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Background: This study compared glucose control with fast-acting insulin aspart (FiAsp) versus insulin aspart following moderate-intensity exercise (MIE) and high-intensity exercise (HIE) using a s...

Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes. We present sub-study data from a dual-center, randomized, open-label, two-sequence crossover study in automated insulin delivery naive users, comparing Medtronic MiniMed® Advanced Hybrid Closed-Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP + PLGM). At the end of each 4-week intervention, impacts on quality of life, sleep and treatment satisfaction were compared using seven age-appropriate validated questionnaires given to patients or caregivers. 59/60 people completed the study (mean age 23.3 ± 14.4yrs). Statistically significant differences favoring AHCL were demonstrated in several scales (data shown as mean ± SE). In adults (≥ 18yrs), technology satisfaction favored AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n = 28) vs SAP + PLGM (n = 29) (30.9 ± 0.7 vs 27.9 ± 0.7, p = 0.004) and DTSQc AHCL (n = 29) vs SAP + PLGM (n = 30) (11.7 ± 0.9 vs 9.2 ± 0.8, p = 0.032). Adolescents (aged 13–17yrs) also showed a higher DTSQc score during AHCL (n = 16) versus SAP + PLGM (n = 15) (14.8 ± 0.7 vs 12.1 ± 0.8, p = 0.024). The DTQ “change” score (n = 59) favored AHCL over SAP + PLGM (3.5 ± 0.0 vs 3.3 ± 0.0, p 16 years (n = 36) and demonstrated improved sleep quality during AHCL vs SAP + PLGM (4.8 ± 0.3 vs 5.7 ± 0.3, p = 0.048) with a total score > 5 indicating poor quality sleep. These data suggest that AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D.

Background: We compared glycemic outcomes and participant experience during MiniMed™ 780G Advanced Hybrid Closed Loop (AHCL) system use while announcing all meals vs. announcing meals at will. Methods: Participants with T1DM used the AHCL system at home during two 90 days phases in which they were given instructions first to announce all meals (AM) , and next, for meals containing up to 80 grams of carbohydrates, to announce meals at will (AMW) . Results: Fourteen subjects (males, mean age 44.3±11) with T1DM were enrolled, with a baseline A1C of 6.9±1%. Table 1 summarizes glycemic indices and AHCL data, demonstrating that patients chose to bolus only slightly less during AMW compared to AM (5.5 vs. 5.2 boluses) , without resultant deterioration in glycemic indices (A1c 6.4 vs. 6.5%, TIR 78.1 vs. 78.8%, p=ns) . Subjects surveyed regarding the option not to have to bolus for all meals experienced a significant reduction in reported effort to manage diabetes (p=0.045) and 86% endorsed worrying less about their diabetes. Most (93%) preferred the AMW phase of the study. Conclusion: The MinMed™ AHCL system is designed for optimal performance with meal announcement. Nonetheless, when meals containing < 80 grams of carbohydrates are consumed with announcement of meals at will, there is a slight reduction in the number of daily boluses with no decline in glycemic control, yet markedly less diabetes related distress and improved treatment satisfaction. Disclosure N. Minsky: None. R. Shalit: Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic, Novo Nordisk. O. Cohen: Employee; Medtronic. N. Kurtz: Employee; Medtronic. A. Roy: Employee; Medtronic. B. Grosman: Employee; Medtronic. A. Tirosh: Advisory Panel; Abbott Diagnostics, AstraZeneca, Boehringer Ingelheim International GmbH, Merck & Co., Inc., Novo Nordisk, Sanofi. Consultant; Bayer AG, DreaMed Diabetes, Ltd. Research Support; Medtronic. Speaker's Bureau; Eli Lilly and Company.

Background: The Medtronic MiniMed™ 670G system adjusts basal insulin delivery in response to continuous glucose monitoring levels and is already in use in clinical practice. We tested the home-base...

