June 12-16, 2020; Virtual; Day #4 Highlights – Draft

Diabetes Technology Highlights

1. Real-World Data from Control-IQ: +2.4 Hours/Day TIR, 96% Time in Closed Loop in 1,649 Early Adopters; Improvements for Both Type 1s and Type 2s

Tandem presented two posters featuring very positive real-world data from early adopters of Control-IQ. Control-IQ was cleared in December 2019 and officially launched in January 2020. The data presented in both posters came from Tandem users who had begun using Control-IQ before March 11, 2020. As of April, Tandem shared that “more than 30,000” t:slim X2 users had updated their pumps to the hybrid closed loop algorithm. See below for a summary of both posters and a comparison to the pivotal data.

• Through the first 30-days of Control-IQ use, Time in Range was increased by 2.4 hours/day (compared to pre-Control-IQ data) and users spent a remarkable 96% of time in closed loop (95-LB). This data set included participants with at least 30 days of pre- and post-Control-IQ data in t:connect and included a total of 1,659 subjects. The Time in Range improvement was driven by a 9.5% reduction in time >180 mg/dl (-2.3 hours/day). The reduction in time <70 mg/dl was low both pre- and post-Control-IQ (1.2% before vs. 1.1% after). This result is unsurprising as most users will likely on Tandem’s predictive low glucose suspend algorithm, Basal-IQ, before going to Control-IQ. Mean glucose fell from 161 mg/dl to 148 mg/dl and GMI fell from 7.2% to 6.9% before and after Control-IQ.

• Control-IQ significantly improved glycemic outcomes for both type 1 and type 2 users (126-LB). This second poster looked at 2,896 participants with type 1 and 144 participants with type 2 diabetes who had at least 14 days of pre- and post-Control-IQ data in t:connect. The data are summarized in the table below and both groups spent 96% of time in closed loop. Time in Range was improved by 2.1 hours/day in the type 1 subgroup, compared to a 1.4 hour/day improvement in the type 2 subgroup, though the type 2 group had a higher baseline. After two weeks on Control-IQ, participants spent an incredible 77%-79% of Time in Range! Notably, total daily dose of insulin was increased in both groups, with the type 2 group seeing a sizeable 12% increase (73 U vs. 82 U).

• Improvements from Control-IQ’s early adopter real-world data and the US pivotal trial are comparable, with real-world users spending even more time in closed loop (96% vs. 92%; ~1 hour/day). In the US pivotal, Time in Range was improved by +2.6 hours/day (59% to 71%); however, given the much higher baseline in the real-world users, the +2.4 hours/day improvement from Control-IQ in the real-world may be even more impressive (68% to 78%). In both trials, the vast majority of the Time in Range improvement came from reductions in hyperglycemia and presented within the first 30 days. Improvements in A1c/GMI and mean glucose were identical (-0.3% and -13 mg/dl, respectively), though from lower baselines in the real-world user group. It’s worth noting that these were early adopters of Control-IQ and likely are not representative of general t:slim X2 users and are certainly not representative of the general type 1 population; in contrast, the Control-IQ pivotal was notable for its broad inclusion criteria (no entry restrictions on A1c, severe hypo or DKA, or device experience). Finally, while the real-world results compare pre- and post-Control-IQ data (i.e., single-arm), the pivotal study randomized users to SAP vs. Control-IQ (i.e., double-arm).

2. Dexcom G6 With Urgent Low Soon Alerts Reduces Rebound Hyperglycemia Events by 7% After <70 mg/dl Event, 33% After <54 mg/dl Event vs. Dexcom G5

Dexcom’s Dr. Giada Acciaroli presented real-world data from 24,518 Dexcom users who transitioned from Dexcom G5 to Dexcom G6 (with urgent low soon alerts) in 2018. Results showed significant reductions in rebound hyperglycemia events and duration with Dexcom G6 users who had their predictive low glucose alerts turned on. As a reminder, G6’s “Urgent Low Soon” alert comes 20 minutes ahead of a predicted <55 mg/dl event. Rebound hyperglycemia was defined as glucose levels >180 mg/dl occurring within 2 hours of a hypoglycemic event (glucose value <70 mg/dl or <55 mg/dl). Following a hypoglycemic event <70 mg/dl, the number of rebound hyperglycemia events per week was reduced from 1.83/week to 1.7/week (p<0.001). Additionally, mean duration of these events was reduced from 214 minutes to 197 minutes (-8%; p<0.001). Following hypoglycemic events <55 mg/dl, the number of rebound hyperglycemia events per week was reduced by 33% (from 0.78/week to 0.52/week; p<0.001) and duration was reduced by 22% (from 219 min to 171 min; p<0.001).

• Dr. Acciaroli also presented real-world Dexcom data demonstrating the correlation between rebound hyperglycemia events and glucose variability. Looking at the quartiles of Dexcom users with lowest glucose variability (%CV<31.2%) and highest glucose variability (%CV>39.1%), the unstable cohort saw 7.4x more rebound hyperglycemia events per week, 0.41 events vs. 3.03 events/week (p<0.001). This translates to a difference of one event every ~17 days in the low variability quartile vs. one event every ~2.3 days in the high variability quartile.

3. Tandem’s Basal-IQ (Predictive Low Glucose Suspend) Significantly Reduces Self-Reported Severe Hypo Paramedic Visits (-45%), ER Visits (-77%), and Hospital Admissions (-75%)

Ms. Molly McElwee-Malloy (Tandem) presented strong real-world data on reductions in severe hypoglycemia related paramedic visits, ER visits, and hospital admissions with Tandem’s predictive low glucose suspend Basal-IQ algorithm. Across all three types of adverse events, the biggest improvements were seen in type 1s who switched from MDI to Basal-IQ. The study surveyed 665 type 1s who had recently started using t:slim X2 with Basal-IQ and received a $20 gift card for their participation. Participants self-reported severe hypo-related adverse events at baseline and after six months on Basal-IQ. Participants had a mean age of 37, 15% were on MDI at baseline, and 91% used CGM at baseline.

• The percentage of participants reporting hospital admissions related to severe hypoglycemia in the last six months was reduced from 3.7% (24/655 participants) at baseline to 0.9% (6/655 participants) with Basal-IQ. The 95 participants switching from MDI saw a dramatic reduction: at baseline, 10 participants experienced a severe hypo hospitalization in the last six months, compared to just 2 during six months of Basal-IQ.

• The percentage of participants reporting ER visits related to severe hypoglycemia in the last six months was reduced from 5.9% (39/655 participants) at baseline to 1.4% (9/655 participants) with Basal-IQ. Once again, the 95 participants switching from MDI saw the biggest improvement: at baseline, 14 participants experienced a severe hypo ER visit in the last six months, compared to just 4 during six months of Basal-IQ.

• Similarly, the percentage of participants reporting paramedic visits related to severe hypoglycemia in the last six months was reduced from 5.3% (35/655 participants) at baseline to 2.9% (19/655 participants) with Basal-IQ. The 95 participants switching from MDI saw the biggest improvement: at baseline, 15 participants experienced a severe hypo paramedic visit in the last six months, compared to just 6 during six months of Basal-IQ. Notably, Ms. McElwee-Malloy also shared that ~5% of all EMS calls nationally are related to hypoglycemic events. Given the very high cost of severe hypo adverse events, we loved seeing these results and would be interested in seeing a longer-term and broader cost-effectiveness analysis of Basal-IQ (and Control-IQ).

4. One Drop to Launch Long-Term (1-6 Month) Outcomes Forecasts For 30-day Average Glucose, Blood Pressure, and Weight “Within the Year”; Overnight Hypo Prediction Model Achieves AUC of 0.82 for CGM Users

This morning, One Drop announced plans to launch long-term outcomes forecasts for “diabetes-related biomarkers” and overnight hypoglycemia predictions for CGM users. The prediction capabilities are expected to launch “within the year” and are part of One Drop’s efforts to shift health management from “reactive to prospective.” The predictions for CGM users will be based on real-time CGM data – the regulatory classification for this “depends on a bunch of things,” so we’d imagine the timeline could change quite a bit. One Drop also told us that the long-term outcomes forecasts may be presented directly to users, but the primary use would be to “provide personalized self-care guidance.”

• One Drop’s supervised learning models for predicting blood pressure, weight, and 30-day average glucose were significantly more accurate than a “naïve persistence” model (assuming no change over time) on all prediction horizons (38-LB). The study included data from ~55,000 One Drop app users and generated over 200,000 test-set predictions across blood pressure, weight, and average glucose. Root mean square error (RMSE) for systolic blood pressure was 9.4 mmHg on a 1-2 month prediction horizon (~17% better than persistence model), rising to 11.4 mmHg on a 4-6 month prediction horizon (14% better than persistence). Predicted weight RMSE was 2.1 kg on a 1-2 month horizon (6% better than persistence) and 3.9 kg on a 4-6 month horizon (7% better than persistence). RMSE for 30-day average glucose in BGM users was 34 mg/dl on a 1-2 month horizon and 44 mg/dl on a 4-6 month horizon (22% and 18% better than persistence, respectively. Predictions for CGM users were more accurate: RMSE was 14 mg/dl on a 1-2 month horizon (26% better than persistence) and 19 mg/dl (13% better than persistence).

