1c Benefit + Enhanced Postprandial Control One Hour Post-Meal

In the same session of orals, Dr. Bruce Bode continued the focus on faster-acting Fiasp with one-year data from Onset 1 (n=1,143 type 1 patients on MDI). These trial extension findings largely paralleled the 26-week results, showing modest but statistically significant A1c improvement and superior performance on a one-hour post-meal test with Fiasp vs. NovoLog. After 52 weeks, A1c declined from a baseline 7.6% to 7.5% for Fiasp-treated patients, staying at 7.6% for patients on NovoLog (estimated treatment difference -0.1%, p=0.042). A1c did climb slightly from the 26-week point, when Fiasp patients were down to a mean 7.3% and NovoLog patients were down to a mean 7.4%, for an estimated treatment difference of -0.15% (p=0.0003). Fiasp demonstrated a 16.5 mg/dl benefit on postprandial glucose control one hour following a meal (p=0.0002), and showed a nonsignificant 7.6 mg/dl treatment difference on a two-hour post-meal test after 52 weeks. Dr. Bode also pointed to a 4.14 mg/dl benefit with Fiasp vs. NovoLog on 9-point SMPG at the one year mark (p=0.047). He shared detailed slides on hypoglycemia and treatment-related adverse events, neither of which differed significantly between groups over the full year. Severe hypoglycemia occurred in 37 of 386 Fiasp patients (9.6%) and in 46 of 380 NovoLog patients (12.1%), which seems like a numerical discrepancy, though Dr. Bode emphasized that “severe hypoglycemia was not an issue” in Onset 1. Blood-glucose confirmed hypoglycemia occurred in 361 (93.5%) of Fiasp patients vs. 369 (97.1%) of NovoLog patients. All other safety data was also well-balanced between the two mealtime insulins, and according to Dr. Bode, showing convincing, longer-term safety of Fiasp was the main reason for the Onset 1 trial extension. These findings are consistent with the overall Onset program, and could provide reassurance to patients/HCPs looking to start on Fiasp for boluses. The product was launched earlier this month in the US, where it’s only indicated for MDI (and not pumps – see above for more on this). We do think highlighting safety will be of help in promoting the new drug and generating early uptake, especially since Fiasp is priced on par to NovoLog, so people could be motivated to make the switch for smaller postprandial excursions and more mealtime flexibility. Although some consider the glycemic benefits to be “marginal” rather than truly significant compared to earlier prandial insulin options, we maintain that current rapid-acting mealtime insulin is just not good enough for many patients, so we’ll take any improvement in postprandial excursions, A1c, or even the peace of mind that comes with a shorter tail, less residual insulin in the bloodstream, and possibly less fear of hypoglycemia.

• During Q&A, Dr. Bode did address the issue of why A1c doesn’t decline as substantially with Fiasp as might be expected given consistent improvements in postprandial control. He hypothesized that patients on the advanced insulin engage in protective eating to avoid going to bed low/nocturnal hypoglycemia, which leads to greater glucose variability overnight. Dr. Bode underscored the relatively long mean duration of diabetes in Onset 1, between 19-21 years, and alluded to the difficulty of changing habits. “If you’re used to going to bed at 150 mg/dl, you want to keep doing that, even if your post-dinner blood sugar is down to 100 mg/dl,” he explained. “You can’t change people’s behavior after 20 years.” We’re not sure that’s entirely true, and we’d be interested in behavioral interventions that can support patients making the switch to Fiasp or another faster-acting insulin, but we also appreciated Dr. Bode’s suggestion that putting faster-acting aspart in pumps or in hybrid closed loop may be the ideal application. Again, we direct you to Onset 5 results on Fiasp in pump users, presented in the same session by Dr. David Klonoff (see above).

Questions and Answers

Dr. Bruce Bode (Atlanta Diabetes Association, GA): I’ll start with a question to myself. Why do you think there was an A1c difference in Onset 5, and the post-meal was always better in Onset 1, but there was no significant drop in A1c?

A: We’ve been using Fiasp in pumps, and one thing my patients are feeding back to me is the greater variability they’re feeling overnight. I wonder if that’s at play.

Dr. David Klonoff (Mills-Peninsula Health Services, San Mateo, CA): That’s a good question, Bruce. What we saw was that glucose levels in faster-acting aspart people rose quite a bit after dinner, and just stayed higher all-night long. So, people taking Fiasp in a pump need to be carefully treated, and they may need a higher basal rate over time than they’re used to.

Q: Were you surprised there was no difference in A1c? And how would you design a study to show a difference?

Dr. Bode: The only problem with increasing basal overnight is you increase the risk for hypoglycemia. I think it’s protective eating, is what it is. If you’re used to going to bed at 150 mg/dl, you want to keep doing that, even if your post-dinner blood sugar is down to 100 mg/dl. So, these patients might eat, and that would then cause variability overnight. Note that we’ve seen this in every single trial of rapid-acting insulin.

Q: So, how do you design a study to prevent this nighttime variability?

Dr. Bode: You put Fiasp in a hybrid closed loop. You can’t change people’s behavior after 20 years. If you’re new to diabetes, maybe.

Comment: When you test new insulins, you need new tools. So, maybe it’s not hybrid closed loop, but you at least need CGM with Fiasp. Patients don’t feel their glucose all the time.

Dr. Bode: Yes, and there’s a sub-analysis of Onset 5 with CGM.

Dr. Klonoff: Someone else did that analysis. That’s where the pattern was higher overnight; that’s where the A1c was lost. You had better control after meals, and if you lost it somewhere, it was overnight.

Dr. Robert Ritzel Illuminates New Data from BRIGHT (Head-to-Head RCT of Toujeo vs. Tresiba), But More Questions Remain; Full Results Presentation Expected at ADA 2018

Munich’s Dr. Robert Ritzel shared more granularity on BRIGHT study results comparing Sanofi’s Toujeo (insulin glargine U300) vs. Novo Nordisk’s Tresiba (insulin degludec), although we’ll likely have to wait until ADA 2018 for hypoglycemia findings. This Sanofi-sponsored open-label trial (n=929 adults with type 2) is the first head-to-head RCT of next-generation basal insulins, so the results could certainly have commercial impact. Sanofi issued a topline release in December 2017, and also discussed the very preliminary data during a corporate symposium at IDF. Dr. Ritzel announced that ~50% of participants in each arm achieved target A1c <7% after 24 weeks (mean baseline A1c was 8.7% in the Toujeo group, 8.6% in the Tresiba group). He showed balanced treatment-emergent adverse events: 44% of Toujeo-treated patients (202 of 462 individuals) and 48% of Tresiba-treated patients (221 of 462 individuals) experienced any treatment-related AE. Serious adverse events occurred in 5% and 4% of the Toujeo and Tresiba groups, respectively, while 4% and 7% of each group discontinued from BRIGHT early. We’re eager for even more specifics on this data: What was the average A1c decline with Toujeo and Tresiba? Sanofi’s topline release reported that Toujeo met its primary endpoint of non-inferiority vs. Tresiba for A1c reduction over 24 weeks, but no mean values of p-values were disclosed. How did treatment satisfaction compare across the two advanced basals? We were pleased to see in the topline release that PROs, as measured by the Diabetes Treatment Satisfaction Questionnaire (DTSQ), are a secondary endpoint in BRIGHT. And of course, as one audience member brought up, we’re very much looking forward to hypoglycemia results. In fact, hypoglycemia risk reduction could be one of the most important advantages to next-gen basals; Tresiba has already shown significant risk reduction vs. Lantus in SWITCH and DEVOTE, and is awaiting an FDA decision on a possible label claim reflecting this benefit. Even more than seeing how Toujeo stacks up to Tresiba on hypoglycemia frequency, we’d love to gain a better quantitative sense of how Toujeo offers hypo benefit over earlier basal insulin options. While these head-to-head results will be intriguing, our view is that both these products are strides above what came before, offering meaningful improvements to patient care. We’d love to see greater commercial uptake of Toujeo and Tresiba alike – sales are strong, but could be so much stronger (the next-gen basal insulin class grew 57% YOY to $2.1 billion in 2017, and accounted for 22% of the $2.5 billion basal insulin market in 4Q17). Sanofi management announced on the company’s 4Q17 earnings call that full BRIGHT results will be presented at ADA 2018 in Orlando, while Novo Nordisk has launched its own head-to-head RCT, with data anticipated in 4Q18. Notably, the primary endpoint of the Novo Nordisk-sponsored RCT is hypoglycemia rather than A1c decline. We take this as another sign that the companies believe in the hypo benefits their advanced products offer.

Questions and Answers

Q: What was the hypo data?

A: That is going to be presented at another conference. The data was not yet available when we submitted for this conference.

Dr. Bode on Lilly’s Ultra-Rapid Insulin Lispro – New Phase 3 PRONTO-Pump Study to Begin Next Week; Describes Speed as More Physiologic; Emphasizes Positive Patient Experiences on Afrezza

Dr. Bruce Bode highlighted promising ultra-rapid-acting insulin candidates in the pipeline, including Lilly’s phase 3 ultra-rapid lispro. He shared that a new phase 3 study in people with type 1 on an insulin pump (n=48) will begin in the next few days. According to ClinicalTrials.gov, PRONTO-Pump is expected to complete in September of this year. Interestingly, the primary endpoint is rate of infusion set failures with ultra-rapid insulin lispro vs. Lilly’s Humalog (insulin lispro); secondary endpoints include percent of participants with ≥1 infusion set failure, rate of premature infusion set changes, and time interval until infusion set change. This suggests to us that Lilly is investing deliberately in developing its ultra-rapid candidate for pump use, which is fitting, since speed of bolus insulin has significant implications for pumps as well as closed loop – Dr. Bode spoke to these applications of faster-acting insulins, both in this morning plenary and in an afternoon oral presentation of Onset 1 (see above). PRONTO-Pump joins PRONTO-T1D and PRONTO-T2D in the phase 3 program for ultra-rapid lispro; these pivotal studies in type 1 and type 2 diabetes are expected to complete in September and February 2019, respectively. Dr. Bode additionally discussed Adocia’s BioChaperone Lispro and Diasome’s HDV insulin lispro; both candidates are in phase 2, though BC Lispro is phase 3-ready (Adocia continues to seek a new development partner following termination of the Lilly partnership in January 2017). As for ultra-rapid-acting insulins already available to patients, Dr. Bode touted the benefits of Novo Nordisk’s Fiasp and MannKind’s inhalable Afrezza. He underscored that the philosophy behind these products is to more closely mimic the kinetics of endogenous insulin secretion, which has both a fast onset and offset of action (resulting in tighter postprandial glucose control and lower hypoglycemia risk). We do see mealtime insulin as one of the areas of diabetes care most in need of improvement, which is why we’re excited by the prospect of Fiasp (just launched in the US) and Afrezza; on Afrezza, uptake has been sluggish thus far, but the product received a label update from FDA last October to reflect an ultra-fast PK/PD profile vs. Humalog. We’d love to see these more physiological options in even more patient hands, though we note that access remains a barrier.

Questions and Answers

Q: On Afrezza, what’s the efficacy of using it post-meal or splitting the dose? How often do we have to give a second dose after the meal?

A: If you look at the PK/PD profile of any of these insulins, it’ll tell you what will happen. If you’re having a high-fat meal that increases insulin resistance, you need to check glucose two hours after you eat and maybe take a correction. More than half of patients will eat a high-fat meal, so at least half will need a correction dose. If you’re eating simple sugar, you’re fine with one inhalation. If you’re eating steak and potatoes and a dessert, you’re going to need a second inhalation. Dr. Garg said early on to put this in the protocol, and we did put it in AFFINITY 1, but only 20% ever used it. In STAT, we encouraged everyone to always check blood sugar and if you’re >160 mg/dl, take a second inhalation.

Q: Is there any concern with not having more flexibility of dosing with Afrezza?

A: Patients love this product. The masses aren’t on it, because many endos think it causes lung cancer, but it has no action in the lung – it’s just a way to get through. Most people need to use a sensor, whether it’s flash (Abbott) or Dexcom, to decide when to take an extra inhalation.