Objective To evaluate glucose control using fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp) delivered by the MiniMedä Advanced Hybrid Closed-Loop (AHCL) system in adults with type 1 diabetes. Research Design and Methods In this randomized, open-label, crossover study, participants were assigned to receive faster aspart or IAsp in random-order. Stages 1 and 2 comprised six-weeks in closed-loop; preceded by two-weeks in open-loop. This was followed by Stage 3, whereby participants changed directly back to the insulin formulation used in Stage 1 for one-week in CL. Participants chose their own meals except for two standardized meal tests; a missed and late meal bolus. Primary outcome was % sensor glucose time-in-range (TIR; 70-180mg/dL). Results Twenty-five adults (52% male) were recruited; median (IQR) age was 48 (37, 57) years, and HbA1c 7.0% (6.6, 7.2) (53 [49, 55] mmol/mol). Faster aspart demonstrated greater overall TIR compared with IAsp (82.3% [78.5, 83.7] vs. 79.6% [77.0, 83.4], respectively; mean difference 1.9% [0.5, 3.3]; p=0.007). Four-hour PPG TIR was higher using faster aspart compared with IAsp for all-meals combined (73.6% [69.4, 80.2] vs. 72.1% [64.5, 78.5], respectively; median difference 3.5% [1.0, 7.3]; p=0.003). There was no ketoacidosis or severe hypoglycemia. Conclusions Faster aspart safely improved glucose control compared with IAsp in a well-controlled group of adults with type 1 diabetes using AHCL. The modest improvement mainly related to mealtime glycemia. Whilst the primary outcome demonstrated statistical significance, the clinical impact may be small given an overall difference in TIR of 1.9%.

Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes.We present sub-study data from a dual-center, randomized, open-label, two-sequence crossover study in automated insulin delivery naïve users, comparing Medtronic MiniMed® Advanced Hybrid Closed-Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP + PLGM). At the end of each 4-week intervention, impacts on quality of life, sleep and treatment satisfaction were compared using seven age-appropriate validated questionnaires given to patients or caregivers.59/60 people completed the study (mean age 23.3 ± 14.4yrs). Statistically significant differences favoring AHCL were demonstrated in several scales (data shown as mean ± SE). In adults (≥ 18yrs), technology satisfaction favored AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n = 28) vs SAP + PLGM (n = 29) (30.9 ± 0.7 vs 27.9 ± 0.7, p = 0.004) and DTSQc AHCL (n = 29) vs SAP + PLGM (n = 30) (11.7 ± 0.9 vs 9.2 ± 0.8, p = 0.032). Adolescents (aged 13-17yrs) also showed a higher DTSQc score during AHCL (n = 16) versus SAP + PLGM (n = 15) (14.8 ± 0.7 vs 12.1 ± 0.8, p = 0.024). The DTQ "change" score (n = 59) favored AHCL over SAP + PLGM (3.5 ± 0.0 vs 3.3 ± 0.0, p 0.001). PSQI was completed in those 16 years (n = 36) and demonstrated improved sleep quality during AHCL vs SAP + PLGM (4.8 ± 0.3 vs 5.7 ± 0.3, p = 0.048) with a total score 5 indicating poor quality sleep.These data suggest that AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D.

OBJECTIVETo evaluate glucose control using fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp) delivered by the MiniMed Advanced Hybrid Closed-Loop (AHCL) system in adults with type 1 diabetes.RESEARCH DESIGN AND METHODSIn this randomized, open-label, crossover study, participants were assigned to receive faster aspart or IAsp in random order. Stages 1 and 2 comprised of 6 weeks in closed loop, preceded by 2 weeks in open loop. This was followed by stage 3, whereby participants changed directly back to the insulin formulation used in stage 1 for 1 week in closed loop. Participants chose their own meals except for two standardized meal tests, a missed meal bolus and late meal bolus. The primary outcome was the percentage of time sensor glucose values were from 70 to 180 mg/dL (time in range [TIR]).RESULTSTwenty-five adults (52% male) were recruited; the median (interquartile range) age was 48 (37, 57) years, and the median HbA1c was 7.0% (6.6, 7.2) (53 [49, 55] mmol/mol). Faster aspart demonstrated greater overall TIR compared with IAsp (82.3% [78.5, 83.7] vs. 79.6% [77.0, 83.4], respectively; mean difference 1.9% [0.5, 3.3]; P = 0.007). Four-hour postprandial glucose TIR was higher using faster aspart compared with IAsp for all meals combined (73.6% [69.4, 80.2] vs. 72.1% [64.5, 78.5], respectively; median difference 3.5% [1.0, 7.3]; P = 0.003). There was no ketoacidosis or severe hypoglycemia.CONCLUSIONSFaster aspart safely improved glucose control compared with IAsp in a group of adults with well-controlled type 1 diabetes using AHCL. The modest improvement was mainly related to mealtime glycemia. While the primary outcome demonstrated statistical significance, the clinical impact may be small, given an overall difference in TIR of 1.9%.