• Another poster showed One Drop’s model for predicting overnight hypoglycemia (<70 mg/dl) in CGM users achieved an AUC of 0.82 (14-LB). The machine learning-based model was trained on ~360,000 nights of data and tested on ~200,000 nights of data from “over 3,000” One Drop users with CGM. 86% of users in the dataset had type 1 or LADA, 8% had type 2, and 6% were unreported. The model achieved an AUC of 0.82 and appeared well-calibrated (see table below): in users with a predicted probability of hypoglycemia of 90%-100%, the actual frequency of overnight hypoglycemia was 97.5%. One Drop identified certain combinations of glucose variability, activity, food, and heart rate data that drove better predictions – these combinations were available in ~30% of the total dataset and these “high-confidence predictions” achieved an AUC of 0.87.

5. Analysis Estimates ~$300 Million in Annual Cost Savings if CGM Were Given to All Type 1 Medicaid Beneficiaries; $1.15 Billion in Reduced Costs vs. $850 Million to Cover Dexcom G6 for All Type 1 Beneficiaries

Mr. Michael Minshall (Certara Evidence & Access) presented a budget impact analysis estimating ~$300 million in net annual cost savings if CGM were given to all type 1 Medicaid beneficiaries. The analysis calculated ~$1.15 billion in total reduced costs with real-time CGM, compared to ~$850 million to cover Dexcom G6 (in lieu of SMBG) for all ~600,000 Medicaid beneficiaries with type 1 diabetes. A walkthrough for these calculations is provided in the bullets below and a summary of analysis’ findings are in the table below.

• Mr. Minshall estimated a total of 593,378 Medicaid beneficiaries with type 1 in 2020. This came from ~72 million Medicaid and CHIP enrollees in 2019, multiplied by 13.9%, the reported prevalence of diabetes in the Medicaid population. Of those ~10 million Medicaid beneficiaries with diabetes, Mr. Minshall estimated ~585,000 with type 1 based on the prevalence of type 1 vs. type 2 diabetes in the general US population. Lastly, Mr. Minshall added on ~9,000 new type 1s in the Medicaid population, in line with historical trends.

• Mr. Minshall estimated $396-738 million in cost savings related to A1c reductions from CGM vs. SMBG. Based on data from the 2017 DIaMonD trial (Dexcom G4 vs. SMBG in type 1 MDI adults), Mr. Minshall assumed CGM could deliver a 0.6% A1c reduction vs. SMBG. Mr. Minshall then referred to two studies estimating annual savings from reductions in A1c. One study (Gilmer et al., 2005) estimated $1,111 in savings from a 1% A1c reduction, while another (Wagner et al, 2001) estimated $2,073 in savings for the same A1c reduction. These cost savings, multiplied by 0.6 (from the 0.6% A1c reduction with CGM), formed the low and high ends of ranges used in Mr. Minshall’s cost analysis.

• Mr. Minshall estimated $210 million in savings from reduced severe hypo hospitalizations and $207 million from reduced DKA hospitalizations. The estimated reductions in severe hypoglycemia and DKA-related hospitalizations came from the RESCUE study in Belgium, which found 73% reductions in severe hypoglycemia hospitalizations and 80% reductions in DKA hospitalizations after real-time CGM was reimbursed for type 1s. Notably, Dr. Irl Hirsch cited similar statistics in his talk on Saturday where he calculated a potential $4.6 billion in potential cost savings for the entire US around DKA-related hospitalizations. The cost per severe hypo hospitalization was estimated at $4,068 (Liu et al., 2018) and the cost per DKA hospitalization was estimated at $9,733 (Tieder et al., 2013). Mr. Minshall noted that both of these numbers were on the more conservative side of estimates.

• Lastly, according to Mr. Minshall, moving all type 1 Medicaid beneficiaries from SMBG to real-time CGM would add ~$849 million in added annual cost. These calculations estimated total SMBG cost at $1,091/year per user ($0.39/test strip, $0.04/lancet, 7 fingersticks/day). Total cost of Dexcom G5/G6 were based on CMS’ Fee Schedule for US state Medicaid plans for 4 transmitters and 37 sensors. 

• Limitations of this budget impact analysis include indirect costs associated with diabetes care and treatment. Mr. Minshall was careful to note the limitations of this analysis stating they only investigated the direct costs associated with A1c and hypoglycemia or diabetic ketoacidosis and therefore could be missing hidden costs. Furthermore, this budget impact analysis did not investigate indirect benefits of CGM such as increased productivity and quality of life metrics that could be important in future assessments.

6. Flash CGM Scanning Frequency Indicates that Time Until Performing a Scan After Dropping <54 mg/dl Might be Strongest Predictor for Impaired Awareness Assessment

Dr. Othmar Moser (Medical University of Graz) presented some of the first data investigating whether type 1 patients with impaired awareness of hypoglycemia and flash glucose monitoring demonstrated different “scan” behavior compared to those with regular awareness of hypoglycemia. Participants (n=92; baseline A1c: 7.3%) who had used flash CGM for at least three months along with those with Gold-, Clarke-, and Pedersen-Bjergaard scale scores indicating impaired awareness were included. Notably, the distribution of participants with normal and impaired awareness of hypoglycemia varied by scale used (see table below). Using Pederson-Bjergaard scores, the split of participants between impaired awareness and non-impaired awareness was exactly 50/50. 

• GOLD Scale: When comparing data on participants classified via the GOLD Scale (n=18 impaired; n=74 non-impaired), significant differences were observed in scan time for those with level 1 hypoglycemia (54-69 mg/dl) and nighttime level 2 hypoglycemia (<54 mg/dl). Participants with impaired awareness took 78 minutes to perform a scan after reaching a hypoglycemia compared to 63 minutes for those with impaired awareness for daytime level 1 hypoglycemia. Similarly, those with impaired awareness took 140 minutes to make a scan relative to 96 minutes.

• Clarke Scale: No statistical differences were seen for any hypoglycemia levels, night or day.

• Pedersen-Bjergaard Scale: Statistical differences (n=46 impaired; n=46 non-impaired) were observed for level 1 hypoglycemia, nighttime level 1 hypoglycemia, and nighttime level 2 hypoglycemia. Participants with impaired awareness respectively took 76 minutes, 132 minutes, and 134 minutes compared to 54, 89, and 80 minutes for those with regular awareness.

• Receiver operating characteristic (ROC) curve analysis for the time until performing a scan after reaching level 2 nocturnal hypoglycemia was done and resulted in an area under the curve of 0.79 (p<0.0001) along with a sensitivity and specificity of 73% each. While technical explanations were not provided, Dr. Moser mentioned that if an episode of level 2 hypoglycemia (<54 mg/dl) occurs at night and a patient performed a scan after 135 minutes, then this was sufficient to diagnose the individual with impaired awareness of hypoglycemia.

7. DPP + Three Whole-Population Interventions Modeled to Reduce 10-Year T2D Incidence by 17% at Cost of ~$68k/case prevented; Neat Tool Helps Policymakers Determine Prevention Path

RTI International’s Mr. Simon Neuwahl presented a simulation modeling analysis indicating that a combination of risk-based (e.g., DPP) and three whole population-based interventions (e.g., soda tax, worksite health promotion, and bike lanes) will be necessary to reduce US type 2 diabetes incidence by 17% within the next 10 years. The interventions are estimated to come with a price tag of ~$500/person – $164 billion overall – and appear to fall short of the CDC’s target of a 21% incidence reduction by 2025. For context, 1.4 million people were diagnosed with type 2 diabetes in the US in 2018, so the cocktail of interventions proposed by Mr. Neuwahl and co. would prevent ~2.4 million cases for the country at a cost of ~$68,000 per prevented case.

• Regarding methodology, the authors used the CDC/RTI Diabetes Cost-Effectiveness Model to estimate the costs and efficacy of the National DPP and the three whole-population interventions. From these estimates, they mapped the cost of an intervention combination against the efficacy of the intervention(s) in reducing new case of type 2 diabetes, creating a useful tool for local, state, and national prevention work. According to Mr. Neuwahl, the chart of cost per person vs. percentage of diabetes cases prevented is an incredibly useful tool for determining the lowest cost intervention at all levels of 10-year diabetes prevention goals. Researchers and public health workers can start with the prevention goal they aim to achieve and find the intervention combinations that would roughly achieve that goal; alternatively, they can approximate what prevention goal is achievable within a given budget. Since the y-axis presents cost per person (not per at-risk person), the tool can be scaled for local, state or national level goals.

• Mr. Neuwahl emphasized that these are estimates and more research is needed to investigate the cost and effectiveness of whole population-based diabetes prevention interventions. There is limited research on the effectiveness of whole population-based interventions, which hindered Dr. Neuwahl and co-researchers’ ability to predict the cost and effectiveness of whole population interventions. The main whole population-based intervention that has been study is the soda tax, which has been shown to be effective. For more on whole-population interventions, see one of our favorite talks from WCPD 2018.

• Mr. Neuwahl added that the DPP has been shown to be an effective population-specific intervention, and DPP access could be expanded by delivering the intervention virtually. However, improvements in the virtual DPP program’s engagement and long-term impacts might be needed. A recent Kaiser Permanente study shows that at 12 months, those using virtual DPP do not maintain their weight loss (while those who engaged in the in-person program do) and that only 46% of those in the virtual arm completed at least 4 of the 16 sessions.