Dr. Garg Optimistic for Tresiba Hypo Label Update, Regrets Lilly’s Discontinuation of PEGylated Insulin Peglispro

In a review of concentrated insulin products on the market, Dr. Satish Garg expressed optimism that FDA could approve a hypoglycemia claim for Novo Nordisk’s Tresiba (insulin degludec), and he lamented Lilly’s discontinuation of insulin peglispro (in December 2015). According to Dr. Garg, FDA was planning an Advisory Committee to discuss the requested label change for Tresiba, but the meeting was canceled. Does this imply that FDA is leaning toward an approval? Dr. Garg shared a positive outlook (we’re keeping our fingers crossed). Novo Nordisk management expects an FDA decision by end of 1Q18. To be sure, there’s no precedent at FDA to reflect hypoglycemia benefit on an insulin label – Dr. Garg explained that all labels come with hypoglycemia warnings, and none compare one insulin to another – so this claim for Tresiba would be revolutionary. In 3Q17, EMA approved a similar Tresiba label update, based on positive data from SWITCH 1, SWITCH 2, and DEVOTE (40% risk reduction for severe hypoglycemia and 53% risk reduction for severe hypo overnight vs. standard of care Lantus, p<0.001 for both comparisons). To further illustrate the value of insulin degludec, Dr. Garg presented a case study of a 44-year-old man switching from Sanofi’s Lantus to Tresiba: The patient’s A1c dropped from 7.8% to 6.5%, his total daily insulin dose dropped 18%, and his CGM tracings showed remarkably less glucose variability. Dr. Garg alluded to the importance of time-in-range for patient quality of life and treatment satisfaction, and in this regard, Tresiba is definitely superior to earlier basal insulin options. He touched upon Sanofi’s next-gen basal Toujeo (insulin glargine U300) as well, which demonstrated a significant reduction in nocturnal hypoglycemia vs. Lantus in pivotal studies. Sanofi management recently suggested that Toujeo could show a similar hypoglycemia benefit to Tresiba, meaning both next-gen basals are a leap above first-gen options like Lantus and Novo Nordisk’s Levemir (insulin detemir). We certainly agree with this latter point, and the former could be determined by head-to-head studies of Tresiba vs. Toujeo. The Sanofi-sponsored BRIGHT trial (an RCT) will report full results at ADA 2018, while Novo Nordisk’s head-to-head study is expected to complete and read out in 4Q18. Dr. Garg also pointed out the important consideration that Toujeo increases an individual’s insulin dose by a mean ~20% vs. Lantus, which is included on the product’s US label.

• In Dr. Garg’s view, “insulin peglispro was the best concentrated insulin” in development, prior to discontinuation in early December 2015. Lilly made this decision based on liver toxicity seen in phase 3, or what Dr. Garg described as issues related to liver enzyme levels and liver fat. These safety concerns aside, he touted the PEGylated insulin candidate for its “hepatic specificity,” which more closely resembles endogenous insulin action. He highlighted the continued weight loss seen with Lilly’s peglispro, which is certainly meaningful, given that most insulins are associated with weight gain – eliminating this side effect could improve adherence, treatment satisfaction, and overall outcomes for people with diabetes. Dr. Garg shared hope that “someone else will take up some other way of doing PEGylation” for the promise of an insulin therapy with fewer side-effects and durable efficacy (peglispro showed significant A1c reductions and a decline in fasting plasma glucose over 78 weeks, in addition to being the only insulin that lowered body weight). Rezolute (formerly AntriaBio) has a PEGylated basal insulin candidate in phase 1, with a study currently underway at Prosciento in San Diego.

• Dr. Garg concisely outlined why we need concentrated insulin: For one, the field is still lacking a basal or prandial insulin that mimics healthy beta cells. Rising BMI in the population introduces a need for higher insulin doses at lower volume, since increasing volume alone would lead to unpredictable absorption, local discomfort, medication complexity, poor glucose control, and heightened hypoglycemia risk. Moreover, Dr. Garg has calculated that there are at least ~100 million people in the world requiring insulin therapy (~30 million type 1s, ~80-100 million type 2s, including those who are antibody-positive), and fewer than one million of them (1%-2%) are on a pump. “Let’s not forget about the 99%,” he said, referring to the majority of diabetes patients who aren’t on an insulin pump due to access issues, knowledge gaps, and/or implementation challenges. The size and scope of this population further underscores the unmet need for better concentrated insulins.

• Dr. Garg concluded his talk with a shoutout to Dr. Irl Hirsch’s annual rants in Diabetes Technology & Therapeutics (read the 2018 edition here), which highlight cost as a persistent issue. In any discussion of insulin, and especially insulin innovation, we can’t ignore the rising cost of this essential medicine, he emphasized.

Dr. Sherr on Benefits to Nasal Glucagon – Speed, Accuracy, Ease of Use; Lilly Plans to File in US/Europe in 2018, Expected Approvals by 2019; Company Working Hard on Manufacturing for Hopeful Swift Launch

As Lilly approaches regulatory filing of nasal glucagon (planned for 2018), Yale’s Dr. Jennifer Sherr provided a timely and comprehensive review of RCTs and real-world trials of the candidate completed to-date. Pivotal studies in adults and pediatrics showed a 3 mg dose to be safe and effective across the entire age spectrum for type 1 diabetes. Since these phase 3 trials relied on HCPs to administer the nasal glucagon, Dr. Sherr also summarized findings from a simulated usability study published in 2017. Participants included primary caregivers of patients with diabetes (n=16) as well as acquaintances who weren’t trained (n=15). In a mock scenario, participants encountered a mannequin representing someone with type 1 or type 2 diabetes unconscious due to severe hypoglycemia; a backpack with glucagon was nearby on the floor, and distracting sounds/stressors were deployed to model the urgency and stress of a real-world emergency. The results were impressive: 94% of instructed caregivers and 93% of untrained acquaintances successfully delivered a full dose of nasal glucagon to the mannequin, while only 13% of caregivers and no acquaintances delivered a full dose of intramuscular glucagon (p<0.001 for both comparisons). Among primary caregivers, the mean time to administer glucagon was only 16 seconds for nasal vs. 113 seconds for intramuscular; these values were 26 seconds vs. 144 seconds for untrained acquaintances. This parallels real-world data presented by Dr. Elizabeth Seaquist at ADA 2017 (n=129), showing how 70% of caregivers were able to administer nasal glucagon in <30 seconds, while 98% were able to do so in less than two minutes. Speed is of the essence for rescue therapy, and Dr. Sherr spoke to the challenges of current glucagon reconstitution kits, which require a lengthy mixing process prone to error in a high-stress hypoglycemia situation. In a small study conducted at a diabetes camp, 70% of parents experienced difficulty with a glucagon reconstitution kit, five of them injected only air/diluent (and not glucagon), and the average time to administration was 2.5 minutes (150 seconds). Dr. Sherr also presented real-world data on nasal glucagon for pediatric patients, showing that 94% of caregivers found the product easy-to-use, and 94% were relatively satisfied, satisfied, or very satisfied after a hypoglycemia episode. Moreover, in all severe hypoglycemia events (33 for 14 participants), the individual returned to normal glycemic status within 30 minutes, which was a similar finding to the real-world study in adults. The last trial she discussed, one published recently in Diabetes, Obesity, and Metabolism, investigated the effects of the common cold or nasal congestion on the efficacy of Lilly’s next-gen glucagon in healthy volunteers. There were no significant differences in PK/PD performance or safety, and Dr. Sherr concluded that nasal glucagon could be used effectively even if a patient is congested.

Questions and Answers

Q: Does the nasal glucagon product need to be refrigerated?

A: No.

Q: What’s the shelf life?

A: I’ll defer to my colleagues at Lilly on that, but my understanding is that it’s up to a two-year shelf life. [Editor’s note: In a call with Lilly management prior to ADA 2017, we learned that shelf life for nasal glucagon will likely be comparable to that of current glucagon reconstitution kits, 1.5-3 years depending on refrigeration.]

Q: When will it be available?

A: Nasal glucagon is still in development worldwide, but there are plans to submit packages both in the US and in Europe in 2018.

Q: Is it going to be more expensive than current glucagon? Do you have any sense about the production difficulties?

A: I can’t speak to cost, but what I can say is that Lilly’s working very hard to make sure manufacturing is all set, so that when the product is approved, it will be ready for distribution right away.

Dr. Irl Hirsch Rants: How Do Positive CVOTs Figure into Cost-Effectiveness Calculations; Are Insulin Analogues Not Cost-Effective for T2D?

For the second consecutive ATTD, UW’s Dr. Irl Hirsch delivered a fascinating talk on cost economics, this time exploring the (complex) impact of positive CVOTs on the calculus of cost-effectiveness research. Before certain anti-hyperglycemic drugs were shown to be cardioprotective, cost-effectiveness was easier from the payer point of view: Cost per 1% A1c drop would be a logical calculation, and Dr. Hirsch found it to clearly point to generic drugs (metformin, SU glyburide, and TZD pioglitazone; ~$3-$8/1% A1c drop) as the obvious choice compared to DPP-4 sitagliptin ($693/1% A1c drop), SGLT-2 canagliflozin ($493/1% A1c drop), and GLP-1 liraglutide ($736/1% A1c drop). This analysis largely excludes acute outcomes such as DKA and severe hypoglycemia, but shows a vast gap that, according to the DCCT and basic economics, points to the generics. But, as Dr. Hirsch pointed out, CV disease and PVD (peripheral vascular disease) contributed 57% of diabetes healthcare costs in 2012; this on top of positive CVOT findings requires a recalibration on both the payer’s and the provider’s parts. Dr. Hirsch proceeded to review cost-effectiveness analyses of empagliflozin (Lilly/BI’s Jardiance) in Turkey, Italy, Greece, and the UK (the official EMPA-REG cost analysis). In all four, researchers deemed empagliflozin cost-effective, with assessments ranging from “reasonable and bearable for payers” in Greece to “extremely cost-effective” (Dr. Hirsch’s words) in Turkey. ICER (incremental cost-effectiveness ratio; a measure of the difference in cost of two approaches divided by difference in their effects) ranged from $2,183/QALY (quality-adjusted life-year) in Turkey to 4,811 euros/QALY in Italy, where the rule of thumb threshold for coverage is 30,000-50,000 euros/QALY. Notably absent from this set of analyses (“the elephant in the room”) was the US…how would the models fare there, where both healthcare as a percentage of GDP and per-patient costs are shooting up, wondered Dr. Hirsch. The cost half of the equation was a definite cause for alarm: Dr. Hirsch’s research showed that whereas one month of empagliflozin costs $54, $119, and 55 euros in the UK, Canada, and Spain, respectively, the retail cost per month in the US is closer to between $449 (GoodRx.com) and $516 (average wholesale price). Barring the scenario in which empagliflozin is significantly more effective in the US, the cost-effectiveness likely takes up to a 10x hit in the US (still a good deal for payers, per the rule of thumb). We too would very much like to see this analysis in the US, and Dr. Hirsch said that an abstract for empagliflozin cost-effectiveness analysis has actually been submitted! We loved this talk because it reminded us just how complex health economics are, barely touching the tip of the iceberg of complexity; Dr. Hirsch pointed out that analyses must also take into account acute savings and costs from glucose lowering (acute hyperglycemia/hypoglycemia), chronic savings and costs from glucose lowering, additional time to work instead of disability before death, and the fact that the costs of everything from complications to drugs are highly dependent on the country. We’d add to that list that (i) cost-effectiveness is a great population-level metric, but there are certainly some individuals for whom a certain treatment would have a sky-high ICER, and others for whom ICER would be $0.50/QALY and (ii) ICER is not the only metric of interest – if a patient doesn’t like a certain drug because of its mode of administration, side-effect profile, or something else, she won’t take it and receive the projected benefit. The shift toward a value-based healthcare system relies on not only determining which drugs are “most” cost-effective across a whole lifespan and population, but also on curating the right treatments for the right person at the right time, and on a continually-learning ecosystem – we see registries and nations with unified EHRs as crucial pieces in solving this puzzle.