Medtronic has developed a virtual patient simulator for modeling and predicting insulin therapy outcomes for people with type 1 diabetes (T1D). An enhanced simulator was created to estimate outcomes when using the MiniMedSixty-seven participants' PK profiles were generated per type of insulin (Total of 134 PK profiles). 7,485 virtual patients' PK measurements was matched with one of the 67 NovoLog® PK Tmax values. These 7,485 virtual patients were then simulated using the Medtronic MiniMed™ 670G algorithm following an in-silico protocol of 90 days: 14 days in open loop (Manual Mode) followed by 76 days in closed loop (Auto Mode). Simulation study was repeated with each NovoLog® PK profile being replaced by its corresponding Fiasp® PK profile in the same virtual patient. To validate our in-silico analysis, we compared the results of "actual" 19 "real life" patients from a clinical study RESULTS: Simulated overall and postprandial glycemic outcomes improved in all age groups with Fiasp®. The percentage of time in the euglycemic range increased by about ~2.2% with Fiasp®, in all age groups (p 0.01). The percentage of time spent at70 mg/dL was reduced by about ~0.6% with insulin Fiasp® (p 0.01) and the mean glucose was reduced by about 1.3 mg/dL (p 0.01), excluding those age7 years. The simulated mean postprandial SG was reduced by ~5 mg/dL, a significant difference for all age groups. A clinical study results showed similar improvements with MiniMedThe simulation studies indicate that using Fiasp® in place of NovoLog® with the MiniMed

Background: Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes. Methods: This dual-centre, randomized, open-label, two-sequence cross-over study in automated insulin delivery naïve users, compared Medtronic Minimed® Advanced Hybrid Closed Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP+PLGM). At the end of each 4 week intervention impacts on quality of life were compared using age-appropriate scales: Diabetes Treatment Satisfaction Questionnaire status and change (DTSQs and DTSQc), Diabetes Technology Questionnaire (DTQ), Pittsburgh Sleep Quality Index (PSQI), World Health Organisation-Five Well-Being Index (WHO-5), Hypoglycemic Fear Survey (HFS-II) and Hypoglycemia Confidence Scale (HCS). Results: 59/60 people completed the study (mean age 23.3±14.4yrs). Statistically significant differences favouring AHCL were demonstrated in several scales (data shown as mean±SE). Technology satisfaction favoured AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n=28) vs. SAP+PLGM (n=29) (30.9±0.7 vs. 27.9±0.7, p=0.004) and DTSQc AHCL (n=29) vs. SAP+PLGM (n=30) (11.7±0.9 vs. 9.2±0.8, p=0.032) in adults. Adolescents also showed a higher DTSQc score during AHCL (n=16) vs. SAP+PLGM (n=15) (14.8±0.7 vs. 12.1±0.8, p=0.024). The DTQ “change” score (n=59) favoured AHCL over SAP+ PLGM (3.5±0.0 vs. 3.3±0.0, p 5 indicating poor quality sleep. No differences were found in the other scales. Conclusion: The findings from this RCT suggest AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D. Disclosure O. Collyns: None. R. Meier: None. Z. Betts: None. D. Chan: None. C. Frampton: None. C.M. Frewen: None. B. Galland: None. N. Hewapathirana: Other Relationship; Self; Sanofi. S. Jones: None. N. Kurtz: Employee; Self; Medtronic. J. Shin: Employee; Self; Medtronic. R. Vigersky: Employee; Self; Medtronic. B.J. Wheeler: Research Support; Self; Medtronic. M. de Bock: None.

Background: The Medtronic Minimed® Advanced Hybrid Closed-Loop system (AHCL) includes an individualised algorithm with optional set points, automated correction bolus, and improved SmartGuard™ Auto Mode stability. Methods: This dual-centre, randomized, open-label, two-sequence cross-over study in automated insulin delivery naïve participants (aged 7-80yrs), compared AHCL to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP+PLGM). Each study phase was 4 weeks, preceded by a 2-4 week run-in, and separated by 2-week washout. Results: 59/60 people completed the study (mean age 23.3±14.4yrs). Overall time in target range (TIR) (70-180mg/dL) favoured AHCL over SAP+PLGM by 12.5±8.5% (p180mg/dL). Mean SG improved in AHCL by 10.0±7.4mg/dL (p Conclusion: AHCL with automated correction bolus showed significant improvement in glucose control compared to PLGM, in a population with a younger mean age reflecting a challenging demographic. Disclosure O. Collyns: None. R. Meier: None. Z. Betts: None. D. Chan: None. C. Frampton: None. C.M. Frewen: None. B. Grosman: Employee; Self; Medtronic. N. Hewapathirana: Other Relationship; Self; Sanofi. S. Jones: None. N. Kurtz: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic. J. Shin: Employee; Self; Medtronic. R. Vigersky: Employee; Self; Medtronic. B.J. Wheeler: Research Support; Self; Medtronic. M. de Bock: None.