8. Barbara Davis Center’s PANTHER Project Provides Targeted Education to Help Patients Onboard with MiniMed 670G and Control-IQ Hybrid Closed Loop Systems

The audience-favorite Dr. Laurel Messer (Barbara Davis Center) presented on the PANTHER Project: Practical Advanced THERapies for Diabetes, a program addressing concerns and barriers with automated insulin delivery (AID) adoption. Despite huge advances in AID in the last few years, Dr. Messer highlighted a variety of barriers that prevent adoption, most notably, issues with the infusion set. According to Dr. Messer, in nearly all AID trials, the number one reason patients experience hyperglycemia or DKA is because of failures with infusion sets. Beyond infusion set issues, other barriers vary by age, further complicating the problem. At a similar talk at ISPAD 2019, Dr. Messer shared data identifying the top barriers to diabetes tech use in adolescents: hassle of wearing devices all of the time (38%), dislike having devices on the body (33%), dislike how devices look on the body (29%), nervousness that the device won’t work (25%), and not wanting to spend more time managing diabetes (20%). During today’s presentation, Dr. Messer walked through some of the experiences and successes seen onboarding patients at BDC in the PANTHER project with MiniMed 670G and Control-IQ.

• MiniMed 670G: Patients (n=72) interested in the MiniMed 670G were first trained on using Manual Mode. Trainings were in-person for 2-3 hours and happened in groups of families to promote peer support. Five to seven days after this training, patients in smaller groups of families were given ~1-2 hours of Auto Mode training to reinforce conventional insulin pump and CGM use on the new system. Three follow-up phone calls in the first four weeks after training were done to assess system use, make insulin adjustments, and provide targeted re-education. Overall, patient engagement in these classes was high. Following perfect retention in the introduction class and the video conference, 92%, 81%, and 53% of participants responded to follow-up calls one, two, and three. Dr. Messer shared that a variety of changes were made during these sessions, with 75% of participants increasing their insulin: carbohydrate ratio and 44% altering active insulin time. Topics ranged from pre-meal blousing (65%), insulin correction doses (48%), and addressing system alerts such as alarms (45%).

• Control-IQ: Participants (n=107; A1c: 7.5%) underwent a different process for onboarding as individuals in this program had already downloaded Control-IQ and were ready to start using it. As a result, the BDC team decided to work with the patient to pick an ideal day for starting, scheduling a follow-up call with a RN/DCES after two weeks of starting, and download their pump data. The PANTHER team created four metrics and benchmarks to assess device success in a week-long period: (i) time using Control-IQ (>5 days per week); (ii) time using the CGM (>5 day per weeks); (iii) Time in Range (>60%); and (iv) time spent <70 mg/dl (<5%). Median follow-up time for the call was 18 days, slightly more than anticipated, but ~64% of participants (n=68) met all four benchmarks. Of the 18 of 39 patients that completed an addition second follow-up call, nine ended up meeting all four benchmarks, with mean Time in Range between calls one and two increasing a remarkable 12.5% (baseline not provided). Dr. Messer noted that these results demonstrate active engagement coupled with education can promote technology uptake and improved glycemic outcomes.

Diabetes Therapy Highlights

1. Teplizumab Follow-Up Shows Extended Efficacy: Clinical Onset Delay of Three Years Compared to Placebo, “Striking Reversal” of C-Peptide Decline 6-Months After Treatment, Dampened Autoimmune Response

The insightful Dr. Emily Sims (Indiana University, USA) unveiled very encouraging follow-up data from the landmark phase 2 teplizumab type 1 diabetes prevention trial, demonstrating sustained reductions in cumulative diabetes onset (47% vs. 16%, HR = 0.457, p=0.01) and median time to diagnosis (60 months vs. 24 months). Previously, teplizumab had been proven to delay clinical onset by only two years in high risk patients; however, these new data support a delay of as much as three years compared to placebo. Furthermore, patients who were treated with teplizumab showed a “striking reversal” in C-peptide decline (as measured by AUC) in the six months following treatment (p=0.02), after which C-Peptide AUC seemed to stabilize. While these data are very promising, Dr. Sims did point out that even in the participants with improved glucose AUC, many high-risk individuals still exhibited dysglycemia. Very interestingly, Dr. Sims closed out her presentation with the suggestion that the early efficacy followed by stabilization of beta cell function may suggest that repeated teplizumab treatment at key time points in clinical development may be able to further extend delay or even prevent diagnosis.

• To delve further into possible beta cell function improvement, Dr. Sims’s team also examined the Insulin Secretory Rate (ISR), a measure that is known to predate loss of C-Peptide AUC. Though both groups showed decreasing total ISR prior to treatment, only the placebo group continued to exhibit decline after treatment. Those in the teplizumab-treated group demonstrated a trend reversal, with increasing ISR over the first six months of treatment (p=0.004).

• Mechanistically, flow cytometry analysis of circulating immune cells (CD8+) suggests that only participants in the teplizumab treatment arm experienced large increases in C-peptide AUC, as well as markers of T cell “partial exhaustion” (TIGIT+KLRG1+). To note, partially exhausted T cells are characterized by loss of function and unresponsiveness and are considered a “beneficial prognostic indicator” in autoimmune diseases. Increased T cell exhaustion was identified at the three, six, and 18-months timepoint. In addition, immune cells that exhibited both partial exhaustion markers and increased C-Peptide production experienced significant decreases in inflammatory cytokine production compared to baseline, as measured by IFNγ and TNF-α.

• As a reminder, the study enrolled 76 participants (55 children and 21 adults) who were the relatives of patients with type 1 diabetes who did not have diabetes but were at high risk for developing type 1. All of the study participants were identified by TrialNet’s Pathway to Prevention screening program and in “Stage 2” of type 1 disease progression, meaning that they had two or more type 1 autoantibodies and abnormal blood sugar levels (nearly 100% of those in Stage 2 progress to a clinical diagnosis of type 1 in their lifetime). Participants were randomized to either a single 14-day course of intravenous teplizumab (anti-CD3 monoclonal antibody) or placebo, with follow-up consisting of OGTTs at 6-month intervals.

• Teplizumab is currently being developed by Provention Bio. Rolling BLA submission to the FDA was commenced in April 2020. Given an estimated six-month review period if Priority Review is granted (as is common with Breakthrough designated therapies), an FDA decision could be expected as soon as mid-2021.  

2. Full Phase 2 Results from Novo Nordisk’s Anti-IL-21 and Liraglutide Combination Therapy Demonstrate +48% Increase in MMTT C-Peptide Response vs. Placebo at 54 Weeks, Compelling Safety Profile

Dr. Thomas Pieber (Medical University of Graz, Austria) shared full results from the positive phase 2 trial of combination anti-IL-21 and liraglutide therapy in people with newly diagnosed type 1 diabetes. Topline results for this trial were first announced on Novo Nordisk’s 2Q19 update. Compared to placebo, participants who underwent combination therapy experienced a 48% increase in MMTT-stimulated C-peptide response (95% CI: 1.16 to 1.89, p<0.01) at 54 weeks, as well as a 32% drop in total daily insulin dose. Combination therapy also conferred significantly improved levels of C-peptide at 54 weeks compared to liraglutide alone (HR = 1.33, 95% CI: 1.04 to 1.69, p=0.02) but not compared to anti-IL-21 monotherapy (HR = 1.20, 95% CI: 0.94 to 1.53, p=0.14). Notably, this C-peptide benefit compared to placebo was no longer maintained through the 26-week observation period following end of treatment (HR = 1.59; 95% CI: 1.21 to 2.09, p=0.58). Anti-IL-21 and liraglutide also conferred an 0.4% reduction in A1c (95% CI: -0.9 to -0.1, p=0.11) and 34% reduction in severe or blood glucose-confirmed symptomatic hypoglycemic events (95% CI: 0.39 to 1.12, p=0.12) vs. placebo at Week 54, though neither were found to be statistically significant. No safety concerns were identified with combination therapy, including activation of viruses or increase in infection. Of late, some KOLs have voiced that patients are becoming increasingly concerned with immunomodulating therapies during the current COVID-19 pandemic, so we were comforted to see anti-IL-21’s clean safety profile.

• We’d be curious to see how the therapy affects patients earlier in disease progression, for example as a disease preventative treatment like Provention Bio’s teplizumab, and if long-term benefit can be maintained with multiple doses. During Novo Nordisk’s 2Q19 update, management noted that they were “engaging with regulatory authorities to evaluate next steps,” though we have yet to hear an update in recent calls.

• As a reminder, anti-IL-21 and liraglutide combination therapy is thought to utilize a complementary mode of action between (i) anti-IL-21’s ability to mediate inflammation; and (ii) liraglutide’s beta cell action against cytokine-mediated apoptosis. Together, the two are thought to “maintain immunological tolerance, allowing beta cell mass to survive, regain functionality, and eventually control glucose.”

• The phase 2 study randomized 304 patients into four arms: (i) anti-IL-21 (n=76); (ii) liraglutide (n=76); (iii) anti-IL-21 and liraglutide (n=76), and placebo (n=76). Anti-IL-21 was administered by IV every 6 weeks until week 54, while liraglutide was dosed at 1.8 mg/day subcutaneously. If patients could not tolerate 1.8 mg/day of liraglutide, the dosage was lowered to 1.2 mg/day. Insulin was given as needed.