• BD’s Dr. Larry Hirsch astutely asked if the fact that most CVOTs have been conducted in people with existing CV disease, thus far, exaggerates the cost-effectiveness of cardioprotective drugs. In other words, how would the health economics play out in the general population? The data to answer this question doesn’t yet exist, which is why Dr. Hirsch framed the talk at the outset by showing two patients – one without CV disease and another with cardiomyopathy – and asking what would be the most cost-effective medications for both. It’s too early to say at this point whether cardioprotective drugs should be administered in people without established CV disease. Without cost as a factor, the answer should be a resounding yes, but cost is obviously a (if not the) major dictator of the medications and tools available to patients today. Notably, SGLT-2s may be the first class to show cost-effectiveness in a broader type 2 population, including those without prior stroke/MI – there have been hints in CVOT data that these agents may confer heart failure benefit in a primary prevention population. A post-hoc of CANVAS, for example, found significant risk reduction for heart failure hospitalization in both cohorts, people with and without baseline CV disease. AZ’s DECLARE CVOT for dapagliflozin includes heart failure in a co-primary endpoint and also enrolls a larger primary prevention cohort (~50% vs. 33% in CANVAS and 0% in EMPA-REG), so this could also move the needle on SGLT-2s as a more cost-effective diabetes therapy (DECLARE results are expected in 2H18).

• On a discouraging note, a systematic review published last year in PharmacoEconomics found that the cost-effectiveness of insulin analogs in type 1s is $27,051/QALY gained, but this number was $425,913/QALY gained when it came to type 2s. In Dr. Hirsch’s words, insulin analogs in type 2 diabetes are “about as cost-effective as a pediatric heart transplant. I thought that was a joke until I looked it up.” The authors concluded that “current evidence suggests that insulin analogs are cost-effective in T1D; however, the evidence for their use in T2D is not convincing.” Dr. Hirsch said he’ll still use insulin analogs in his type 2 patients (which we were happy to hear since we would advocate for more, not fewer people to get on insulin); this story is no more than a cautionary tale about the importance of taking cost-effectiveness analyses with a grain of salt.

• Last year, Dr. Hirsch’s talk revolved around the economic benefit of intermittent CGM ($8,893/QALY). This cost seems to be significantly higher than the cost-effectiveness of empagliflozin, but recall that ICER depends critically on the comparator approach/treatment, so they are not directly comparable. Still, $8,893 is a great deal for a payer, according to most economists, said Dr. Hirsch.

Fiasp in Pumps: Dr. Eric Zijlstra Indicates that Fiasp May Be Even Faster Via CSII; Dr. David Russell-Jones Reviews Evidence for Fiasp in Pumps

At a Novo Nordisk corporate symposium, Profil’s Dr. Eric Zijlstra presented data indicating that Fiasp might actually perform better in a pump than via injection, based on available data. Compared to NovoLog, pumping Fiasp results in onset of exposure 12 minutes earlier, compared to 10 minutes earlier for injection, and insulin exposure is three-fold higher for Fiasp vs. NovoLog with pump compared to two-fold higher with injection. Importantly, this trend holds true for offset of action as well. In pumps, Fiasp’s mean offset time is 35 minutes earlier than NovoLog’s, and it’s only 12 minutes earlier with injection. While these are striking results, Dr. Zijlstra emphasized that they are indirect comparisons from different studies (total n=48 for pump and n=218 for injection), and shouldn’t be used to draw hard conclusions. That said, we certainly think further investigation is warranted. To be sure, Fiasp is an improvement over other rapid-acting insulin analogs regardless of how it’s taken, offering more flexibility/less uncertainty around meals. This could correlate to less fear of hypoglycemia, which gets in the way of optimal glucose control for so many patients with diabetes (79% of type 1 patients and 58% of type 2 patients lower their insulin doses following a severe hypoglycemia episode). While Fiasp is approved for pump use in the EU, it’s currently only available in pens or vials in the US/Canada. But we’ll be interested to see if this changes, especially if the next-gen, faster-acting insulin continues to show even more impressive efficacy in a pump setting. Dr. Zijlstra emphasized that an ideal insulin for pumps would have even faster onset (even Fiasp can’t compete with endogenous insulin secretion in speed) and offset (to avoid postprandial hypoglycemia), with a particular eye toward application in a fully-automated closed loop – many believe subcutaneous insulin delivery kinetics are the ultimate limiting factor, and IP administration needs to be explored more in-depth if full closed loop will ever be reached.

• University of Surrey’s Dr. David Russell-Jones reviewed data from the phase 3 Onset program, supporting the use of Fiasp in type 1 diabetes and in pumps. Onset 1 (n=1,143) demonstrated modest but significant A1c improvements with Novo Nordisk’s Fiasp vs. NovoLog in adults with type 1 diabetes (0.15% greater with Fiasp at 26 weeks). See above for the 52-week data, presented by Dr. Bruce Bode as an oral. Additionally, Dr. Russell-Jones discussed Onset 4, a small, six-week compatibility trial of Fiasp in pumps for type 1 diabetes, which randomized patients to pumps with Fiasp (n=25) or NovoLog (n=12). On a primary endpoint of number of occlusions over six weeks, no confirmed cases occurred in either group, a positive lead-in to the proper large-scale Onset 5 trial of Fiasp in pumps – see above for those results as well (presented by Dr. David Klonoff), demonstrating Fiasp’s edge on postprandial glucose.

Select Questions & Answers

Q: Does Fiasp make a clinical difference for patients?

Dr. Russell-Jones: In the UK, Freestyle Libre has just been approved for coverage for people with type 1 diabetes. Anyone who puts on a CGM for the first time runs back to us when they find these huge post-meal excursions in blood glucose. Now we can say, “try this,” and see if they do improve with Fiasp.

Dr. Eda Cengiz: From a clinical care perspective, it is a huge difference if something improves post-meal blood glucose. Another thing is, 10 minutes faster onset is big if you’re sitting at the dinner table and everyone is waiting for you. I know Fiasp is not approved yet for children, but often our kids actually eat and then parents bolus afterwards for them. These “incremental” changes are important. In the future, we might see big improvements in artificial pancreas systems.

Dr. Stephanie Amiel Sheds Light on the “Unlearning” of Hypoglycemia Unawareness, Points to Specific Cortical Regions of the Brain

To a packed room (despite the 8 AM hour!), King's College London’s renowned Dr. Stephanie Amiel explained the neurological signatures of impaired hypoglycemia awareness, and she described her research into how awareness can potentially be restored. Educational interventions and the use of technology such as CGM or insulin pumps can improve hypoglycemia awareness, but it’s unclear exactly how this occurs. Dr. Amiel’s team performed fMRI scans on 12 people with hypoglycemia unawareness, both before and after an educational intervention. Although the data are still being analyzed, preliminary findings suggest a possible difference in anterior cingulate cortex (ACC) signaling before and after the intervention. This brain region is responsible for decision-making, conflict-resolution, evaluating actions, and detecting events that require a behavioral response – all of which is very consistent with a role for mediating the restoration of hypoglycemia awareness. Interestingly, the ACC is not one of the brain regions known to be involved in the development of hypoglycemia unawareness – among these, according to Dr. Amiel, are the globus pallidus (responsible for the aversive sensation that decreases with hypo unawareness), the pre- and post-central gyri (responsible for the symptomatic responses to hypoglycemia), and the temporal gyrus (responsible for consolidating the memory of a hypoglycemia experience). In our view, this raises the intriguing possibility that rather than simply reversing the neurological changes that mediate hypoglycemia unawareness, the awareness-restoring behavioral intervention activated an additional compensatory process mediated by the ACC. We eagerly await the full rundown of study results from Dr. Amiel. In the meantime, we’re fascinated by this potential mechanistic explanation for the “unlearning” of hypoglycemia unawareness.

Simple Basal Insulin Titration Algorithm Results in Superior A1c Reduction vs. Physician-Managed Titration in Type 2 Patients

Dr. David Russell-Jones (Royal Surrey County Hospital, UK) presented data (n=602) from a 24-week, multicenter randomized parallel-group study showing a simple patient-managed insulin glargine U300 titration algorithm results in slightly, but significantly greater A1c reductions than physician-managed titration. Type 2 patients not at goal on their previous regimen were randomized to either patient-managed or physician-managed groups. For the patient-managed group, dose adjustments were made by participants every time the median fasting self-monitored plasma glucose (FSMPG) differed from the target for three consecutive days – if the FSMPG was >130 mg/dl, the recommended dose adjustment was +3 U/day, while if the FSMBG was <80 mg/dl, the recommended dose adjustment was -3 U/day. For the physician-managed group, adjustments were recommended by the treating physician at each study visit or telephone call depending on glucose values. At 24-weeks, those in the patient-managed group (n=300) achieved an A1c decrease of 1.0% (baseline: 8.4%) while those in the physician-managed group (n=302) achieved an A1c decrease of 0.9% points (baseline 8.4%). The difference in reductions between groups were found to be superior. Though the 0.1% improvement can hardly be viewed as clinically significant in isolation, given that it was patient-driven makes it highly so. 67% of the patient-managed group and 58% of the physician-managed group achieved an FSMPG of 80-130 mg/dl without confirmed (<54 mg/dl) or severe hypoglycemia. Targets were achieved in a greater proportion of those in the patient-managed group regardless of prior insulin status. There were no differences in hypoglycemia events between groups. Given that very few providers have the time to provide tailored insulin titration, non-inferiority alone would be a huge win for the field – demonstrating superiority in A1c reductions is icing on the cake.

6. Beyond A1c and Additional Topics

Dr. Roy Beck at The diaTribe Foundation’s Beyond A1c 2.0: Where Do We Go From Here? Views on CGM Metrics, Rebranding “Estimated A1c”, and More

The diaTribe Foundation’s hosted a breathtaking ArtWalk #4 at the Belvedere Palace. This is Vienna's most famous museum with the world’s largest collection of Klimt oil paintings, along with a magnificent collection of art immortalized by Claude Monet, Egon Schiele, Vincent van Gogh, Max Beckmann and others. The museum was closed exclusively for a reception for guests of The diaTribe Foundation, followed by a tour of these magnificent works, featuring Klimt’s legendary “The Kiss," as well as so many other of his gorgeous paintings. Afterwards,  attendees took a gorgeous walk to an incredible local tavern called Gmoakelle to hear Jaeb’s legendary Dr. Roy Beck give a comprehensive overview on CGM outcomes beyond A1c. Download his fascinating slide deck here. In a 40-minute presentation, he detailed the limitations of A1c (not indicative of mean glucose on an individual level), consensus CGM metrics and data visualization (same as were agreed upon at last year’s Glycemic Outcomes Beyond A1c meeting), the validation of CGM metrics for trials, and the debate over estimated A1c (eA1c). Dr. Beck weighed in on one of the new hot questions in the glucose-centric movement: How much time in range (70-180 mg/dl) should people be spending? “Humbling” data from the T1D Exchange – some of the very best clinics in the US – showed that adults spend a mean 40%-50% of their time in the ideal glucose range, while youth spend 30%-40%. While he didn’t provide specific recommendations (it really is too soon to know until the field analyzes time in range profiles of patients considered to manage their diabetes with the very best tools and at the highest levels), he challenged everyone present to take the data as a reminder that “we’re not even near the end of where we need to be.” Unfortunately, despite the scientific community’s consensus on CGM metrics, they still have to be accepted by FDA (particularly CDER) to really move the needle – Dr. Beck sees hypoglycemia as an easier sell than time in range since there are copious data that time <54 mg/dl is detrimental. The door is still open for time in range, and Dr. Beck sees a few routes to close it: (i) evoke the transitive property of equality – time in range is associated with A1c and A1c is associated with CV complications, therefore time in range is associated with CV complications (“hasn’t sold them yet”); (ii) Use CGM in a longitudinal study to see if time in range is associated with complications (which is actually currently underway in the NIH-funded PERL study in kidney disease, thanks to Dr. Irl Hirsch and others, and could feasibly be included in CVOTs moving forward); (iii) redo the DCCT with CGM (“doesn’t seem practical” though we’d still say it’s not impossible); and (iv) use 7-point SMBG profile data from the DCCT to look for associations between in-range readings and complications (on Dr. Beck and Bergenstal’s already busy docket). Dr. Beck also showed many fascinating correlations in his talk (download the slides), highlighting that time-in-range is really a measure of hyperglycemia, and that many metrics are highly correlated with each other – including different measures of hyperglycemia (>180, >250, area under the curve, HBGI), hypoglycemia (<70, <54, area under the curve, LBGI), and variability metrics. Dr. Beck proposed that two measures are always going to be needed – e.g., time-in-range and time <54 mg/dl – as one metric cannot capture everything. Lastly, we were not previously aware that CDRH has received complaints that “estimated A1c” values (based on CGM-measured average glucose) were not aligning with lab-measured A1c values. While the CDRH staff likes the metric, they declared that it needs a new name to avoid seeding confusion and even distrust in either CGM or lab values. A survey was sent to ~100 endocrinologists and nurses in the T1D Exchange to ask for opinions, which ranged from “get rid of A1c altogether” to “Estimated Long Term Glucose Control” and “Three Month Glycemic Estimate.” Eventually, a number of folks in the field have come up with “Glucose Management Indicator” (GMI), of which Dr. Beck seems to be a big fan – he asked the room to vote on it and received great positivity. He sealed his talk and a follow-up conversation with our own Adam Brown definitively: “We’ve seen in our studies, if you had to pick one device, there’s no question in my mind, CGM is more important than a pump.” Pumps will be, of course, very important as a number of people move toward the closed loop. He also said it would be very important to have a room full of hypoglycemia experts consider questions around validation. Finally, Dr. Beck urged the entire room to think about more access to CGM, looking forward to a day where it is available in pharmacies without a prescription. In fact, Dr. Beck are looking at a study on that front, comparing home delivery of CGM with self-training to usual endo-prescribed CGM – whoa! We are elated that we have leaders like Dr. Beck leading the charge to embrace more patient-centric metrics of diabetes and that there are so many people in the field eager to think expansively – aided by the vision of Belvedere Palace and Gustav Klimt paintings.