Background: Faster-acting insulin aspart (FiAsp) may improve responsiveness of closed-loop (CL) systems and provide better postprandial glucose (PPG) management due to its more rapid onset and offset compared to insulin aspart (Asp). The Medtronic Advanced Hybrid Closed Loop (AHCL) System features auto-basal and auto-bolus functions. Aim: To compare PPG control using FiAsp vs. Asp delivered using AHCL. Methods: Twelve adults with T1D (median HbA1c 7.1% [IQR 6.8, 7.2]; 54mmol/mol [51, 55]) were assigned to FiAsp or Asp (unblinded) in random-order over two-stages (6-weeks duration each) using AHCL. Postprandial periods were defined using set time-blocks for breakfast (06:00-10:00); lunch (11:00-15:00); and dinner (17:00-21:00), based on conventional meal-times and meal distribution. CGM data was analyzed using signed-rank test. Results: With all postprandial time-block data aggregated, FiAsp demonstrated greater overall time-in-range (TIR) (70-180mg/dL) (p=0.028) and less hyperglycaemia (p=0.041) compared with Asp (Table). TIR was greater during lunch (p=0.034) for FiAsp vs. Asp, with no difference during breakfast or dinner. Over the 6-week duration, FiAsp use trended towards greater TIR vs. Asp (82.7% vs. 80.4%, p=0.07). Conclusions: FiAsp appears to confer an advantage compared with Asp for PPG control whilst using AHCL even in subjects with high overall TIR. Disclosure M.H. Lee: Research Support; Self; Medtronic. Speaker’s Bureau; Self; AstraZeneca, Medtronic. S. Vogrin: None. B. Paldus: Research Support; Self; JDRF. Speaker’s Bureau; Self; Australian Diabetes Society, Medtronic. D. Morrison: None. D. Zaharieva: Speaker’s Bureau; Self; Ascensia Diabetes Care, Insulet Corporation, Medtronic. J. Lu: None. H. Jones: None. S.A. Wyatt: Other Relationship; Self; Medtronic, Ypsomed AG. E. Netzer: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. R. MacIsaac: None. B. Grosman: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic. N. Kurtz: Employee; Self; Medtronic. A. Jenkins: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Sanofi-Aventis. D.N. ONeal: None.

Background and Aims: Advanced Hybrid closed loop (AHCL) algorithm combines automated basal rate with additional enhancement when a rise in glucose level is detected. This study assessed the effectiveness and safety of AHCL with unannounced meals. Methods: Fourteen participants were using Medtronic AHCL system at home for a mean of 72.6 days. Each participant spent 4 days in a protected free-living environment while consuming pre-defined meals consisting of up to 80 grams of carbohydrates each day. On day 5, participants initiated a 3-months unannounced meal phase at their homes with the instruction to announce only meals containing over 80 grams. Results: Fourteen subjects with T1DM (10 males, mean age 44.3±3.9 years) and baseline HgbA1C% of 6.75± 1.2 were enrolled. Patients spent 97±3% of time in Auto-Mode, with mean SG of 157.8±19.2. Mean %time in range70-180was 67.6±12.8, %time Conclusion: Medtronic AHCL system is designed for best performance with meal announcement. Nevertheless, when meals containing ≤ 80 gram of carbohydrates are consumed without meal announcement, the system can provide safe glycemic control with about 67.6% of TIR. Disclosure A. Tirosh: Advisory Panel; Self; Novo Nordisk Inc., Sanofi. R. Shalit: Research Support; Self; Medtronic. M. Laron Hirsh: None. O. Cohen: Employee; Self; Medtronic. N. Kurtz: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic. B. Grosman: Employee; Self; Medtronic. Funding Medtronic