• Looking ahead, our understanding is that a phase 3 trial for this treatment might substitute semaglutide in place of liraglutide. It appears that discussions with FDA are ongoing regarding the design of this phase 3 trial; nonetheless, we would be incredibly excited to see semaglutide investigated due to its increased efficacy as a GLP-1 when compared to liraglutide. Also of note, Novo Nordisk holds an Orphan Drug designation for this treatment in type 1 from FDA.

3. Kelly West Award Lecture: Dr. Elizabeth Selvin Reinforces the Validity and Importance of A1c in Addition to CGM, Argues Impact of Race on A1c is Minimal

Johns Hopkins epidemiologist Dr. Elizabeth Selvin was honored with the Kelly M. West Award for Outstanding Achievement in Epidemiology. Dr. Selvin delivered an outstanding lecture outlining her work on the epidemiology of A1c, which has heavily influenced ADA’s guidelines on the diagnosis or diabetes. Indeed, Dr. Selvin’s lecture was, in many ways, a defense of the epidemiological, scientific, and clinical validity of A1c as a measure of glycemic control, and her expertise on the topic was clear. Dr. Selvin directly addressed the “Beyond A1c Movement”, expressing concern that the rise of CGM has resulted in a sort of rivalry – or “false dichotomy” – between CGM-based metrics and A1c. Dr. Selvin was clear and enthusiastic in her appreciation of the value CGM offers patients and researchers. However, she also asserted that CGM and A1c measure different aspects of glycemia and neither should be suggested as a replacement for the other: We must avoid “motivating CGM with the limitations of A1c.” In our view, most on either side of A1c vs. CGM discussion would agree that both are valuable tools from a variety of perspectives, but we can also recognize that the semantics of “Beyond A1c” can appear to discount the value of A1c. She outlined the limitations of CGM: cost, poor accuracy at low glucose, within- and across-sensor variability, unclear utility in type 2, the absence of a link to long-term outcomes, and moderate concordance with lab glucose values – aiming to demonstrate that, like A1c, CGM is not perfect. Driving home this point, Dr. Selvin presented her own data from an ongoing study in type 2 (n=155) showing that two sensors (Dexcom and Abbott) on the same person often give different values – sometimes dramatically so – at the same point in time, and that mean glucose calculations are also not perfectly correlated between systems (r=0.86, RMSE=17 mg/dl).

• Dr. Selvin’s work contributed to ADA’s 2010 recommendation that A1c can be used as a diagnostic criterion for diabetes. That same year, Dr. Selvin published (NEJM) an analysis based on A1c measurements from >11,000 participants in the ARIC (Atherosclerosis Risk in Communities) study, obtained from whole blood samples that had been in storage for over a decade – meaning they also came with 15 years of follow-up data. This research demonstrated that A1c is a useful marker for identifying people at risk for future diabetes, CV disease, and all-cause death – and also a better prognosticator than fasting glucose, supporting A1c as a diagnostic test for diabetes.

• ADA’s acceptance of A1c as a diagnostic criterion was controversial, Dr. Selvin said, for a few reasons. Many were concerned about hemoglobin trait interference with assays, disruption from conditions or procedures (anemia, transfusion, pregnancy, blood loss), and the greater cost of an A1c test vs. plasma glucose. Additionally, differences in A1c among black people and other races/ethnicities are commonly cited as a limitation of A1c, leading some to call for race-specific A1c cut-points – which Dr. Selvin took particular issue with. Currently, she noted, there is no evidence for racial differences in the association between A1c and diabetes complications, nor are there racial differences in the correlation of A1c with fasting glucose or average glucose. Race differences in A1c are on the order of ~0.2% A1c points, and Dr. Selvin asserted that the hyperglycemia of diabetes makes this virtually meaningless. She also argued that genetic and racial differences are not interchangeable, meaning that conditions affecting RBC turnover, hemoglobin, A1c may be associated with but are not equivalent to race. Dr. Selvin ultimately recommended a combination of A1c and fasting glucose for diabetes diagnosis as a practical solution that allows providers to keep an eye on any discordance while also meeting ADA’s diagnostic requirements.

4. Pfizer’s Small Molecule Oral GLP-1 Candidate Delivers Impressive Dose-Dependent Effects on Weight and Glucose in Phase 1 Trial

Dr. Aditi Saxena presented highly positive phase 1 data for Pfizer’s oral GLP-1 candidate (PF-06882961), demonstrating impressive dose-dependent effects on glucose levels and body weight after one month. The trial enrolled 98 patients with type 2 who were on metformin at baseline to either placebo or one of five doses of the twice-daily oral candidate (10 mg, 15 mg, 50 mg, 70 mg, or 120 mg). In the highest 120 mg group, meaningful effects on fasting plasma glucose (-90 mg/dL from baseline), mean daily glucose (-106 mg/dL), A1c (-1.2%), and body weight (-7.9 kg) were seen. See table below for the full breakdown of results for each dose. Baseline A1c between the various cohorts ranged from 8.0% to 8.6%.

• On safety, most adverse events in were mild/moderate. 85% of trial participants reported at least one adverse event. Of 319 total adverse events in the trial, 294 were deemed mild. Of the 23 adverse events that were considered to be moderate in severity, 18 were related to treatment. The proportion of patients experiencing an adverse event increased with higher doses of the study drug, from 67% with the lowest dose to 100% with the 120 mg dose. The usual GI-related side effects with GLP-1 therapy emerged, including nausea (49%), diarrhea (25%), and vomiting (27%). Six participants on the study drug discontinued during the trial, only two of which were related to adverse events.

• Pfizer’s management has been very enthusiastic about the potential of this candidate. On Pfizer’s 1Q19 earnings call, Global President of Worldwide R&D Dr. Mikael Dolsten highlighted the “unique chemistry” of the candidate and noted that “to the best of our knowledge, this is the only true small molecule that has come this far and shown this level of promise in favorable PK/PD effects.” We’re very happy to see this enthusiasm coming from Pfizer, especially in light of a relatively disappointing launch for its Merck-partnered SGLT-2 inhibitor Steglatro.

• Taking a step back, we note that competition is shaping up to be fierce within the oral GLP-1 landscape. Novo Nordisk has paved the way with the landmark approval of Rybelsus (oral semaglutide) in September 2019 as the first oral GLP-1 option, and several promising candidates are not far behind in development. Several large diabetes manufacturers, including Lilly and AZ, have oral GLP-1 candidates in their pipelines (Novo Nordisk also has another oral GLP-1 in its pipeline as well). vTv and Pfizer round out the oral GLP-1 landscape. Our sense is that the next push in the oral GLP-1 field will be a shift to small molecule candidates (instead of larger peptide drugs like semaglutide), which might allow for cheaper manufacturing costs, better bioavailability, enhanced patient experience by eliminating fasting requirements, lower costs for patients, and potential combination pills with SGLT-2 inhibitors.

• Pfizer has already moved this candidate into phase 2, with at least one known trial expected to begin in July 2020. That trial – listed on ClinicalTrials.gov here – is using 2.5, 10, 40, 80, and 120 mg doses of the candidate, which is slightly different from the doses tested in this phase 1 study. To be sure, we’re glad to see such a wide range of doses continue to be investigated by Pfizer for this candidate. The trial will run for 16 weeks and primarily assess A1c reductions.

5. Are SGLT-2s/GLP-1s Ready for “Prime Time” in Primary CV Prevention? Drs. Mikhail Kosiborod and Darren McGuire Debate

Highly esteemed cardiologists Dr. Mikhail Kosiborod and Dr. Darren McGuire faced off in a debate on one of the most important questions facing the diabetes/cardiology communities in the wake of positive CVOT data for the SGLT-2 and GLP-1 classes: should we broaden the use of these therapies into “primary prevention” patients? Dr. Kosiborod started the session with a forceful argument in favor of this use of the two classes and debunked what he thought of as the three primary counterarguments against their use: (i) there is not enough evidence from RCTs, as most patients enrolled in these trials had established ASCVD; (ii) event rates are too low in primary prevention populations, which means that the NNT would be too high (i.e. “juice not worth the squeeze”); and (iii) using these agents more broadly would be too expensive and not cost-effective. On the first point, Dr. Kosiborod asserted that there is no sound physiological reason for why these therapies should only work in secondary prevention and not primary prevention – in fact, other effective therapies for prevention work for patients with established ASCVD and those at high risk (he pointed to statins as a good example of this). On the second point, Dr. Kosiborod argued that although NNTs would be higher in the primary prevention population, the risk is still high in these patients, and that the overall magnitude of adverse events prevented by intervening in this population would actually be greater compared to intervention in the secondary prevention population. On the third point, Dr. Kosiborod conceded that these therapies are expensive, but that a key part of cost-effectiveness is clinical effectiveness, and that there is no doubting this aspect of treatment. Moreover, with some SGLT-2s and GLP-1s set to be generic in a few years, this should make these drugs more affordable for many more patients.