Dr. Bergenstal Calls for CGM in CVOTs – “We Would Learn Amazing Correlations Between Glucose Variability and Outcomes”

IDC’s Dr. Rich Bergenstal advocated for all diabetes CVOTs to use CGM, which he argued is the most realistic path to correlate glucose variability with outcomes. In order for a measure of glucose variability to be “meaningful,” it has to show significant association with microvascular risk, Dr. Bergenstal explained. It’s unrealistic (but not impossible) that the field will sponsor another DCCT-like trial with coefficient of variation (CV) as the independent variable, but CVOTs are ~10,000-person datasets ripe for the picking. “Where else do we have 10,000 patients followed for five years with adjudicated outcomes? Why not just throw in a CGM?” We’re love this idea, as having CGM tracings as a component of CVOT results would provide hard evidence on the relationship between glucose variability and microvascular outcomes, while also giving researchers heaps more information about the drug’s action profile. As Dr. Roy Beck mentioned at the diaTribe Foundation’s “Beyond A1c 2.0” dinner last night, the NIH-sponsored PERL study is using CGM longitudinally to investigate how time-in-range affects kidney disease; the study was initiated in October 2017 (thanks to Dr. Irl Hirsch and others), and is expected to complete in August 2019 per ClinicalTrials.gov. Dr. Bergenstal echoed Dr. Beck’s commentary today, suggesting CGM in CVOTs as a way to demonstrate the promising applications of beyond-A1c glycemic metrics, proving their utility in the clinical trial setting (comparing drugs/devices) as well as the real-world clinical setting (identifying an optimal treatment plan for the individual with diabetes). “We could get some amazing data. We would learn amazing correlations between variability and outcomes,” Dr. Bergenstal emphasized. “We should work hard to make this happen.”

• Notably, post-hoc analyses of DEVOTE (Novo Nordisk’s CVOT for basal insulin Tresiba) have started this effort of correlating beyond-A1c glycemic metrics with outcomes. Across both arms of the study, Tresiba or Lantus, day-to-day glycemic variability was significantly associated with all-cause mortality (HR=1.58, 95% CI: 1.23-2.03, p=0.0004). Severe hypoglycemia also significantly increased risk for death in DEVOTE – in the first 15 days post-severe hypo event, the hazard ratio for all-cause mortality was 4.20 (95% CI: 1.35-13.09), which decreased to 2.78 (95% CI: 1.92-4.04) in the one year following a severe hypo episode. If the quality of life impact of glucose variability wasn’t compelling enough, DEVOTE has now shown RCT evidence linking variability to death. But DEVOTE didn’t use CGM – imagine the level of detail and analysis that would be possible with this technology.

• We hope to see more manufacturers invest in CGM for diabetes clinical trials, including CVOTs, although it may take a movement from thought leaders, patients, and even FDA and NIH, as Dr. Bergenstal suggested. His second research proposal around glucose variability was for NIH to create a “CGM toolbox” like there is for quantifying cognition or emotion. This could be a valuable resource to HCPs and researchers, alike, with the need-to-know on standardized CGM metrics, hypoglycemia definitions, time-in-range targets, and patient assessment tools.

• Interestingly, Peyser et al. and Garcia et al. published accompanying papers in the January 2018 edition of Diabetes Technology & Therapeutics introducing a new metric for variability, the glycemic variability percentage (GVP), which takes both the period and amplitude of the glycemic tracing into consideration. Calculating GVP is made possible by the richness of CGM data and was shown to capture differences in glycemic variability undetected by traditional metrics like CV or standard deviation (SD). The field seems to have reached a consensus on CV for now since it captures variation without being biased by the mean and is rather easy to understand, but is not without its problems, as it weights hypoglycemia and hyperglycemia equally – clinically, straying 70 mg/dl above the mean should probably not be viewed the same as straying 70 mg/dl below the mean.

Dr. Thomas Danne: “For Me, The Death Star Is HbA1c”; Details ATTD Call for Action 2018 to Petition Availability of Closed Loop in EU

In his opening ceremony remarks, Dr. Thomas Danne (Auf der Bult Hospital for Children and Adolescents, Germany) looked to Star Wars for some beyond A1c inspiration, claiming: “for me, the death star is HbA1c.” To illustrate how A1c can be extremely misleading, Dr. Danne referenced the recent paper published by Drs. Roy Beck and Rich Bergenstal (“The Fallacy of Average”) – the piece nicely summarizes how patients can achieve the same A1c, but have markedly different glucose levels. Dr. Irl Hirsch and colleagues’ have shared similar work on ethnic disparities for A1c. (See this highly-read diaTribe article for a summary.) Dr. Danne emphasized the need to involve regulatory agencies and policymakers in this important movement. He reviewed the recently published ATTD International Consensus statements (Diabetes Care 2017) regarding time in range and time in hypoglycemia, emphasizing that these metrics actually reflect patients’ daily experiences with their diabetes, unlike A1c. Dr. Danne highlighted that when describing glucose variability, coefficient of variation has less bias to hyperglycemia than standard deviation (since it is standard deviation divided by mean glucose). Interestingly, Peyser et al. and Garcia et al. published accompanying papers in the January 2018 edition of Diabetes Technology & Therapeutics introducing a new metric for variability, the glycemic variability percentage (GVP) which takes both the period and amplitude of the glycemic tracing into consideration. (See the photo from a Dr. Rich Bergenstal talk below; we believe far more education is needed on Coefficient of Variation, which only recently achieved consensus and is still confusing to many. Moving beyond to new variability metrics is interesting from a research perspective, though the field is certainly not short of yet more metrics to describe glycemic variability.) Ultimately, Dr. Danne acknowledged that while A1c is quite useful for assessing health on a population level, CGM is needed for personal care to determine whether a given individual is moving in a healthy direction. We agree!

• In a final reference to Star Wars, Dr. Danne urged the audience to not fear closed loop systems, quoting Yoda: “Fear is the path to the dark side.” He cited the #WeAreNotWaiting movement as an indication that patients all over the world are ready for this life-changing technology. He urged attendees to sign the ATTD Call for Action 2018, which petitions for accelerated availability of closed loop systems in the EU. Nearly 900 attendees did, including our team. We’ll be interested to see if this moves the regulatory needle in the EU – the MiniMed 670G was in the CE Mark process as of February, Diabeloop had submitted its algorithm (though pump and CGM submissions were not clear), and DreaMed received CE Mark for its MD Logic algorithm years ago.

Higher Mean Glucose in Cardiac Perioperative Setting More Closely Correlates with 30-Day Mortality than A1c

Conference co-chair Dr. Tadej Battelino detailed a freshly-published paper (Van Den Boom et al., Diabetes Care) showing that higher mean glucose in the cardiac perioperative setting significantly correlated with lower 30-day mortality. A1c had no such relationship. The graph of perioperative mean glucose vs. percent mortality in cardiac procedures was striking, with a U-shaped curve indicating best outcomes (~3% post-op mortality) occur when mean glucose is between 120-160 mg/dl. Contrarily, mortality rises to ~11% and ~15% when mean blood glucose is 80 mg/dl and 220 mg/dl, respectively. In Dr. Battelino’s words, “A1c is useless in this prediction…if we switch to time-in-range, we can save lives within 30 days.” Interestingly, the relationship didn’t hold for non-cardiac procedures, where post-op mortality was significantly lower, rising steadily from ~1% at 80 mg/dl to ~1.5% at 220 mg/dl. This study is fascinating, and will hopefully add fuel to the push to validate outcomes beyond A1c. (We’ve seen a number of hospital studies like this in past year, and hope as CGM is more used in the hospital, we’ll see more.) Of course, it’s also possible this study points to correlation, not causation: If a surgery goes well – no adrenaline surges causing blood sugar to spike, and no sudden drops in blood sugar – then one might expect 30-day mortality to be lower. Mean blood glucose may just reflect other processes during a surgery that have a greater impact on mortality. It’s logical that the same relationship wouldn’t hold for A1c since A1c is a marker of average blood glucose over the past ~three months, not an indicator of surgery successes.

Dr. Eran Segal’s Personalized Nutrition Project: Microbiome-Based, Predictive, Individualized Diet Advice Based on CGM Diet Study

Weizmann Institute’s Dr. Eran Segal provided a fascinating overview of his work on the Personalized Nutrition Project, an initiative designed to uncover personal nutrition recommendations using insights from the microbiome. From a data science perspective, this research has been a massive undertaking: Across 800 study participants, Dr. Segal’s group used CGM data to measure glucose response to nearly 50,000 meals. From there, the researchers developed a machine-learning algorithm that integrated the CGM data, dietary intake, anthropometrics (BMI, A1c, etc.), and microbiome composition to produce a prediction of each individual’s post-prandial response to a different meal. The researchers then designed an individualized “good” and “bad” diet for 100 of the original participants based on the algorithm’s assessment of their microbiomes. In a blinded CGM study, the algorithm-recommended diet resulted in significantly lower post-prandial glucose responses – see the very cool TED Talk here and the 2015 Cell paper here. Although this research was conducted in a non-diabetes population, we see big potential implications for this predictive microbiome-based diet to minimize post-prandial excursions in people with type 1 and 2 diabetes alike, as well as the prediabetes population. To this end, Dr. Segal’s predictive algorithm was recently licensed to DayTwo, which makes an app that provides personalized decision support and nutrition advice for blood sugar management based on customers’ microbiome samples. Last February, DayTwo and Dr. Segal’s lab teamed up with the Janssen Human Microbiome Institute to conduct further translational research on the gut microbiome, with the ultimate goal of refining DayTwo’s app to make even more actionable microbiome-based nutritional guidelines. While we believe that both the novelty of the field and complexity of the gut microbiome limits how quickly we will see any concrete microbiome-based therapies, we are intrigued by its potential in the near-term to inform this kind of decision support technologies paired with CGM and other biometric data – an area of high unmet need in the realm of nutrition, where we still have so very much to learn.

7. ATTD Yearbook

The 2018 ATTD yearbook session shared 12 chapters, covering the year of publications in diabetes technology and therapeutics. Dr. Tadej Battelino noted that last year’s version received 12,000 downloads, led by three popular chapters: digital health, CGM, and new insulins. See summaries of each chapter below, or get the full yearbook here.

Continuous Glucose Monitoring in 2017

• Dr. Bruce Bode reviewed the “busy year” in CGM studies, covering DiaMonD and REPLACE-BG. He reviewed the type 1 (JAMA 2017; ADA 2016), type 2 (Ann Int Med 2017; ATTD 2017), and pump extension (Lancet D&E; ATTD 2017) phases of DiaMonD, noting that MDIs can benefit from CGM regardless of diabetes type or level of education. In particular, Dr. Bode emphasized the A1c and time-in-range benefits in both DiaMonD cohorts; the ~3 SMBGs/day in DiaMonD at baseline; and the very strong compliance with CGM in this study. He also covered the REPLACE-BG study, which confirmed the safety of non-adjunctive use of Dexcom CGM. The CGM chapter includes 16 total articles and can be found here.