Introduction Medtronic has developed a virtual patient simulator for modeling and predicting insulin therapy outcomes for people with type 1 diabetes (T1D). An enhanced simulator was created to estimate outcomes when using the MiniMedTM 670G system with standard NovoLog® (EU: NovoRapid, US: NovoLog) versus Fiasp ® by using clinical data. Methods Sixty-seven participants' PK profiles were generated per type of insulin (Total of 134 PK profiles). 7,485 virtual patients' PK measurements was matched with one of the 67 NovoLog® PK Tmax values. These 7,485 virtual patients were then simulated using the Medtronic MiniMed™ 670G algorithm following an in-silico protocol of 90 days: 14 days in open loop (Manual Mode) followed by 76 days in closed loop (Auto Mode). Simulation study was repeated with each NovoLog® PK profile being replaced by its corresponding Fiasp® PK profile in the same virtual patient. To validate our in-silico analysis, we compared the results of “actual” 19 “real life” patients from a clinical study Results Simulated overall and postprandial glycemic outcomes improved in all age groups with Fiasp®. The percentage of time in the euglycemic range increased by about ~2.2% with Fiasp®, in all age groups (p Conclusions The simulation studies indicate that using Fiasp® in place of NovoLog® with the MiniMedTM 670G system will significantly improve the time spent in the healthy, euglycemic range and reduce exposure to hyperglycemia and hypoglycemia in most patients.

We aimed to compare closed-loop glucose control for people with type 1 diabetes undertaking high-intensity interval exercise (HIIE) versus moderate-intensity exercise (MIE).Adults with type 1 diabetes established on insulin pumps undertook HIIE and MIE stages in random order during automated insulin delivery via a closed-loop system (Medtronic). Frequent venous sampling for glucose, lactate, ketones, insulin, catecholamines, cortisol, growth hormone, and glucagon levels was performed. The primary outcome was plasma glucose4.0 mmol/L for ≥15 min, from exercise commencement to 120 min postexercise. Secondary outcomes included continuous glucose monitoring and biochemical parameters.Twelve adults (age mean ± standard deviation 40 ± 13 years) were recruited; all completed the study. Plasma glucose of one participant fell to 3.4 mmol/L following MIE completion; no glucose levels were4.0 mmol/L for HIIE (primary outcome). There were no glucose excursions15.0 mmol/L for either stage. Mean (±standard error) plasma glucose did not differ between stages pre-exercise; was higher during exercise in HIIE than MIE (11.3 ± 0.5 mmol/L vs. 9.7 ± 0.6 mmol/L, respectively; P 0.001); and remained higher until 60 min postexercise. There were no differences in circulating free insulin before, during, or postexercise. During HIIE compared with MIE, there were greater increases in lactate (P 0.001), catecholamines (all P 0.05), and cortisol (P 0.001). Ketones increased more with HIIE than MIE postexercise (P = 0.031).Preliminary findings suggest that closed-loop glucose control is safe for people undertaking HIIE and MIE. However, the management of the postexercise rise in ketones secondary to counter-regulatory hormone-induced insulin resistance observed with HIIE may represent a challenge for closed-loop systems.

We compared glycemia, treatment satisfaction, sleep quality, and cognition using a nighttime Android-based hybrid closed-loop system (Android-HCLS) with sensor-augmented pump with low-glucose suspend function (SAP-LGS) in people with type 1 diabetes.An open-label, prospective, randomized crossover study of 16 adults (mean [SD] age 42.1 [9.6] years) and 12 adolescents (15.2 [1.6] years) was conducted. All participants completed four consecutive nights at home with Android-HCLS (proportional integral derivative with insulin feedback algorithm; Medtronic) and SAP-LGS.percent continuous glucose monitoring (CGM) time (00:00-08:00 h) within target range (72-144 mg/dL). Secondary endpoints: percent CGM time above target (144 mg/dL); below target (72 mg/dL); glycemic variability (SD); symptomatic hypoglycemia; adult treatment satisfaction; sleep quality; and cognitive function.The primary outcome for all participants was not statistically different between Android-HCLS and SAP-LGS (mean [SD] 59.4 [17.9]% vs. 53.1 [18]%; p = 0.14). Adults had greater percent time within target range (57.7 [18.6]% vs. 44.5 [14.5]%; p 0.006); less time above target (42.0 [18.7]% vs. 52.6 [16.5]%; p = 0.034); lower glycemic variability (35 [10.7] mg/dL vs. 46 [10.7] mg/dL; p = 0.003); and less (median [IQR]) time below target (0.0 [0.0-0.4]% vs. 0.80 [0.0-3.9]%; p = 0.025). In adolescents, time below target was lower with Android-HCLS vs. SAP-LGS (0.0 [0.0-0.0]% vs. 1.8 [0.1-7.9]%; p = 0.011). Nocturnal symptomatic hypoglycemia was less (1 vs. 10; p = 0.007) in adolescents, but not adults (5 vs. 13; p = 0.059). In adults, treatment satisfaction increased by 10 points (p 0.02). Sleep quality and cognition did not differ.Android-HCLS in both adults and adolescents reduced nocturnal hypoglycemia and, in adults, improved overnight time in target range and treatment satisfaction compared with SAP-LGS.