• Dr. McGuire argued that the evidence for effectiveness of SGLT-2s and GLP-1s in primary prevention is not strong, and that the definition of “primary prevention” in these trials masks the higher event rates seen than in other primary prevention populations. Dr. McGuire focused on the definition of “primary prevention” and showed that rates of CV adverse events in the SGLT-2/GLP-1 CVOTs for their “primary prevention” populations were actually higher than actual rates in usual primary prevention patients. He also pointed to meta-analyses for both classes showing no significant effects of treatment in the primary prevention populations of their respective CVOTs. Dr. McGuire touched on cost as well, homing in on an example with GLP-1 Trulicity, which did show consistent and significant effects in its primary prevention population in the REWIND trial. Despite this, he noted that the absolute risk reduction seen was quite small, resulting in a large NNT of 333 patients over the trial’s length to prevent one MACE event. For a drug that costs $840/month, this results in a $3.4 million in costs to prevent one MACE event. Even if the cost was cut by 90% (which might be unlikely even with generics), Dr. McGuire pointed out that it would still amount to $300,000 to prevent one MACE event. Whether this is cost-effective would have to be determined with more sophisticated analysis, but we appreciated Dr. McGuire teasing out this illustration of what total costs may look like based off of the available data.

• Both speakers agreed that SGLT-2 inhibitors have shown robust effects in primary prevention for heart failure and kidney outcomes. There was no significant debate on this point, as the data speak for themselves regarding the profound effect of SGLT-2 treatment in reducing these outcomes.

• Moderator Dr. Julio Rosenstock closed the session by stating that he believes that “a lot of this discussion will become semantics in the future.” He emphasized that CV risk with type 2 diabetes is “all a continuum” and that even at type 2 diagnosis, patients harbor a certain amount of risk. He also reiterated his thesis on simultaneous therapy over sequential therapy – see his talk at ATTD 2020 for more on this, in which he argues that nearly all type 2 patients should be prescribed a metformin/SGLT-2 combo at diagnosis.

6. REWIND Post-Hoc Analysis Finds 17% RRR on Composite Renal Endpoint, Adding to Evidence For GLP-1 Class Effect

Dr. Jonathan Shaw presented results from a post-hoc analysis of the REWIND CVOT that suggest significant effects with dulaglutide treatment on impacting renal outcomes. On several key renal composite endpoints, dulaglutide was associated with significant improvements vs. placebo: a 17% RRR on a composite of sustained eGFR decline ≥40%, end-stage renal disease (ESRD), and all-cause death; an 18% RRR on the composite of sustained eGFR decline ≥40%, ESRD, and CV/renal death; and a 28% RRR on the composite of sustained eGFR decline ≥40%, ESRD, and renal death.

• Renal outcomes for REWIND were first presented at ADA 2019 along with the initial readout from the trial. That analysis showed that on the primary composite of new macroalbuminuria, 30% fall in eGFR, or progression to renal replacement, Trulicity conferred a significant 15% risk reduction (HR=0.85, 95% CI: 0.77-0.93, p=0.0004). This was driven primarily by reduction in new macroalbuminuria (HR=0.77, 95% CI:0.68-0.87), followed by sustained eGFR decline (HR=0.89, 95% CI:0.78-1.01, p=0.066), and slightly by reduction in renal replacement therapy (HR=0.75, 95% CI:0.39-1.44, p=0.39). Seeing as the eGFR component just barely missed out on superiority, a sensitivity analyses with more stringent guidelines (which are often used in dedicated renal trials or other CVOTs, e.g., DECLARE) was subsequently presented: If the eGFR decline threshold had been set at ≥40%, then the component would’ve reached nominal significance in favor of Trulicity (HR=0.70, 95% CI:0.57-0.85, p=0.0004), which further improved when tested at ≥50% (HR=0.56, 95% CI:0.41-0.76, p=0.0002). We note that the analysis presented here today uses this ≥40% cutoff.

• KOL consensus around renal outcomes for REWIND were semi-enthusiastic following initial presentation at ADA 2019, with some noting that the effect seemed to be driven by reductions in macroalbuminuria. Experts view this endpoint as the most prevalent but least important component in assessing renal efficacy. We imagine that reaction in light of this new analysis will be much more positive, considering that dulaglutide treatment was shown to convey significant benefits on much “harder” outcomes of eGFR decline, ESRD, and renal/CV/all-cause death. We also find it very impressive that these benefits were delivered in the comparatively “low-risk” population that REWIND enrolled. Nevertheless, the data for the GLP-1 class on renal outcomes is still a notch below the SGLT-2 class, which has shown tremendous efficacy on impacting these same outcomes.

• Looking ahead, for the strongest evidence on GLP-1s and potential renal protection, we’re waiting on results from Novo Nordisk’s FLOW trial of semaglutide in CKD. As a reminder, the FLOW trial was initiated in June 2019 and will enroll 3,160 patients with type 2 diabetes and CKD (eGFR 25-75 ml/min/1.73 m2) for up to five years. Expected completion is August 2024, and the primary endpoint is a composite of persistent eGFR decline of ≥50%, reaching ESRD, and CV or renal death. Traditional MACE endpoints will also be measure. This is a highly notable, first-ever renal outcomes trial among GLP-1s, and it’s clear that enthusiasm is high for the trial’s potential in further informing renal benefits of the GLP-1 class. We’ve sensed optimism from Novo Nordisk that more efficacious GLP-1s (such as semaglutide) may be able to compete in the future with renal outcomes data from the SGLT-2 class, along with providing the additional benefit of not losing their glucose lowering abilities in patients with a lower eGFR.

7. Exploratory 52-Week Results from AWARD-11 Trial of High-Dose Trulicity Show Sustained Effects on A1c and Weight, Consistent with 36-Week Data

A week after presenting full 36-week results at ENDO 2020, Dr. Juan Frias followed-up with exploratory 52 week results from the AWARD-11 trial. Results after 52-weeks tightly mirrored the impressive efficacy seen with higher doses of Trulicity in the 36-week data from the trial. As a reminder, Trulicity is currently approved and marketed in 0.75 and 1.5 mg once-weekly doses – in AWARD-11, Lilly hoped to show the potential of higher doses (3.0 and 4.5 mg) in helping patients achieve and maintain A1c and body weight goals. After 52 weeks of treatment, significant A1c reductions of 1.83% and 1.71% were seen with 4.5 mg and 3.0 mg doses of dulaglutide when compared to 1.5 mg (1.52% drop). A greater proportion of patients also reached an A1c goal of below 7% with the higher doses: 72% for the 4.5 mg group and 65% with the 3.0 mg group, compared to 59% for the 1.5 mg arm. Similar significant dose-dependent effects on body weight were also seen: 5.0 kg weight loss in the highest dose, 4.3 kg in the 3.0 mg group, and 3.5 kg with the current Trulicity dose. These results are essentially identical to the 36-week results – a reassuring sign that treatment effects do not wane over this longer period of time. Although, positively, on weight, a continued effect with weight loss may be occurring between 36 weeks and 52 weeks, hinting at further potential weight loss effects with longer treatment. See the table below for the full comparison of outcomes.

• Adverse event data were also consistent with those presented at 36-weeks, with a general trend toward higher rates of GI-related events in the higher dose arms. This trend is expected for higher doses of GLP-1, but we note that the overall rates were relatively well-balanced between all doses. In the 4.5 group, there were 239 nausea/diarrhea/vomiting events, compared to 229 in the 3.0 mg group and 173 in the 1.5 mg group. In terms of total treatment-emergent adverse events, there were 408 in the 4.5 mg group, 384 in the 3.0 mg group, and 380 in the 1.5 mg group.

• Mean A1c at baseline in the trial was 8.6%, which is higher than previous studies in the AWARD program. Dr. Frias explained that this design was implemented in order to more accurately depict the patient population that may benefit from treatment intensification with a higher dose of dulaglutide. Lilly is envisioning high-dose Trulicity as an intensification option for patients currently on Trulicity that may not be meeting their A1c goals and might prefer to stay on the same medication instead of adding on another diabetes medication or switching to a new therapy altogether. High dose Trulicity may also be positioned as a competitor to Novo Nordisk’s Ozempic (more on this below).

• We note that from a commercial perspective, higher dulaglutide doses could also serve as a link between current Trulicity doses and upcoming GIP/GLP-1 receptor dual agonist tirzepatide – submission is currently expected ~2022 based on the timeline for the phase 3 SURPASS program. Management has already stated that it would cannibalize Trulicity sales to make tirzepatide the new standard-of-care, assuming outstanding efficacy and ameliorated tolerability concerns are sustained in phase 3 – this is obvious from our view and very similar to the way in which Novo Nordisk sales for Ozempic are skyrocketing and Victoza sales are dropping. Lilly has stated that it views high-dose Trulicity as a treatment intensification option for patients not meeting goals on Trulicity 1.5 mg. Moreover, we also see these higher doses of Trulicity as Lilly’s response to Novo Nordisk’s once weekly Ozempic, which had shown superiority to Trulicity in the SUSTAIN 7 trial. SUSTAIN 7 had shown a 1.8% A1c drop with semaglutide compared to 1.4% for Trulicity (baseline 8.2%), making the A1c reductions seen with dulaglutide 3.0 and 4.5 mgs in AWARD-11 very comparable to that of semaglutide in SUSTAIN 7 (with both trials enrolling similar patient populations of those on background metformin therapy). Of course, Novo Nordisk is itself investigating higher doses of semaglutide, which it expects to show similar A1c and weight effects as Lilly’s tirzepatide.