Closing the Loop

• Harvard’s Dr. Eyal Dassau reviewed the closing the loop chapter, spending the most time on the landmark NEJM 2016 study testing Cambridge’s system in pregnancy for up to 3+ months, including during labor – read our coverage of that here. Dr. Dassau was very impressed with the results (as we were), noting the outstanding reduction in variability (see the compelling modal day profiles here): “This is what technology can do across the board.” He noted the importance of bringing closed loop to broader populations – especially pregnancy – as they are often excluded in current studies (particularly in the US). The chapter also includes several other major papers in the closed loop field, including the 670G pivotal study outcomes in adults/adolescents (JAMA 2016 and DT&T 2017); three Cambridge team studies, including a compelling one in type 2 diabetes that we first saw a couple years back (Diabetes Care 2016, Lancet D&E 2017, Lancet D&E 2017) Bionic Pancreas multicenter study (Lancet 2016), among others. The Closing the Loop chapter includes 15 total articles and can be found here.

Using Digital Health Technology to Prevent and Treat Diabetes

• Dr. Neal Kaufman reported on the digital health chapter – the most downloaded of the previous year – which reviewed 19 articles. Even before delving into discussion of data, Dr. Kaufman expressed concern with the types and quantity of articles that were available for review; There were “only three intervention studies worth sharing…not a good idea,” along with 10 systematic reviews, which detailed outdated studies performed ~five years ago. And echoing a debate the field has been negotiating of late, Dr. Kaufman pointed out that there are over 15,000 diabetes apps out there, with very few researched. “The evidence for effectiveness and generalizability to the larger population is not really there. As you can imagine, those trials are difficult. Yet there were a number of analyses conducted and published in the past year, showing “modest” and “not really prolonged” improvements in glycemic control, physical activity, and weight loss. Interestingly, Dr. Kaufman highlighted TEXT4DSM, which implemented a texting intervention in three diabetes programs that existed in three low-resource countries (the Democratic Republic of Congo, Cambodia, and the Philippines). The study was large (n=1,440 patients, presumably with type 2 diabetes) and the text intervention included messages pertaining to healthy eating, physical activity, medications, foot care, and more, but did not result in a difference in the proportion with well-controlled diabetes after two years (although there was a decrease in foot wounds in the experimental group). He suggested that the lack of positive impact “implies caution about mHealth outcomes,” but acknowledged a number of possible reasons for no impact. On the one hand, we found it curious that the one study Dr. Kaufman chose to feature used a relatively simplistic intervention and had negative results, but on the other hand, this may reflect the dearth of randomized, controlled, peer-reviewed outcomes in this area. We expect the slew of newer developments, such as personalized coaching and insulin titration, will slowly make its way into the literature and change this summary meaningfully in the years to come.  Download the full chapter here.

  • Our team’s Clinical Diabetes article on challenges in digital health was the first article reviewed in the chapter. The paper was written by Varun Iyengar (a Close Concerns Associate alum), Alex Wolf (a diaTribe alum), Adam Brown, and Kelly Close

Insulin Pumps

• Reviewing pump therapy, Dr. John Pickup identified six themes from the past year: (i) Comparative effectiveness of MDI vs. pump therapy (are pumps as beneficial as some had traditionally thought?); (ii) Factors that determine effectiveness of pump therapy (further evidence that poor control on pump therapy is not associated with fear of hypoglycemia, but psychological issues); (iii) The role of pumps in type 2 diabetes (a meta-analysis from Dr. Pickup’s group shows pumps are most effective in those with highest baseline A1c and insulin dose; see above); (iv) safety and reliability of pump therapy (surveys show reliability of modern pumps continues to be a concern, and SAP may be the most unreliable); (v) ultra-fast-acting insulin in pumps (potential for improved control); and (vi) PLGS pumps (evidence for reduction in hypoglycemia, including after exercise, though longer-term studies in adults with severe hypoglycemia are still needed). He dug in deeper on the first theme, pointing to the somewhat controversial REPOSE results suggesting that glycemic outcomes in type 1 patients were no different on pumps and injections (though satisfaction was higher in the pump group) – see our coverage from IDF 2015 here, including an insightful interview with Dr. Irl Hirsch. There are a host of positive and negative factors to consider, said Dr. Pickup: On the positive side, the REPOSE study was robust (large, and long) and subjects were not highly-selected, but on the other hand, the study had a small number of patients with severe hypoglycemia, A1c difference was significantly different for those with baseline A1c ≥8.5%, there was a large center difference in pump efficacy, etc. He also pointed to the DIaMonD type 1 pump extension phase (Lancet D&E; ATTD 2017), which found that glycemia is further improved by switching to pumps in type 1s already on CGM, though biochemical hypoglycemia was increased. The whole pump chapter can be downloaded here.

Self-Monitoring of Blood Glucose

• Kicking off the packed ATTD Yearbook session, Dr. Irl Hirsch reviewed the “important, but older technology” that is SMBG. A study published in JAMA Internal Medicine looked at the policy impact in Ontario, Canada of limiting test strips in 2013: 400 strips/year for those receiving drugs known to cause hypoglycemia, 200 strips for all other patients, and 3,000 strips/year for those using insulin. The time series analysis (2008-2015) showed the policy reduced costs by 20% (24 million Canadian dollars), without a negative impact on emergency department visits or A1c (JAMA Int Med, 2017). Dr. Hirsch questioned whether the costs of SMBG will continue to decrease in both high- and low-income countries, especially given these Canadian results. More importantly, and Dr. Hirsch’s “big concern,” he wondered how strip quality might be affected if SMBG use declines alongside increasing CGM penetration. Dr. Hirsch detailed a Swedish study (BMJ Open Diabetes Res Care 2017) surveying 314 type 1 patients not using CGM. Only 44% of respondents indicated that they take a fingerstick four or more times/day, leaving more than half of the participants with an SMBG frequency below the recommended rate – no surprise there, given T1D Exchange data and dQ&A data (see Adam’s presentation from day #1). Top reasons for not testing included forgetting, a lack of time, and self-consciousness. Unfortunately, Dr. Hirsch believes SMBG frequency is unlikely to improve. The SMBG chapter reviews 14 key articles and can be found here.

Diabetes Technology and the Human Factor

• Dr. Alon Liberman summarized 2018’s “Diabetes Technology and the Human Factor” chapter, touching on two themes: locus of control and barriers to device use. “Locus of control” refers to whether individuals believe that they have control over the outcomes/events in their lives. When applied to diabetes, people with an internal control orientation believe that success or failure are attributable to their own efforts. A 2017 study in Diabetic Medicine found that internal locus of control “plays a significant role in achieving tight glucose control” in type 1 adults on pumps. The correlations in the actual paper are not that strong (r=0.18 or less), though they are statistically significant and do link locus of control to A1c and severe hypoglycemia. Dr. Liberman also reviewed two psych studies on devices, one on barriers to uptake (Tanenbaum et al., Diabetes Care 2016) and another on clinicians’ views on barriers to adherence (Tanenbaum et al., JDST 2017). We liked some of the questions included in these studies, which serve as a bar for devices to meet: “Diabetes technology has made my life easier”, “Diabetes technology has made managing my health easier”, and “I am lucky to live in a time with so much diabetes technology.” This chapter includes 11 total articles and can be found here.

Technology and Pregnancy

• Dr. Jennifer Yamamoto (filling in for Dr. Helen Murphy) emphasized that there is still substantial room to improve glycemic control in pregnant women with preexisting diabetes. She reviewed a study (Diabetologia 2017) analyzing 2015 national audit data (n=3036 women) showing only 14% of those with type 1 diabetes and 37% of those with type 2 diabetes meet the A1c target of <6.5%. Pregnancy preparation remains less than ideal, with high numbers of complications: Prevalence rates for congenital anomalies (46.2/1000 births for type 1, 34.6/1000 births for type 2) and neonatal death (8.1/1000 births for type 1, 11.4/1000 births for type 2) were unchanged as compared to 2002/2003. However, stillbirth rates were nearly 2.5-times lower, dropping from 25.8/1000 births to 10.7 and 29.2/1000 births to 10.5 for type 1 and type 2 mothers, respectively. On a more positive note, Dr. Yamamoto detailed Dr. Murphy’s study investigating closed loop insulin delivery during pregnancy in women with type 1 diabetes (NEJM 2016; read our coverage). She found it particularly telling that 14 out of the 16 participants chose to continue on closed loop therapy throughout their pregnancy and noted the system performed “remarkably well.” There were no hypoglycemia events lasting over 20 minutes either 24 hours prior to delivery or 48 hours post-delivery. Women reported 87% time-in-range 24 hours prior to delivery and 74% time-in-range 48 hours post-delivery. Dr. Yamamoto was particularly excited by the ability for closed loop to adapt to the changing demands of pregnancy, including dynamic insulin resistance, glucose utilization, steroid use, and labor and delivery. The technology and pregnancy chapter reviewed 10 articles and can be found here.

Diabetes Technology and Therapy in the Pediatric Age Group

• Dr. David Maahs gave a crisp review of five pediatric diabetes trials published in the past year, demonstrating steady progress in diabetes tech (from PLGS to day-night closed loop in poorly controlled adolescents and young children), but emphasizing that there is still more work needed to bring these benefits to more children worldwide. He began with Battelino et al.’s 14-day PLGS study in children with type 1 diabetes, which showed that predictive insulin suspension resulted in fewer hypoglycemia events, but at the expense of more time spent >140 mg/dl. Spaic et al.’s follow-on paper showed that addition of predictive hypoglycemia-hyperglycemia minimizer to PLGS is safe, feasible, and effective overnight (increasing time-in-range and lowering mean glucose). Next, Tauschmann et al. demonstrated that day-and-night hybrid closed loop therapy in adolescents resulted in higher time in range, lower mean glucose, and less hypoglycemia in adolescents with type 1. Dr. Maahs again cited Dr. Tauschmann et al.’s paper describing free-living home use of 24-hour hybrid closed loop in sub-optimally controlled adolescents with type 1 to be safe, feasible, and glycemia-improving (without a concomitant increase in hypoglycemia). And lastly, Del Favero et al.’s camp study investigating closed loop in 5-9-year-olds showed that closed loop is feasible and safe, though a 3x decrease in time-in-hypoglycemia was counterbalanced by a decreased time-in-range and increased mean glucose. Download the full chapter here.

Advances in Exercise, Physical Activity, and Diabetes Mellitus

• As Dr. Michael Riddell astutely noted, the fitness and diabetes fields are beginning to merge. Dr. Riddell found a whopping 1,334 papers on exercise and diabetes in the yearbook timeframe, but limited himself to ten for the ATTD Yearbook chapter on advances in exercise, physical activity, and diabetes mellitus. In one study (DTT 2017), circuit-based exercise was found to be less risky than continuous exercise, resulting in a less-dramatic drop in blood glucose. However, Dr. Riddell cautioned that there is still substantial individual variability, with certain participants showing a rise in blood glucose following higher-intensity circuit-based exercise. He reviewed a second study (Diabetes 2017) suggesting that high-intensity interval training (HIIT) reduces hypoglycemia awareness in type 1 diabetes patients following exercise. He found these results “a little bit alarming,” creating yet another perfect storm for people with type 1 diabetes to deal with. Interestingly, participants scored higher on a cognitive performance test following HIIT – even more intriguing, the difference in cognitive score was found to be significant only in the sub-group with type 1 diabetes and no history of impaired hypoglycemia awareness. Exercise will continue to be a hurdle for closed loop systems, given the extreme inter- and intra-patient variability, though we’re optimistic about decision support and smarter algorithms here – since most people to the same types of exercise, pattern recognition should be possible.