Background: Forgetting a premeal bolus can lead to hyperglycemia in patients with type 1 diabetes (T1D). A prototype e-HCL system was designed to automatically deliver basal insulin and correction boluses based on sensor glucose (SG) values. The effect of the system on hyperglycemia due to unannounced medium-sized meals was assessed. Methods: Twelve subjects with T1D aged 15-25 years (median 17 years) underwent a 1-week hotel phase of e-HCL Auto Mode use, followed by a 3-week unsupervised at-home phase of use. On the third day of the hotel phase, a ∼40gm-carbohydrate (carb) dinner was consumed without a premeal bolus. Five hours of postprandial data were analyzed and compared to data captured after 40gm-carb meals eaten during the at-home phase, but accompanied by a premeal bolus. Results: Meals without a premeal bolus resulted in postprandial SG levels statistically similar to those observed for meals accompanied by a premeal bolus (Table). Conclusion: These data suggest that e-HCL can handle unannounced medium-sized meals to a similar extent as meals of equal size accompanied by premeal boluses. This may improve overall glycemic control of patients who underestimate or frequently forget to administer premeal boluses. Disclosure A. Roy: Employee; Self; Medtronic MiniMed, Inc. B. Grosman: Employee; Self; Medtronic. N. Parikh: None. D. Wu: None. L.J. Lintereur: Employee; Self; Medtronic MiniMed, Inc. N. Kurtz: Employee; Self; Medtronic MiniMed, Inc. F.R. Kaufman: Employee; Self; Medtronic.

Background: Automated insulin delivery, or closed-loop (CL), systems are emerging as a management tool for individuals with T1D. The MiniMed™ 670G system is a single hormone hybrid closed-loop (HCL) system that adjusts basal insulin delivery based on sensor glucose (SG)levels and is already used in clinical practice. An enhanced HCL system (e-HCL) prototype with an automated correction bolus feature was developed and evaluated in a small feasibility study. Methods: Subjects (n=12) aged a mean±SD of 17.6±2.9 years with T1D and an A1C of 7.3±0.7% (56.5±7.7 mmol/mol) completed a 6-day run-in period with the e-HCL system in open-loop (OL) (i.e., Auto Mode OFF and Suspend before low ON). Thereafter, a supervised hotel period (6 days/5 nights) with CL challenges (missed meal bolus, late meal bolus, and physical activity) was completed, and followed by a 3-week at-home period with Auto Mode and automated correction boluses ON, without restrictions. Glycemic control was compared between the OL run-in period and CL period. Results: During the at-home period, subjects spent 93±4% of the time in Auto Mode. Time within target glucose range of 70-180 mg/dL (3.9-10.0 mmol/L) increased from 68.8±10.5% to 74±6.1%, time >180 mg/dL reduced from 27.1±11.9% to 23.7±8.8%, and time Conclusions: Incorporating automated correction boluses to an HCL system was safe and effective in controlling day and night glucose levels, during a 3-week at-home period. Disclosure R. Nimri: Employee; Self; DreaMed Diabetes. Research Support; Self; Dexcom, Inc., Glooko, Inc., Insulet Corporation, JDRF, Medtronic, National Institutes of Health. Speaker's Bureau; Self; Lilly Diabetes. Stock/Shareholder; Self; DreaMed Diabetes. B. Grosman: Employee; Self; Medtronic. N. Kurtz: Employee; Self; Medtronic MiniMed, Inc. A. Roy: Employee; Self; Medtronic MiniMed, Inc. J. Nir: None. N. Loewenthal: None. F.R. Kaufman: Employee; Self; Medtronic. M. Phillip: Consultant; Self; Qulab Medical, RSP Systems A/S. Research Support; Self; Bristol-Myers Squibb Company, Dexcom, Inc., JDRF, Lexicon Pharmaceuticals, Inc., Merck & Co., Inc., OPKO. Stock/Shareholder; Self; DreaMed Diabetes, Ltd., NG Solutions Ltd., Nutriteen Professional Ltd. Other Relationship; Self; AstraZeneca, Eli Lilly and Company, Insulet Corporation, Medtronic MiniMed, Inc., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis.