8. Dr. Skyler: Combination Therapy is the Future of Immunomodulation for New-Onset Type 1; Much-Anticipated DIPIT to Start Post-Covid

Dr. Jay Skyler looked toward a future of “aggressive combination therapy” for type 1 immunomodulation, particularly in new-onset disease. He outlined the three components of the immune system – innate, adaptive, and regulatory – in addition to beta cell health as critical targets of any combo regimen. Dr. Skyler pointed to a Diabetes Care Perspective he published in 2015, which suggested a framework for such a combination regimen to tackle the complicated pathophysiology of type 1:

Excitingly, two combination trials promise to test the combo hypothesis. First, Dr. James Shapiro – known for his work on islet transplantation – is conducting a trial in new-onset type 1 that began in early March of this year at the University of Alberta, according to Health Canada (below, left). Second, Dr. Skyler highlighted that FDA has greenlit the phase 1/2 DIPIT trial (below, right), which he and Dr. Camillo Ricordi will lead from Miami and is many years in the making. DIPIT was posted to ClinicalTrials.gov in 2015, but Dr. Skyler has previously noted challenges accessing the anti-TNF and IL-2 drugs. Further, he commented in this talk that they’re now waiting for Covid-19 to wane due to concern over the immunomodulators used. DIPIT aims to enroll 42 participants with new-onset type 1, and the active comparator arm will receive all five of ATG, GCSF, IL-2, etanercept, and exenatide. The primary outcome of DIPIT is C-peptide, and the current estimated start and completion dates are December 2021 and June 2025. With these studies plus POInT, we could be seeing a tidal wave of scientific progress across the natural history of type 1 diabetes in the next few years.

• Dr. Skyler discussed teplizumab, supporting a two-infusion dosing protocol to maximize the C-peptide maintaining benefits of the treatment. This would involve one dose at stage 2 (autoimmunity + dysglycemia, but asymptomatic) and a second dose at stage 3 (symptomatic type 1), to best maintain C-peptide concentration. The previous ABATE study supports the latter timing, while the more recent phase 2 study supports the former. Remember, groundbreaking phase 2 results for the anti-CD3 therapy in those at risk of developing type 1 and with dysglycemia were presented at ADA 2019, and Provention is working to submit the therapy to FDA within 2020.

• Dr. Skyler also added beta cell replacement to the mix, telling the audience to expect an explosion of interest in the field. As he outlined, industry has already invested substantially in beta cell replacement technology, often in collaboration with academia (see our competitive landscape). Most of the time Dr. Skyler spent talking about beta cell replacement was used to outline the challenges: availability of beta cells, alloimmune response and transplant rejection, and recurrent autoimmune response against the transplanted cells. While there are many technologies focused on the latter two issues, sources of beta cells remain limited, and the field has generally been slow to progress. However, it could also bring the most definitive solutions to type 1 diabetes, and we’re thrilled to see where it goes over the next decade.

9. TEDDY Symposium Highlights A1c Change (Rather Than A1c Itself) as a Predictor of Type 1 Diabetes Development

TEDDY investigators provided an update on recent findings from this ambitious program, which aims to identify the environmental triggers for type 1 diabetes in a prospective cohort of children at high genetic risk. We were particularly intrigued by Dr. Kendra Vehik’s (University of South Florida) discussion of A1c as a predictor of type 1 diabetes onset in children. She underscored that “children are not small adults,” and that the A1c threshold for adult diabetes (6.5%) is not at all sensitive for diagnosing type 1 diabetes in people under the age of 21. To this end, one analysis showed that a single A1c measurement of >6.5% in a young person had between a 33-75% probability of indicating type 1 diabetes – in other words, this measurement was completely uninformative. In Dr. Vehik’s analysis, what predicted type 1 diabetes development in children was not an absolute A1c threshold, but instead a large change in A1c. A 10% relative change in A1c increased the risk of type 1 diabetes by 7-fold, whereas a 20% relative change increased the risk by over 20-fold. Therefore, changes in A1c (rather than A1c itself) could be a useful non-invasive diagnostic for diabetes in the pediatric and adolescent population. We found this study interesting from a beyond A1c perspective, as it reinforces that A1c thresholds are not the end-all and be-all to evaluate diabetes management. We are curious what CGM data might reveal about blood glucose in the weeks and months before the onset of type 1 diabetes symptoms.

• University of Colorado’s Dr. Marian Rewers provided valuable context for these new results with a summary of TEDDY’s major findings to date. One of TEDDY’s earliest findings was that the incidence of islet auto-antibodies (GADA, IA-2A, and IAA) peaks in the second year of life. Furthermore, there are distinct phenotypes associated with which particular antibody appears fist. IAA as the first auto-antibody is much more likely to occur before the second year of life, whereas GADA as the first auto-antibody is likely to occur anywhere between 2 and 12 years. This suggests that there are distinct “endotypes” of type 1 diabetes with a different underlying course of autoimmunity development. As for environmental risk factors, exposure to enteroviruses predicts the development of auto-antibodies, particularly via the IAA-first pathway. Turning to nutritional exposure, higher vitamin C is associated with lower risk of islet autoimmunity, as is vitamin D for people with a specific genotype.

• Dr. Qian Li (University of South Florida) presented new data identifying unique metabolomic signature preceding the first appearance of a T1-related auto-antibody. Participants’ metabolomes were profiled by mass spectrometry every three months until the first appearance of an auto-antibody. Interestingly, each first auto-antibody was preceded by a reduction in the amino acid proline, followed by a reduction in the branched-chain amino acids (leucine, isoleucine, and valine). Furthermore, unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of auto-antibodies. Interestingly, higher abundance of the neurotransmitter GABA was associated with development of the IAA auto-antibody, but not any others. Overall these results could enable earlier prediction of auto-antibody development, and better identification of people at risk for type 1 diabetes. These results also point to noticeable differences in the pathophysiology of IAA-first vs. GADA- or IA-2A-first forms of type 1 diabetes – a finding that could, down the line, offer hints at targets for primary prevention of type 1 diabetes.

• Additionally, Dr. William Hagopian (Pacific Northwest Research Institute) provided an update on the overlap between type 1 diabetes and celiac disease. These diseases have very similar pathophysiology: Both are cytotoxic T-cell mediated diseases, and the target organs (the pancreas and the small intestine) are located immediately next to each other, suggesting cross-signaling and similar exposures. Among TEDDY participants, having type 1 diabetes auto-antibodies increased the risk of developing additional celiac-associated auto-antibodies. This underscores the need for more vigilance in screening people with type 1 diabetes for celiac disease and educating patients about this increased risk of additional autoimmune conditions.

• As a reminder, TEDDY is a prospective cohort study started in 2004 that includes children at increased genetic risk of type 1 diabetes (i.e. carriers of HLA-DR and HLA-DQ risk alleles; n=7,718) and children with high-risk HLA genotypes and a first-degree relative with type 1 diabetes (n=948) across the US, Finland, Germany, and Sweden. Participants are typically enrolled as infants, and TEDDY tracks diet, illnesses, allergies, and other life experiences for the first 15 years of life. Frequent blood, urine, microbiome, and nasal swab samples are collected, enabling incredibly comprehensive investigation of changes in a wide array of biomarkers that occur with the progression to type 1 diabetes. See the TEDDY website for more background.

10. POInT – Europe’s Primary Prevention Oral Insulin Trial – Enrollment is Tracking Ahead of Schedule, Study ~65% Enrolled

Dr. Olga Kordonouri offered an update on GPPAD’s type 1 diabetes risk screening efforts and POInT study enrollment, revealing that study recruitment is actually tracking slightly ahead of schedule:

With respect to this strong progress, Dr. Kordonouri commented that parents across GPPAD’s study sites have been accepting of participation in the trial. The study protocol accounts and allows for 20% dropout at study completion; at ~28 months into the study, participants are tracking at just above 5% dropout, which Dr. Kordonouri was quite positive about. As of May 7, 2020, GPPAD had screened 176,222 infants <5 months old. The 47-SNP genetic risk score that GPPAD is using – developed and validated by TEDDY – identified 1.17% (1,074) of these as eligible for POInT (i.e., they had 25-fold higher genetic risk for type 1 diabetes). This allows GPPAD to successfully identify children from the general population who have a >10% chance of developing type 1 diabetes, which has positive implications for current and future diabetes prevention trial enrollment.

POInT is a phase 2b primary prevention study aiming to enroll 1,040 infants at high genetic risk for type 1 diabetes, randomizing them 1:1 to oral insulin or placebo. The insulin group will escalate from 7.5 to 22.5 to 67.5 mg of “bulk human crystals” in capsules by 4 months. This dosing and timeframe are critical: They reflect a higher dose of oral insulin and earlier intervention in the natural history of type 1 diabetes compared to prior oral insulin studies, including TrialNet’s oral insulin study. POInT’s two primary endpoints are (i) development of ≥two autoantibodies (IAA, CADA, IA-2A, or ZnT8A) and (ii) development of type 1 diabetes. Recruitment began in February 2018, per Dr. Kordonouri, and is expected to take 3.5 years. Infants will be enrolled at four to seven months old (and with solid foods introduced), remain on oral insulin or placebo to three years old, then followed for up to 7.5 years. An interim analysis will be conducted at ~4.5 years after first randomization. Expected completion is January 2025.