New Insulins, Biosimilars, and Insulin Therapy

• Dr. Thomas Danne presented on faster, longer, safer, and biosimilar insulins. First, faster. He highlighted Novo Nordisk’s Fiasp (faster-acting insulin aspart) as the first-in-class ultra-rapid mealtime insulin. Although pre-meal injection leads to the best outcomes, Dr. Danne alluded to the fact that Fiasp can be injected up to 20 minutes after you start eating (it’s the first injectable bolus approved without a pre-meal dosing recommendation, which affords extra flexibility around meals). Next, longer. Dr. Danne mentioned Novo Nordisk’s Tresiba (insulin degludec) and Sanofi’s Toujeo (insulin glargine U300), pointing to a CGM study (from Dr. Rich Bergenstal) that confirmed Toujeo’s flatter profile vs. Lantus. He said a direct head-to-head comparison of the two advanced basals is “highly-desirable,” so that HCPs can better understand the differential advantages/disadvantages to decide which insulin is right for which patient. These head-to-head RCTs are coming – Sanofi’s BRIGHT and a Novo Nordisk-sponsored comparison trial – and could be part of next year’s ATTD Yearbook. Third, safer. DEVOTE provided reassurance around Tresiba’s CV safety, in addition to showing hypoglycemia benefit vs. Lantus. Lastly, biosimilars. Compared to other disease areas, diabetes is behind in bringing biosimilars to market, according to Dr. Danne. That said, 2017 was an important year for biosimilar insulins, and the Yearbook features studies of Lilly/BI’s Basaglar vs. Lantus as well as the SORELLA studies of Sanofi’s Admelog vs. Humalog. The “new insulins” chapter includes 17 total articles and can be found here.

New Medications for the Treatment of Diabetes

• Dr. Satish Garg discussed new medications for the treatment of diabetes that emerged this past year, including basal insulin/GLP-1 combos and SGLTs for type 1. The new fixed-ratio combination class, comprised of Sanofi’s Soliqua and Novo Nordisk’s Xultophy, saw “modest uptake” in its first full year on the market. In the words of Dr. Garg, these products are “making their way,” though volume/sales trended below expectations in 2017. He forecast that SGLT inhibitors may become an option for people with type 1 diabetes by next year, pointing to inTandem3 (Sanofi/Lexicon’s sotagliflozin will be filed with FDA in the “very near future”) and DEPICT 1 (AZ’s phase 3 study of dapagliflozin in type 1), which both read out at EASD 2017. Dr. Garg focused much of his short presentation on MannKind’s Afrezza, and this particular Yearbook chapter includes numerous papers on the inhaled mealtime insulin (Postgraduate Medicine 2016, Cardiology in Review 2017, World Journal of Diabetes 2016, etc.). Dr. Garg reviewed the FDA’s label update to Afrezza to reflect an ultra-rapid-acting profile, which came through in October 2017, and he shared an optimistic outlook on how this product could improve postprandial glucose control in people with diabetes. The full chapter on new medications, highlighting 23 studies, is available here.

Immune Intervention for Type 1 Diabetes

• Dr. Desmond Schatz highlighted a 2017 study on type 1 diabetes immune intervention, emphasizing efforts to identify responders to immunotherapy and define immune markers of type 1. Malmegrim et al. found that immunological balance of autoreactive and regulatory T cells was associated with C-peptide levels following autologous hematopoietic stem cell transplantation (AHSCT). In this study (n=21), longer duration of insulin independence after AHSCT was associated with higher regulatory T cell counts, and the subgroup of patients with lower frequencies of autoreactive islet-specific T cells had superior responses to stem cell transplant (remained insulin-free for longer, presented with higher C-peptide). Dr. Schatz discussed the concept of endotypes, the different potential disease mechanisms that can be associated with the phenotype of type 1 diabetes, and he explained how research is now moving to identifying these. Better understanding these etiologies should enable personalized immune therapy, as researchers continue piecing apart the immunological mechanisms leading to type 1 diabetes. The Immune Intervention for Type 1 Diabetes chapter includes six articles and can be found here.

8. Startup Showcase

Between sessions on Day #2 and Day #3, we heard 15 10-minute pitch presentations from several start-up companies in the diabetes arena. Session chair Prof. Moshe Phillip characterized this as “the most important part of the ATTD meeting – the future.” Indeed, these sessions were filled with exciting early-stage projects; below, we recap some of the most promising ventures.

Arecor

• Arecor CEO Dr. Sarah Howell presented new preclinical data on the company’s ultra-concentrated rapid-acting insulin, which completed preclinical studies early in 2018. Arecor’s U1000 candidate showed an onset of action and PK/PD profile comparable to U100 insulin aspart (Novo Nordisk’s NovoLog). Merely increasing the concentration of NovoLog to U1000 confers markedly slower onset of action, which is an unacceptable tradeoff for prandial insulin (when fast onset/offset is critical for precision around meals). In contrast, Arecor combines insulin aspart with proprietary formulation technology Arestat to maintain onset time. Dr. Howell did show that the tail of Arecor’s candidate is longer vs. U100 aspart, and we wonder how this will play out in the first-in-human studies, planned for 2018. Notably, Arecor’s U1000 insulin could have applications in miniaturized insulin pumps/closed loop systems, and it stands to improve quality of life for those who require higher doses of insulin (the company has positioned its candidate for patients with total daily insulin dose >200 units). Dr. Howell also presented data on Arecor’s ultra-rapid insulin, another reformulation of insulin aspart, which has shown faster onset (but not offset) vs. NovoLog in a pig model of diabetes. Beyond this, Dr. Howell pointed out that the ultra-rapid candidate seems at least comparable to Novo Nordisk’s Fiasp (faster-acting insulin aspart) in both onset and offset time (possibly even faster on the front end) – could Arecor’s ultra-rapid insulin offer a meaningful improvement over even Fiasp? We’re intrigued by the possibility, though we understand that this is still very early-stage. Finally, we learned that Drs. Bruce Buckingham, Eda Cengiz, and Thomas Pieber have joined Arecor’s Scientific Advisory Board; having such expertise on board is certainly confidence-inspiring.

Integrated Medical Sensors

• Dr. Muhammad Mujeeb-U-Rahman, co-founder of Integrated Medical Sensors (IMS), highlighted the development progress for his company’s preclinical implantable CGM – which he deems the “world’s smallest CGM.” Born out of Dr. Mujeeb-U-Rahman’s electrical engineering thesis work at Caltech, the sesame seed-sized sensor is the first fully-integrated implanted CGM that uses standard electrochemical monitoring. Despite its small size (3 mm x 0.6 mm), it contains every component of a computer – a tiny processor, an antenna, and a sensor. The three- to six-month-wear sensor can be injected under the skin using a simple needle and interfaces with a wearable wireless transmitter (such as a smart watch) in order to relay the data to a smartphone app. The sensor has demonstrated a MARD of 12.5% in animal studies, and according to the company, human feasibility studies could begin as early as this year after final “chemistry optimization.” Due to its inexpensive underlying semiconductor technology, the sensor is projected to cost just $1/day – a key differentiator from other products on the market. That said, IMS’ product is very early stage in an already robust competitive landscape: Senseonics’s 90-day Eversense implantable sensor has already launched in 14 countries (a variety of EU countries plus South Africa) and remains under FDA review; the 180-day version is slated for a 2Q launch in Europe. Furthermore, Glysens’ one-year implant is awaiting a pivotal trial, and there are additional implantable CGM projects in development by Profusa. And perhaps most importantly, non-implantable sensors are growing more accurate, user-friendly, and discrete – how will the market segment between implanted vs. subcutaneous sensors?

Med Angel

• Mr. Amin Zayani, CEO of Med Angel and winner of the 2017 Novo Nordisk-Lyfebulb Innovation Summit, discussed his company’s smart, waterproof sensor that continually measures the temperature of insulin (or other injectables, including Epipens, biologics, and hormones) in order to ensure that it is safe to use. The Med Angel app sends notifications and alerts to the user, displaying a heart to indicate temperature in one of three colors: (i) green for in range (~36­°-46° Fahrenheit for most insulins), (ii) blue for too cold, and (iii) red for too hot. Users select their insulin from a list within the free Med Angel app (iTunes, Google Play), which supports all available insulin products in the US and Europe. Google Play users have rated the app 4.8 stars (19 reviews) with 500-1,000 reported installs. The product is currently available on Amazon, priced at $45 and earning 3.7/5 stars in 15 customer reviews. As a person with type 1 diabetes himself, Mr. Zayani described his relationship with insulin as “the most important relationship in my life” in that it requires constant, everyday attention. He learned firsthand the importance of keeping insulin in a narrow therapeutic range after he ended up in the emergency room from dosing himself with insulin that had been accidentally frozen and therefore rendered ineffective.

  • Mr. Zayani compared data from 432 MedAngel users to published data from 255 patients on biologic disease-modifying anti-rheumatic drugs, finding that fewer MedAngel users exposed their drugs to temperatures below zero for two hours or longer (13% vs. 25%). As an added benefit, Mr. Zayani mentioned, “even in the event that such accidents happen, users are informed of them and can act accordingly.”

Baci Insulin Infusion Systems

• Dr. Thiago Artioli unveiled the Baci Insulin Infusion System, a 3D-printed insulin pen well-suited for type 1 diabetes patients in low-resource areas due to its low-cost (~$1/pen) and extreme user-friendliness. Hailing from Brazil, Dr. Artioli explained the severe limitations that poverty places on insulin therapy – both in terms of cost (an insulin pump costs 1400% of the monthly income of a low-income person in Brazil) and in terms of usability, given low medical literacy and the complicated dosing regimen for insulin. The 3D-printed Baci pen represents a cheap, simple insulin delivery tool – vastly more patient friendly than a traditional insulin syringe. The pen additionally comes with 3D-printed insulin cartridges which can be made in different colors or in different shapes to help make dosing less complicated for patients with low medical literacy (i.e. “Take two pink squares every morning and take one blue circle with meals.”) According to the company website, the pen accepts any type of insulin refill. We’ll be eager to see outcomes data for the device, as it has the potential to improve access to diabetes care in low-resource settings.

Microdermics

• Dr. Sahan Ranamukha, co-founder and VP of R&D at Microdermics, presented compelling proof-of-concept data on the use of Novo Nordisk’s Fiasp via intradermal injection. Compared to subcutaneous administration, intradermal administration gave significantly faster appearance of Fiasp (faster-acting insulin aspart) in the bloodstream (Tmax of ~5 minutes vs. ~15 minutes subcutaneously), as well as faster offset of action. The insulin reached a similar maximum concentration with both injection routes. While intradermal administration of Fiasp has only been evaluated in a rat model, we’re quite intrigued by these results – this is evidence that an alternative administration method could bring Fiasp even closer to mimicking endogenous insulin secretion, and we hope Microdermics pursues this further. (That said, BD tried to make this technology work and did not push it forward, so the early data will have to be confirmed and scaled commercially.) The company’s intradermal platform uses microneedles to take advantage of the rich vascular (capillary and lymphatic) and immune system presence in the intradermal space. Benefits include improved patient experience (comfort, ease of use), dose reductions, improved drug performance, and the potential for integration with existing drugs with respect to volume, viscosity, and speed. We think this concept could appeal to a wide range of patients, especially children, the elderly, those with serious phobia of needles, and those with motor challenges. Moreover, we would be particularly interested to see whether this platform could be used with GLP-1 agonists: Improved absorption could allow for greater efficacy at lower doses, potentially leading to an improved side-effect profile (i.e. more GI tolerability) and even lower cost.

9. Exhibit Hall

Abbott

Not surprisingly, Abbott’s large, welcoming booth advertised FreeStyle LibreLink, LibreLinkUp, and LibreView, all now available in 12 EU countries for Android and iOS (launched just before ATTD). It was great to see the app focus in an Abbott booth, which has historically shown only readers. Representatives were unable to provide updates on when we might expect to see these features in the US, nor could they comment on a potential pediatric indication for the FreeStyle Libre in the US (it is already available for pediatrics in the EU). A non-randomized, single-arm study evaluating the safety and effectiveness of FreeStyle Libre in pediatric populations (4-17 years-old) is listed as currently recruiting on Clinicaltrials.gov. It’s likely this study will serve as the basis for a pediatric FDA submission, in which case Abbott likely won’t launch in pediatrics until late 2018.

Ascensia

The Ascensia booth highlighted the Contour Next One BGM and new features of the paired Contour Diabetes app, including “my patterns” pattern detection, test reminders, and Contour Cloud compatibility (patients can now sync their glucose results with Glooko so that providers can view them). All of these features are already live in Germany, and to arrive in other markets by the end of April (no comment on US timing). The reps were also not able to comment on the Voluntis partnership, which was previously expected to launch in 4Q17, though the companies are still working on it.