Sensor-augmented pump therapy (SAPT) with a predictive algorithm to suspend insulin delivery has the potential to reduce hypoglycemia, a known obstacle in improving physical activity in patients with type 1 diabetes. The predictive low glucose management (PLGM) system employs a predictive algorithm that suspends basal insulin when hypoglycemia is predicted. The aim of this study was to determine the efficacy of this algorithm in the prevention of exercise-induced hypoglycemia under in-clinic conditions.This was a randomized, controlled cross-over study in which 25 participants performed 2 consecutive sessions of 30 min of moderate-intensity exercise while on basal continuous subcutaneous insulin infusion on 2 study days: a control day with SAPT alone and an intervention day with SAPT and PLGM. The predictive algorithm suspended basal insulin when sensor glucose was predicted to be below the preset hypoglycemic threshold in 30 min. We tested preset hypoglycemic thresholds of 70 and 80 mg/dL. The primary outcome was the requirement for hypoglycemia treatment (symptomatic hypoglycemia with plasma glucose63 mg/dL or plasma glucose50 mg/dL) and was compared in both control and intervention arms.Results were analyzed in 19 participants. In the intervention arm with both thresholds, only 6 participants (32%) required treatment for hypoglycemia compared with 17 participants (89%) in the control arm (P = 0.003). In participants with a 2-h pump suspension on intervention days, the plasma glucose was 84 ± 12 and 99 ± 24 mg/dL at thresholds of 70 and 80 mg/dL, respectively.SAPT with PLGM reduced the need for hypoglycemia treatment after moderate-intensity exercise in an in-clinic setting.

Background Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70–180 mg/dL (3.9–10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes. Methods We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4–5 days. Results The overall mean percentage of time in range (70–180 mg/dL, 3.9–10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort. Conclusions Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control.

In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient's pump.A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject's BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested.The percentage of time in glucose range 80-180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61-231 mg/dl min-max envelope, whereas use of the simulator's default treatment resulted in BG measurements 90-210 mg/dl min-max envelope.The study results demonstrate the potential of this method, which could serve as a platform for improving, facilitating, and standardizing insulin pump therapy based on a single download of data.

Background: Hypoglycemia remains a risk for closed loop insulin delivery particularly following exercise or if the glucose sensor is inaccurate. The aim of this study was to test whether an algorithm that includes a limit to insulin delivery is effective at protecting against hypoglycemia under those circumstances. Methods: An observational study on 8 participants with type 1 diabetes was conducted, where a hybrid closed loop system (HCL) (Medtronic™ 670G) was challenged with hypoglycemic stimuli: exercise and an overreading glucose sensor. Results: There was no overnight or exercise-induced hypoglycemia during HCL insulin delivery. All daytime hypoglycemia was attributable to postmeal bolused insulin in those participants with a more aggressive carbohydrate factor. Conclusion: HCL systems rely on accurate carbohydrate ratios and carbohydrate counting to avoid hypoglycemia. The algorithm that was tested against moderate exercise and an overreading glucose sensor performed well in terms of hypoglycemia avoidance. Algorithm refinement continues in preparation for long-term outpatient trials.

Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70-180 mg/dL (3.9-10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes.We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4-5 days.The overall mean percentage of time in range (70-180 mg/dL, 3.9-10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort.Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control.