• POInT is being conducted by GPPAD (Global Platform for Prevention of Autoimmune Diseases), a network of clinical centers across Germany, Poland, Sweden, Belgium, and the UK. These centers aim to screen >300,000 pregnant mothers and newborns for POInT alone, but will also serve as infrastructure for future studies. The program is supported by the Helmsley Charitable Trust. GPPAD infant screening in Europe is focused on identifying infants with >10% risk of developing type 1 diabetes, for the purposes of both enrolling them into the primary prevention POInT trial and monitoring them for early onset of type 1. Screening can occur via cord blood at delivery, with regular newborn screening, or any time before 5 months using filter paper cards.

11. PRE-D Analysis Shows No Impact of Dapa, Metformin, or Exercise on Glucagon in Prediabetes, Despite Positive Glycemic Impact

A new analysis of Steno Diabetes Center’s PRE-D trial (n=120) revealed that neither SGLT-2 inhibitor dapagliflozin, metformin, nor exercise affects plasma glucagon concentration in people with prediabetes over 13 weeks (844-P), despite positive effects on A1c and glycemic variability. Neither fasting nor post-75g OGTT plasma glucagon was affected compared to controls. For reference, participants were randomized to dapagliflozin 10 mg/d, metformin 1700 mg/d, 30 minutes of interval training 5 days/week, or control (normal living) for 13 weeks, then followed to 26 weeks. Baseline characteristics of this analysis include 56% men, median age 62, BMI 30.8 kg/m², A1c 5.9%, and fasting glucagon 11 pmol/L. We’ve included full results from the abstract below.

Increased glucagon has a well-established role in the pathophysiology of both type 1 and type 2 diabetes – indeed, glucagon antagonists have been studied in both type 1 and type 2 diabetes, but hampered by safety concerns. However, this data fails to suggest that any of these interventions can specifically target or improve disordered glucagon release in type 2 diabetes. This could be due to the short duration of the intervention and/or the mechanism of action of these drugs. To our understanding, glucagon excess is a function of insulin resistance at the level of alpha cells – a problem SGLT-2s and metformin aren’t thought to target, and one that would be challenging to improve via exercise without a focus on weight loss. This evokes an ongoing conversation in the diabetes prevention arena: Interventions can target glucose at a superficial level, or they can target the underlying pathology of insulin resistance; many feel the latter is necessary to improve long-term outcomes. We’re optimistic that upcoming readouts, most notably from VA-IMPACT, will offer new clarity on diabetes prevention strategy.

• Prior analyses of the PRE-D Trial presented at ADA 2019 demonstrate mostly-positive effects of all three therapies on glucose metabo­lism and glycemic variability. All three treatment groups were shown to improve A1c and fasting measures, while only dapagliflozin and exercise improved postprandial glucose metabolism. By 13 weeks compared to controls, A1c fell 1.3% with dapagliflozin, 1.3% with metformin, and 1.1% with exercise. Additionally, glycemic variability (as measured by MAGE) was reduced 17% by dapagliflozin (p=0.042) and 15% by exercise (p=0.067) at 13 weeks compared to the control group; metformin did not change MAGE compared to controls (p=0.99). PRE-D does not provide long-term outcomes data on progression to diabetes, but it does suggest a potential role for dapagliflozin/SGLT-2 inhibitors in prediabetes – a concept we’ve seen other posters investigate over the past few years. In fact, AZ’s PRESERVED-HF outcomes trial of dapa in HFpEF includes a secondary endpoint examining change in A1c in patients with vs. without type 2 diabetes – potentially valuable long-term data.

• These results are interesting in contrast to positive data on dapagliflozin impacting diabetes incidence in an analysis of the DAPA-HF trial, presented earlier this week at ADA. There, dapa treatment was associated with a 32% RRR vs. placebo on diabetes incidence after nearly two years of follow-up, although metabolic effects were not dramatically impacted – see here for more.

12. Panel on Diabetes Remission Highlights the Need for Comparative Studies, Support for Patients, and Elucidating Physiological Mechanisms

In a panel discussion moderated by Dr. Rita Basu, Drs. William Cefalu, Roy Taylor, and Francesco Rubino talked about the promise of new diets and metabolic surgery in promoting diabetes remission. As put by Dr. Cefalu in his presentation preceding the discussion, remission is currently based on A1c in normal limits for at least one year. However, as more data is available on the physiological appearance of remission, organizations are working together to revise its definition. This recent data comes from interventions like very-low calorie diets (most recently the DiRECT trial) and bariatric surgeries. One trend persisted in both of these interventions, as those with shorter duration of diabetes were the most likely to go into diabetes remission.

• The panel began with discussion on identifying patients most likely to respond to these treatment options. Dr. Taylor answered that while people with long-duration diabetes can experience remission, they are statistically much less likely to, and they need to be aware of that before attempting a low-calorie diet or undergoing surgery. However, he emphasized that losing weight has advantages that go beyond diabetes remission. If they decide to undergo bariatric surgery, they should be aware of post-bariatric surgery hypoglycemia, which Dr. Rubino affirmed is much more common than many believe. As it’s difficult to identify clinically meaningful post-prandial hypoglycemia after bariatric surgery, there is currently no accurate prevalence measure of the condition.  Though surgeons have been performing bariatric procedures for 60-70 years, risks and side effects unique to the procedure still need to be considered. Dr. Rubino urges that while surgery shouldn’t be front-line therapy, patients should move between different levels of therapy more quickly to not miss the window of possible remission. Dr. Cefalu agreed, adding that this delay in therapy intensification “has everything to do with clinical inertia.”

• Dr. Basu shifted the conversation to accessibility. As diets and access to HCPs varies across the globe, what’s the best approach to a low-calorie diet given these limitations? Dr. Taylor stated that these interventions do need to consider food intake in the context of cultural beliefs. With this, the low-calorie diet has seen success in countries like Barbados and India, and Dr. Taylor believes that it can be adopted to suit more cultures. He emphasized that any means of losing weight is effective, as the mechanism behind remission likely has to do with moving excess fat out of ectopic stores. In the future, it would be beneficial to compare low-calorie diets to low-carb diets to understand underlying mechanisms. Dr. Taylor warned that there haven’t been many studies on low-carb diets because of the emotion and pressure associated with them. Dr. Rubino suggested that new studies should examine cardiovascular endpoints. While procedures like biliopancreatic diversion can yield fast weight loss, these procedures are not approved globally because of their malabsorptive nature. Dr. Taylor also emphasized that long-term weight maintenance is different because people live different lives, making support and rescue plans in the case of weight gain integral.

• The session concluded with a conversation on what providers can do to best support patients. Dr. Basu asked the panelists for motivational factors that can help patients, to which Dr. Cefalu answered that providers must work to keep patients engaged. Telehealth may assist with this, but more research is needed on both achieving and maintaining weight loss in real world settings. Dr. Taylor believes that legislation changes hold promise in promoting healthy eating behaviors, and Dr. Rubino emphasized that HCPs shouldn’t assume patients lack the willpower and strength to stick to difficult diets.

13. PERL CGM Substudy Finds No Link Between Glycemic Variability and CKD Progression in Adults with T1D and Mild/Moderate Kidney Disease

New data from the PERL CGM substudy showed no association between glycemic variability or glucose control and the rate of loss of iGFR (iohexol GFR), among people with type 1 diabetes and mild-to-moderate kidney disease. PERL was a three-year study of allopurinol vs. placebo (n=530), and primary results were presented at ASN last November (see design below). Presenter Dr. Janet McGill reiterated that there was no significant difference between allopurinol and placebo on baseline-adjusted iGFR after three years of treatment + two months of drug washout (p=0.99). The larger trial contained a smaller CGM substudy on its back end, which enrolled 175 PERL participants (exclusions: pregnancy, history of skin reactions to LibrePro or Libre) who wore 1-5 blinded Freestyle Libre CGMs at some point during the last 15 months of the study (between visits 12-17). In total, 366 CGMs were worn. There were no significant associations between CGM-based metrics and iGFR, leading Dr. McGill to conclude that there is no evidence glycemic variability or glucose control impacts rate of iGFR loss. Here are the full results:

Dr. McGill noted that the CGM substudy in particular is limited by its observational nature, small sample size, variability in CGM data collection, and relatively short duration of observation. However, the authors of the study call for a larger, prospective study using CGM to improve glycemic control and reduce variability to definitively show whether glycemic variability and renal function are related.

• PERL (“Preventing Early Renal Loss in Diabetes”) evaluated allopurinol vs. placebo in people with type 1 diabetes and mild to moderate CKD (eGFR 40-100 ml/min/1.73 m²) – see the methods paper in Diabetes Care. Participants also had (i) serum uric acid ≥4.5 mg/dl and (ii) either history/presence or albuminuria or evidence of a >3 ml/min/1.73 m² loss in GFR per year in the previous 3-5 years. Allopurinol is a xanthine oxidase inhibitor used to reduce endogenous production of uric acid and a commonly prescribed treatment for gout. Its use in PERL was based on data from animal models, epidemiology, and small trials indicating high uric acid levels were related to CKD; participants received 200-400 mg/day depending on renal function. The study was funded by the Helmsley Charitable Trust and enrolled participants in the US, Canada, and Copenhagen.