BD

At BD’s Type 2.0 Lab, attendees voted on which areas of diabetes technology warranted prioritization. A screen in the booth displayed real time results. We stopped by fairly early in the meeting, but at the time a tube-free insulin delivery device was in first place, holding 21% of votes – great news for BD! Dose capture was in second place (17% of votes) and flexible dosing was in third (15% of votes). As expected, booth representatives were unable to comment on the current status of BD’s infusion set partnership with Medtronic, international plans for BD’s type 2 smart patch pump Swatch, or news on the decision to halt the smart pen needle program (per the company’s 4Q17 call).

Biocorp

Biocorp, whom we first wrote about upon their receiving a CE mark for their Easylog smart pen attachment in December, divulged expectations to launch in the US this summer and in the EU by the end of the year, both with partners. The rep demoed the device, which consists of an oblong piece that clips on to the top of the pen, and a circular piece that fits over the control dial/button (see pictures below). Dose capture is accomplished simply by tracking the turn of the pen’s dial. The rep further indicated that it will cost <$50, be compatible with all major pens (including Lilly, Sanofi, and Novo Nordisk’s), and last for two years. Further, because it will launch with partners, the paired app that we wrote about in December is more of a placeholder that can be replaced or augmented by proprietary software from the partner company. If the technology is deemed accurate and durable (Biocorp is still rather unknown to us), then it might be in a device or pharmaceutical company’s best interest to acquire Easylog.

Biomicro

Singapore-based Biomicro is developing a 12-mm (the size of a grain of rice) implantable sensor/stimulation platform that can be used for a number of different applications, including neurostimulation (for pain) and glucose sensing. A poster boldly touted “ultra-low powered implantable CGM” with factory calibration and a 180-day lifetime. The device would be implanted under the skin, transmit to a reader (large – about the size of a deck of cards at this point) that sits on top of the skin and powers the sensor, which then sends glucose readings to a smart device via Bluetooth. Unlike Senseonics’ reversible glucose-binding fluorescence-based reaction, Biomicro’s sensing mechanism is irreversible, though the rep told us that byproduct buildup over 180 days wouldn’t be an issue. The company is extremely early-stage at this point, with animal trials expected to commence next month.

Cnoga

The Cnoga booth displayed the company’s BGM, consisting of two parts: (i) a traditional fingerstick used for calibration; and (ii) a non-invasive BGM channel personalized to the individual (see picture below). Users calibrate with eight fingersticks/day for the first week and can then test non-invasively. The device has been CE marked for two years with “thousands” of “very happy” users in 10 countries – we haven’t previously heard of it, so presumably uptake has been quite limited. Booth representatives boldly expect 1.5-2 years until a US launch and have just submitted IRBs for two clinical trials in the US. The non-invasive monitor reportedly leverages the same technology as face-recognition software, using optical sensors to generate signals from four LED sources. Representatives emphasized that it is the most accurate non-invasive device on the market: A trial conducted in Germany found that the non-invasive monitor “came close” to meeting the 2013 ISO requirements, with calibration issues at fault for the readings in Zone B. Thorough initial calibration is key for the success of the BGM, as it is driven by self-learning software (i.e. the more readings the device has over a broader blood glucose range, the more accurately it will be able to read non-invasively). It’s a tough time to break into the BGM market, though a non-invasive device – if it actually works – would certainly help Cnoga persevere.

Defymed

In a mid-size booth at the side of the exhibit hall, Defymed displayed its two preclinical intraperitoneal (IP) insulin infusion devices: the ExOlin insulin delivery device and the MailPan Bioartificial Pancreas. ExOlin involves a biocompatible membrane that is implanted in the patient’s abdomen and a subdermal membrane that fields injections. The non-biodegradable device is permeable to insulin, and allows insulin to be delivered to the sub-dermal membrane via injection – this allows patients to continue their normal insulin injection methods (i.e. syringes, pens, and pumps), while still providing the advantages of greater portal vein insulin delivery (similar philosophy to Roche’s DiaPort). According to the Defymed representative, the device is on track to enter its first in-human trial in Europe by the end of the year, and the company hopes to achieve CE marking by the end of 2020. The even-earlier-stage MailPan Bioartificial Pancreas involves a semipermeable, immune protective membrane pouch that can be filled with insulin-secreting cells and inserted into the intraperitoneal space; a subdermal membrane fields injections to provide nutrients to the encapsulated cells, which would otherwise lose vitality because of lack of vascularization with the surrounding tissue. The product is expected to enter phase 1 in 2020. Notably, Defymed is in partnership with Semma Therapeutics for preclinical validation of a version of the MailPan device containing Semma’s insulin-producing stem-cell derived beta cells. Though these early-stage projects are certainly exciting, IP infusion technology is not without steep scientific challenges. As discussed at length at the JDRF-Helmsley Charitable Trust Closed Loop Intra-Peritoneal Infusion Workshop, “biosymbiosis” to avoid a foreign body response clogging the catheters will be a major hurdle for Defymed to overcome.

Dexcom

Dexcom showcased G5 mobile on iOS and Android phones, alongside table-top screens highlighting the web-based Clarity data management platform. Clarity was a bigger focus than ever for Dexcom at ATTD – see above for coverage of the dedicated oral and symposium, which shared glycemic outcomes from 50,000 US users, screenshots of EHR integration, and uptake statistics. Handouts focused on the benefits of CGM in MDI, including ample reprints of the DiaMonD study.

Diabnext

At the Diabnext booth, we learned that the company’s multi-device AI management platform (BGM connector, pen dose capture, connected pill bottle top, activity sensor, weight scale, carb counting app) will first launch in China in March followed by a US launch expected in June – this has been pushed back again, most recently from the expected 1Q18 timeframe shared at CES. The app is being piloted in multiple countries to collect patient feedback and to support reimbursement in Singapore, Australia, and France. In the US, the app will be free with a premium version priced at less than $50/year including special features like graphs and additional insights. Each device will cost $49 with special coupons provided in exchange for patient recommendations. Diabnext hopes to partner with insulin, pump, and BGM companies to pursue US reimbursement from self-insurers and expects to receive France reimbursement “pretty fast.” The company is proposing to the Australian and Japanese governments for reimbursement and eventually hopes to pursue CMS, though we imagine CMS’s gatekeepers will need to see some compelling outcomes data, of which Diabnext has none that we know of at this stage. As a reminder, the “all-in-one” digital diabetes management platform includes: a cable to Bluetooth-enable non-connected meters (Gluconext; think Glooko’s MeterSync Cable); an insulin pen clip attachment to capture doses (Clipsulin; slightly dubious in design); an app that uses AI and pictures to calculate carbs on the plate (Snapcarbs); a connected pill bottle top (Vigicap); a coin-sized activity sensor that can be carried in a pocket (Vigifit); and a wireless body composition scale (Vigiscale).

Dianax

In a small booth at the edge of the exhibit hall, Dianax highlighted its “lab on a chip” technology – a disposable test cartridge that inserts into a connector and can be plugged into a smartphone to reportedly provide fast and easy lab results. The company is currently developing this technology to measure diabetes-relevant parameters such as A1c, C-reactive protein, and hemoglobin/ferritin (important for the monitoring of CKD) at the point of care. With its promise of fast results and anywhere use, we think the Dianax platform could be great for use at-home or in under-resourced areas where it is difficult for patients to reach a clinic for screening/checkups. The project is currently funded by a grant from the EU’s Horizon 2020 initiative, and according to Dianax’s website, a clinical trial of the technology is “ready to start” at the San Raffaele Hospital in Milan.

Glooko

Glooko’s welcoming booth demoed the DreaMed Advisor Pro software running on the web-based Population Tracker – as covered above, the CE-Marked clinical decision support software optimizes pump settings, giving HCPs specific pump basal, insulin:carb, and correction factor adjustment recommendations based on CGM data. The software is also under FDA review. The Advisor Pro user experience takes place within Glooko’s well-designed web-based Population Tracker (see picture below), and DreaMed had a separate booth looking for signups from early adopter clinics. We learned from Glooko that pump and CGM data are actually sent out to DreaMed, analytics are run by DreaMed, and then the recommendation are sent back to Glooko and displayed on the Population Tracker. Once a clinician approves the recommendations, he/she can click “Approve and Share,” which relays the pump settings changes to a patient’s Glooko mobile app. The Glooko team told us over 20 patients are now enrolled in the Helmsley Charitable Trust-funded multicenter study – per the post on ClinicalTrials.gov, the n=112 study is expected to wrap up by this December.

GlucoMe

The GlucoMe booth presented its digital diabetes platform, consisting of a connected BGM, patient-facing app, and provider-facing Digital Diabetes Clinic (DDC). GlucoMe’s BGM has already received a CE mark and the company is working to commercialize in Israel, India, Europe, and Latin America. GlucoMe is finalizing its clinical trial for FDA clearance of the BGM and expects to launch the app and DDC in the US ahead of the device in 3Q18. In a call with EVP John Erickson, we learned that the company expects a 90-120-day FDA clearance, though obviously the bar for BGM accuracy has risen at FDA. The BGM is unique in that it uses patented technology to transmit readings to the app via audio waves, independent of Bluetooth or WiFi (is this more or less susceptible to interference?). According to the booth representative, GlucoMe’s BGM has met the latest ISO accuracy requirements. While the app can only stream GlucoMe’s BGM data, there are plans to eventually integrate with Apple Health Kit and other wearables. The DDC reportedly integrates with EMRs, thereby streaming data from multiple sources, and can also serve as a telemedicine platform. GlucoMe is also boldly developing an insulin pen monitor that will be compatible with any insulin pen, as per the company website. It is still under development and is expected to launch in 2019.

Insulclock

Insulclock has a CE-marked insulin pen cap that tracks insulin dose, timing of dose, what type of insulin has been administered, and temperature. A rep tried to demo the device but unfortunately couldn’t pair it to the app (Google Play; App Store). He also couldn’t divulge the mechanism of dose capture, but it seemed to us to be accelerometer (motion)-based. The pen cap costs €249 and reportedly lasts an impressive five years. A single charge through the micro-USB port lasts three days, and it takes ~1.5 hours to fill the battery. The device will be available for Lilly’s Kwikpen on March 26^th, Novo Nordisk’s Flextouch on April 9, Sanofi’s Solostar on April 23, and Novo Nordisk’s Flexpen on May 7 – the rep indicated that launches will begin in Spain, followed by other EU countries. The app can pull in glucose data from Apple Health and Google Fit, but conversations with BGM companies for direct integration are ongoing. The rep was excited about an Emory study, PI’d by Dr. Guillermo Umpierrez, of Insulclock in type 2 diabetes: An n=80, 24-week crossover trial with a primary outcome of insulin injection irregularities. Secondary outcomes are related to satisfaction, quality of life, change in A1c, and hypoglycemia. In the intervention arm, participants will use the Insulclock and receive daily information on their smartphone on insulin administration (time and dosing) as well as reminders in the event of missing doses, while participants in the control arm will use Insulclock without feedback; they will then switch over at week 12. We are excited to see results from this trial either in December 2018 or December 2019 (unclear based on projected primary or overall completion dates on CT.gov) which could make a compelling case for reimbursement.

Insulet

In its first European exhibit hall booth, Insulet reps shared tremendous excitement to take over European Omnipod distribution from Ypsomed on July 1. (Ypsomed did advertise the Omnipod on its own booth wall, though its in-house YpsoPump was definitely the focus in booth demos.) Insulet reps emphasized the desire to provide uninterrupted care for Omnipod’s 50,000+ OUS customers. The biggest question from attendees was OUS timing on the new Dash PDM, but there is none to report at this time – the much-improved touchscreen, Bluetooth-enabled controller was submitted to FDA earlier this year, with clearance expected in 2H18 followed by a “limited market release.” Presumably an OUS launch could follow in 2019 (our speculation)…

Insulin Algorithms

Mellitus Health’s Insulin Algorithms exhibited its insulin dose clinical decision support software, which has already received CE marking and FDA clearance. Through the system, BGM readings are sent to a provider-facing dashboard, which generates insulin regimen recommendations “in 15 seconds.” The healthcare provider must then relay any changes to patients. Insulin Algorithms works with “nearly all glucometers” as per the company website and lists several partners, including Abbott, Roche, Ascensia, and Agamatrix. The booth displayed a poster demonstrating that the software resulted in an impressive 1.9% A1c reduction (baseline: 10.0%) at 90-days (n=11). For those who remained in the study for six months (n=17), an A1c reduction of 2.4% points (baseline: 10.0%) was reported by the study’s end. We’ll have to see if Insulin Algorithms can scale effectively and integrate with provider workflow – since providers have to review every recommendation and personally inform the patients of alterations, efficiency will be key to follow (similar to DreaMed’s Advisor Pro). Still, the study results are quite impressive, assuming the algorithm avoids hypoglycemia with this profound decrease in A1c. The booth representative shared that the software is available in 30 “countries and clinics” in Europe and the US. Depending on the clinic and number of patients, the software is either priced at a flat annual rate or by the number of users.