• Baseline characteristics (mean) in the CGM substudy were: Age 52 years, 66% male, 81% white, type 1 duration 36 years, BMI 30 kg/m², A1c 8.2%, and eGFR and iGFR at visit four 75 and 68 ml/min/1.73 m².

14. AZ’s GLP-1/Glucagon Dual Agonist Cotadutide Reduces Liver Fat and Improves NASH Biomarkers in Phase 2a Readout

AZ’s Dr. Victoria Parker presented encouraging phase 2a on GLP-1/glucagon dual agonist cotadutide (MEDI0382) in NASH. Participants with type 2 diabetes (A1c <8%) and overweight/obesity (n=21) were randomized to receive cotadutide or placebo for 28 days. After this period, people on cotadutide showed significant reductions in postprandial hepatic glycogen content (-100.2 mmol/L vs. +5.5 mmol/L, p=0.023), a 27% relative reduction in fasting hepatic glycogen content (p=0.003), and a 33% relative reduction in liver fat (p=0.006). Additionally the cotadutide group saw reductions in fasting levels of amino acids that are typically elevated with NASH, including alanine, glutamate, glycine, lysine, and threonine levels vs. placebo (all p<0.05). Overall these results point to cotadutide as a promising therapy for NASH, an area of significant unmet need with no currently-approved therapies.

• These findings are in line with recent phase 2b data from AASLD 2019, in which cotadutide reduced the levels of several liver enzymes (ALT, AST, and GGT) and reduced body weight vs. placebo (p<0.003). At a 300 ug dose cotadutide even out-performed GLP-1 agonist liraglutide for weight loss (p=0.022).

• Notably, cotadutide was recently granted FDA Fast Track designation following the initiation of an additional phase 2 trial. Fast Track designations are granted to expedite the review of drugs with the potential to fill a large unmet medical need. AZ will now be privy to more regular meetings with FDA to discuss the development of cotadutide in NASH and may also be granted Priority Review down the line if certain criteria are met. Fast Track designations are by no means uncommon in the NASH space, especially given the total lack of approved therapies to treat NASH.

Exhibit Hall

Diabetes Technology

Abbott

If we had an award for best virtual exhibit hall booth, Abbott would certainly be in the conversation. Abbott’s fantastic “booth” proclaims FreeStyle Libre the “#1 CGM Worldwide” (by global user base) and includes webpages on US Products, International Products, Clinical Outcomes, and Remote Patient Monitoring. Providers can also schedule appointments to chat with a Medical Affairs, Sales, or LibreView representative. On the US Products page, Abbott highlighted its partnerships in the diabetes ecosystem (Bigfoot, Insulet, Novo Nordisk, Omada, Sanofi, and Tandem) and a short video gave us a look at Abbott’s partnership with Omada (announced October 2019). The International Products page features both FreeStyle Libre and FreeStyle Libre 2 (also FDA-cleared as of this morning). The page includes a number of videos, showing how to set up alarms, use LibreView, LibreLinkUp, and more. On the Clinical Outcomes side, the focus was entirely on Time in Range, which “provides more actionable information than HbA1c alone” – we couldn’t agree more! 

Companion Medical

Companion was one of the first companies to launch a virtual exhibit space, rolling out its “Companion Medical Virtual Conference” webpage back in April. The page features a variety of resources where visitors could view a virtual product theater, participate in webinars, secure information brochures on the InPen, and schedule demos with company reps. A quick ~2-minute video did an excellent job of describing the value of InPen, which strives to remove human error out of insulin dose decision dosing reminders, blood glucose entries, and insulin on board notifications. As a reminder, the Companion in April launched fixed dose and meal estimation-based dose calculation features in the InPen app (App Store; Google Play).

Dexcom

Dexcom tried to provide the most “authentic” exhibit hall experience allowing viewers to walk around a 3D-model of their booth in the browser. Dexcom’s G6 Pro was heavily featured, advertising “real-time alerts” and “quick and easy set-up.” G6 Pro is Dexcom’s first fully-disposable device and the first professional time to have an unblinded (i.e., real-time) mode. Dexcom’s marketing continues to focus on “no fingersticks,” “no scanning,” and “real-time CGM.” The last two points are obviously references to Abbott’s FreeStyle Libre CGM, which requires scanning to receive glucose values and trends.  

Glooko

Glooko’s virtual booth places a 6.5-minute video front-and-center (available on YouTube here) titled, “The Future of Telehealth.” CEO Russ Johannesson opens with a message from his home, noting that COVID-19 has accelerated the adoption of telehealth and remote monitoring by “ten years.” Mr. Johannesson outlines seven important criteria for effective telehealth solutions to hit: (i) easy to access; (ii) cost-effective; (iii) convenient to use; (iv) focused on driving quality outcomes; (v) meet regulatory requirements; (vi) maintain safety and privacy; and (vii) support reimbursement mechanisms. COO Komathi Stem appears next and we loved her focus on reducing the cognitive load of diabetes management through automation and AI tools. Moving onto CMO Mark Clements, the focus shifted to real-world evidence. Dr. Clements noted that CGM, AID, and mobile apps didn’t exist just a few years ago; as new tools and digital therapeutics become increasingly common, a platform like Glooko will become increasingly valuable to help gather real-world data. Finally, Chief Commercial Officer Zach Henderson made his appearance, sharing the Glooko is now used at 4,700 clinics and hospitals across 26 countries, with 300,000 “active monthly patients.”  

Insulet

Insulet’s exhibit hall page links viewers to new resources around Omnipod Virtual Care, including automatic data upload via Insulet Provided Glooko, remote monitoring with the Omnipod DISPLAY and VIEW apps and Omnipod DASH’s availability through the pharmacy channel, which makes for “easier prescribing,” “less paperwork,” and a “faster start to therapy.” As we heard on the company’s 1Q20 update, “almost 30%” of total volume is now coming through the pharmacy channel, driven by Omnipod DASH. In the company’s marketing, there was also noticeable focus on MDI and type 2 patients, where Omnipod DASH is particularly well-positioned for success as the result of Medicare Part D coverage through pharmacy channel, reducing upfront paperwork for the HCP while giving patients the ability to easily switch with no DME lock-in. Lastly, an American flag with Pods in place of stars caught our eye: Insulet is running a “30 Days of Freedom!” promotion, offering a 30-day free trial of Omnipod DASH for U.S. patients of ADA-registered healthcare providers through July 31st.

LifeScan

LifeScan’s nifty booth took the viewer through a series of five stations highlighting the company’s OneTouch Verio Reflect BGM. As a reminder, the device provides both readings and active coaching to help patients manage blood glucose as part of a three-prong strategy: (i) guidance; (ii) insight; and (iii) encouragement. For example, if a patient is below 70 mg/dl, the meter’s display will inform the user to employ a treatment strategy. If a specific pattern of hyperglycemia is found, the meter will ask a question prompting if any behavior has changed. The device uses a color-coded scheme called the ColorSure Dynamic Range Indicator to inform patients if they are out of range. LifeScan also offers a patient web application where users can access visuals highlighting diabetes trends and numbers (e.g. blood glucose levels, % Time in Range, color schemes). Physicians likewise have their own professional web app where they can view large-scale trends (e.g. average blood glucose, sorting by demographics, patients enduring hypoglycemia). Last month, New York-based weight-loss app Noom launched a digital diabetes and weight loss pilot program where selected LifeScan BGM users gain free access to the One Touch Reveal app (App Store; Google Play) and Noom’s Diabetes Management Program.

Medtronic

Attendees entering Medtronic’s virtual exhibit are greeted with three big signs reading, “Outcomes,” “Technology,” and “Support.” Under the Outcomes sign, Medtronic highlights how its products improve “outcomes that matter,” namely quality of life, reducing burden, and empowering users and caregivers with information. Medtronic’s booth advertises the new FDA approval for standalone Guardian CGM and the system’s predictive high and low glucose alerts. A short video on Guardian Connect gave us our first look at the new updated version of the Guardian Connect app, expected to come “this summer.” The update will add customizable alerts (different alert settings for nighttime and daytime hours), adjustable alert volumes, and a new set-up wizard. Also in the Outcomes section, a slide on MiniMed 670G notes “over 250,000” users, slightly above the “~249,000,” figure shared last month. 

In the “Technology” section of the booth, Medtronic highlights four of its product lines: pump systems, MDI solutions (Guardian Connect CGM and i-Port Advance Injection Port), infusion sets, and software. In this section, we especially enjoyed seeing a “What is Time in Range?” graphic, which nicely broke down the new consensus guidelines and notes that a 4% increase in Time in Range results in 15 extra day per year. Finally, in the “Support” section, Medtronic advertises its “support you can count on.” The section includes video resources on transitioning to telehealth, financial assistance programs for patients, virtual patient trainings, supply ordering, Medtronic’s medical education programs, and the company’s own response to COVID-19.

--by Ursula Biba, Rhea Teng, Ann Carracher, Abigail Dove, Payal Marathe, Martin Kurian, Joseph Bell, Kira Wang, Ani Gururaj, Hanna Gutow, Katie Mahoney, Albert Cai, Brian Levine, and Kelly Close