J&J – OneTouch

Apart from the booth reps’ name tags, the OneTouch booth did not have any J&J marketing – at least from what we could tell). The reps themselves weren’t OneTouch employees, and so couldn’t comment on a possible sale of the business despite reporting that many attendees had inquired about it. The booth did highlight the blue (low), green (in-range), and red (high) color indicators of blood glucose values on the OneTouch Verio Flex Bluetooth-enabled BGM. Conference-goers’ sorting ability and reaction timing were assessed in a game where a glucose value would fall from the top of the screen and they’d have to sort it into high, low, or in-range depending on the magnitude. In the second phase of the game, the numbers fell faster, but they were haloed by the color that corresponded to their range. To OneTouch’s point, this made it much easier to mentally categorize the value as in-, above-, or below-range. Animas closed in October, and following ATTD, J&J received a binding offer from Platinum Equity to buy the business for $2.1 billion.

Lilly

The wallpaper was the highlight of Lilly’s exhibit hall booth, showing a timeline of the company’s diabetes efforts, from the 1876 founding to the 2016 CV indication for SGLT-2 inhibitor Jardiance (empagliflozin). Reps also pointed to Basaglar’s US launch in December 2016 as a major recent milestone for Lilly. Indeed, Basaglar (biosimilar insulin glargine) is the first-to-market biosimilar insulin, and has posted remarkably strong sales so far. There was no mention throughout the booth of Lilly’s “Connected Diabetes Ecosystem,” which includes a connected pen and AID system (Dexcom CGM + in-house pump + hybrid closed loop algorithm acquired from Class AP in Montreal).

Medtronic

Medtronic’s large booth was the first visible in the convention center, highlighting Unomedical’s new Mio Advance infusion set (see below), the Guardian Connect standalone mobile CGM, and the MiniMed 640G. No MiniMed 670G was on display, despite a hope in 3Q17 to launch outside the US before the end of April. We enjoyed taking a time-in-range quiz using a Nintendo Wii balance board – great to see Medtronic educating attendees on this topic.

Metronom

Stealth CGM startup Metronom finally made its public debut in the exhibit hall, sharing plans to submit a CE Mark in 2Q19 for its 14-day wear, optical-based, factory calibrated CGM. The sensor technology includes direct oxygen measurement (which can monitor sensor reliability and prompt for a “smart” calibration when needed); dedicated sensors for hypoglycemia, euglycemia, and hyperglycemia; an insertion that is more like a lancet (applicator device like FreeStyle Libre); and a durable transmitter that sends data via Bluetooth to phone and watch apps (it can already go direct-to-Apple Watch, according to the company). Notably, the plan is to manufacture the sensor like a test strip (“reel-to-reel”), enabling lower expected cost of goods and expected EU pricing on par with FreeStyle Libre (second picture below). The first-in-human feasibility data (hand assembled sensors) demonstrated a 9.0% MARD and 94% of points within 20/20 (n=1,641 paired points, range of 50-300 mg/dl) in 20 people with diabetes (n=10 T1D, n=10 T2D). The study used retrospective calibration and obviously was not making sensors at scale, so upcoming studies will need to prove accuracy and reliability on a bigger scale. The sensor also has a unique adhesive that moves with the body. More in-human studies are expected this year in advance of a 1Q19 EU pivotal study. The company definitely plans to secure a commercial partner, and assuming these results and product features hold, we’d have to imagine many are interested. A second-gen concept (prototype) version that is fully disposable and much slimmer on the body was shown on a plasma screen– see the third picture below, which is not final and may change. We first covered Metronom Health in July 2014 – when it raised $4.8 million – though the company has been very quiet up until now. The company was incorporated in 2009, meaning nearly ten-years of work have gone into the product. We were impressed with the team at ATTD, though the path to scaling any CGM is always challenging and winding – can Metronom get everything in place over the next year? Who are the likeliest commercial partners?

MyMedBot

MyMedBot is a new tool for remote monitoring of people with diabetes that is currently in a closed, 20-30-patient prototype beta testing stage. Founder and CEO Jacob Arnould, who was inspired to start MyMedBot after two close calls with severe hyper- and hypoglycemia, noted that current remote monitoring solutions are limited in scope and not very easy to set up. With MyMedBot, he and his team are creating an app that integrates with CGM to send automated and manual alerts so that anyone can easily follow or receive notifications from a person with diabetes. Perhaps most importantly, MyMedBot shares information about a person’s location and provides step-by-step instructions on how to help. We imagine this system would be easiest to use if “followers” don’t have to download another app themselves to receive alerts, and we hope this product might eventually offer more peace of mind to people with insulin- or SFU-dependent diabetes (though CGM will obviously be necessary for automated alerts).

Novo Nordisk

One corner of Novo Nordisk’s booth was dedicated to the company’s digital health department, now two-years-old. An “idea box” was set up so that conference attendees could share suggestions for what Novo Nordisk might do in digital health to better support providers/patients – we note that there’s a big need for this sort of input, given that only 43% of HCPs find pharma’s digital support tools useful. ATTD was the first-time debut of the “idea box,” and we hope it sparks even more momentum in Novo Nordisk’s digital health department. Reps discussed the Glooko-partnered Cornerstones4Care (C4C) app, which offers patients personalized diabetes support, automated tracking of blood sugar and exercise, trend recognition, reminders, food/medication databases, and educational information on diet/exercise. C4C is available for free download on the Apple Store and Google Play, offering a fairly similar experience to Glooko. Reps also discussed the connected pen pilot in Sweden: The NovoPen 5 Plus was launched at limited volume to 10 Swedish clinics participating in the trial, and it stores three months of data at a time that patients can discuss with their HCP for individualized advice on diabetes management. Great to hear Novo Nordisk being more public on this front!

Fiasp dominated the majority of the booth. Bright messaging (“from the first bite”) and graphs highlighted faster onset/offset with the next-generation, faster-acting mealtime insulin. Fiasp made waves at this year’s ATTD as the subject of several oral presentations (one-year Onset 1 data, Onset 5 data in pumps, etc.), and the product was launched earlier this month in US pharmacies at parity pricing to NovoLog.

Roche

At the Roche booth, we learned of the company’s plans to eventually merge all components of its digital ecosystem with a smartphone app, currently available for limited download through Roche’s BETAtogether website. The app is still in its earliest development stage, connecting only to Roche’s pumps and displaying basic metrics like battery status and basal rate. The next step will be to add in remote control functions on the app, including bolus advice and basal settings. Once these functions have been added, the app will launch to a greater market. Eventually, Senseonics CGM data will also stream to the app. Booth representatives also noted that Roche’s Solo Patch Pump is undergoing its last clinical trial and will launch in certain EU pilot countries by the end of 2018 – one representative expected an initial launch as early as this Summer or Fall. The timing feels quite ambitious, given how long this has been sitting and that (news to us) it’s still in a clinical trial. The patch pump will initially be controlled with a separate PDM, which the representatives emphasized as being a significant improvement over the previous (clunky) version in both response time and display. Eventually, the patch pump will also be controlled via the app directly on users’ smartphones. Smartphone control would be a huge win for Roche – the Dana pump is the only option currently on the market with this feature, although Ypsomed reportedly is close behind. Booth representatives anticipated a US Solo launch at least two years following the complete EU launch.

Senseonics

At the Senseonics booth, reps ball-parked that there are now >2,000 total Senseonics users, with ~1,500 in Germany alone. While the 180-day Eversense XL has now rolled out in the UK, it won’t be until April that it enters the German marketplace (presumably waiting for the current 90-day lot to run out). We’re not sure about timing for other markets. Reps were unable to comment on the FDA process, nor an n=300 French reimbursement study, but did indicate that enthusiasm and curiosity about the sensor remained high from booth visitors.

Sooil

The Sooil booth displayed the company’s new Dana U pump, currently under development. The Dana U boasts a full color touch screen controller (it can also be controlled via smartphone app) and uses a normal AAA battery – an improvement from the current pump, which operates via a special AA battery. A booth representative expected a clinical trial for the Dana U to possibly start by the end of 2018. The company is also investigating integration with a cloud-based system for Dana U. The current Dana pump is available in a remarkable 66 countries across Europe and Asia. The pump can be directly controlled via an Android mobile app, with a CE mark for iOS devices likely to be received in one to two months, according to the representative. Sooil hopes to get FDA clearance in the future, but the representative believes submission is still one to two years out. Sooil’s largest market is China, in which the Dana is the second most utilized pump (presumably Medtronic is the leader). The company is currently seeking out distribution partners in Canada and Japan to determine whether to pursue regulatory approval.

Theranova

At the sparse Theranova booth, we learned that the company seeks to raise $1.2 million to complete a next-gen closed loop prototype (with sub-cutaneous sensing and use of Roche’s Diaport for proof-of-concept), manufacturing, and acute preclinical studies. A rep told us they have already approached JDRF, NIH, and Helmsley Charitable Trust for funding, and Montpellier’s Dr. Eric Renard concerning the closed loop study program. Eventually, the system will consist of IP glucose sensing (see data from April 2017) and IP insulin delivery. A handout suggests that product development is expected to take 12-24 months, and a CE mark and FDA 510(k) clearance for IP insulin delivery will be pursued in parallel. The company is not only developing an IP-IP closed loop system, but also an IP islet encapsulation system (see picture below).

Unomedical (Convatec)

Unomedical proudly showed commercial versions of the two products we first learned about at ATTD 2017 – the Mio Advance all-in-one, hidden-needle, fully disposable inserter and the Lantern catheter (package as part of “Inset II”). Mio Advance launched here with distribution partner Medtronic (see the YouTube intro here), and it’s currently available in a limited launch in the UK, Italy and the Netherlands. Canada, Hong Kong and certain Europe/Middle East/Africa launches are expected by end of April, and availability in other countries (not specified) is expected later in 2018. The rep told us it’s been the “best feedback ever” about an infusion set, a major win for Unomedical and certainly strong competition to BD’s FlowSmart set. The initial Mio Advance launch with Medtronic does not appear to be an exclusive partnership (like BD), though Unomedical has not developed a version for Tandem’s t:lock at this point. However, the set’s website does indicate a luer lock version is available, meaning Roche pumpers could theoretically use it. Regarding Lantern, the catheter with side-cut slits for additional insulin flow, the team remains very excited – the pictures and branding looked great, and a microscope with a screen allowed attendees to view it up close (see below). As we covered last year, Lantern has been designed to allow insulin to flow out of many additional side-cut slits, even when occlusion/kinking  occurs. The positioning of the slits is based on extensive studies and analyses to provide an optimal solution for the functionality of the concept. Lantern’s launch timing depends on what product claims Unomedical goes for – the team said it could possibly launch this year without a product claim, or it might wait to run studies and build more clinical evidence and claims for the set. The ATTD 2017 update called for a Lantern launch in 3Q17, so it’s running at least a couple quarters behind the initial expectation.

Ypsomed

An Ypsomed representative shared that the bolus calculator for the YpsoPump will be available on the MyLife smartphone app in May or June. Unfortunately, representatives were unable to comment on the timing for smartphone control of the YpsoPump, last slated for a 2019 launch, nor did they have any updates regarding Ypsomed’s plans for its patch pump YpsoPod or its participation in a closed loop system. During Ypsomed’s F1H18 call, management noted the company’s plans to launch the YpsoPod in late 2020 to early 2021 and conduct a closed loop pivotal trial with the YpsoPump in 2019. Per a press release in January, the MyLife app is expected to be available in 16 European countries by the end of April.

 

-- by Adam Brown, Ann Carracher, Abigail Dove, Brian Levine, Payal Marathe, Maeve Serino, and Kelly Close