OBJECTIVE A key milestone in progress towards providing an efficacious and safe closed-loop artificial pancreas system for outpatient use is the development of fully automated, portable devices with fault detection capabilities to ensure patient safety. The ability to remotely monitor the operation of the closed-loop system would facilitate future physician-supervised home studies. RESEARCH DESIGN AND METHODS This study was designed to investigate the efficacy and safety of a fully automated, portable, closed-loop system. The Medtronic Portable Glucose Control System (PGCS) consists of two subcutaneous glucose sensors, a control algorithm based on proportional-integral-derivative with insulin feedback operating from a BlackBerry Storm smartphone platform, Bluetooth radiofrequency translator, and an off-the-shelf Medtronic Paradigm Veo insulin pump. Participants with type 1 diabetes using insulin pump therapy underwent two consecutive nights of in-clinic, overnight, closed-loop control after a baseline open-loop assessment. RESULTS Eight participants attended for 16 overnight studies. The PGCS maintained mean overnight plasma glucose levels of 6.4 ± 1.7 mmol/L (115 ± 31 mg/dL). The proportion of time with venous plasma glucose 8 mmol/L was 7, 78, and 15%, respectively. The proportion of time the sensor glucose values were maintained between 3.9 and 8 mmol/L was greater for closed-loop than open-loop (84.5 vs. 46.7%; P < 0.0001), and time spent CONCLUSIONS These results suggest that the PGCS, an automated closed-loop device, is safe and effective in achieving overnight glucose control in patients with type 1 diabetes.

Studies using outpatient closed-loop insulin delivery for type 1 diabetes have recently been published (1–5). We conducted a 5-day outpatient feasibility study comparing hybrid closed-loop (HCL) to sensor-augmented pump therapy with low-glucose suspend (SAPT + LGS) in eight patients with type 1 diabetes using an open-label randomized crossover trial design (ACTRN12614001005640). We used the Medtronic HCL system: MiniMed insulin pump, MiniMed Enlite II glucose sensor, MiniMed MiniLink REAL-time sensor, MiniMed Translator, and an Android mobile device with the algorithm (proportional integrative derivate with insulin feedback and additional safety parameters—primarily being an upper limit of allowable insulin delivery). Multiple algorithm parameters were individualized according to total daily insulin requirements in the preceding 48 h. Meals were announced by entering a capillary glucose value and meal carbohydrate content, for which bolus insulin was delivered according to the patient’s unique carbohydrate ratio. The Android mobile device sent data via the Internet, …

Initial studies of closed-loop proportional integral derivative control in individuals with type 1 diabetes showed good overnight performance, but with breakfast meal being the hardest to control and requiring supplemental carbohydrate to prevent hypoglycemia.The aim of this study was to assess the ability of insulin feedback to improve the breakfast-meal profile.We performed a single center study with closed-loop control over approximately 30 h at an inpatient clinical research facility.Eight adult subjects with previously diagnosed type 1 diabetes participated.Subjects received closed-loop insulin delivery with supplemental carbohydrate as needed.Outcome measures were plasma insulin concentration, model-predicted plasma insulin concentration, 2-h postprandial and 3- to 4-h glucose rate-of-change following breakfast after 1 d of closed-loop control, and the need for supplemental carbohydrate in response to nadir hypoglycemia.Plasma insulin levels during closed loop were well correlated with model predictions (R = 0.86). Fasting glucose after 1 d of closed loop was not different from nighttime target (118 ± 9 vs. 110 mg/dl; P = 0.38). Two-hour postbreakfast glucose was 132 ± 16 mg/dl with stable values 3-4 h after the meal (0.03792 ± 0.0884 mg/dl · min, not different from 0; P = 0.68) and at target (97 ± 6 mg/dl, not different from 90; P = 0.28). Three subjects required supplemental carbohydrates after breakfast on d 2 of closed loop.Insulin feedback can be implemented using a model estimate of concentration. Proportional integral derivative control with insulin feedback can achieve a desired breakfast response but still requires supplemental carbohydrate to be delivered in some instances. Studies assessing more optimal control configurations and safeguards need to be conducted.

OBJECTIVE—The most promising β-cell replacement therapy for children with type 1 diabetes is a closed-loop artificial pancreas incorporating continuous glucose sensors and insulin pumps. The Medtronic MiniMed external physiological insulin delivery (ePID) system combines an external pump and sensor with a variable insulin infusion rate algorithm designed to emulate the physiological characteristics of the β-cell. However, delays in insulin absorption associated with the subcutaneous route of delivery inevitably lead to large postprandial glucose excursions. RESEARCH DESIGN AND METHODS—We studied the feasibility of the Medtronic ePID system in youth with type 1 diabetes and hypothesized that small manual premeal “priming” boluses would reduce postprandial excursions during closed-loop control. Seventeen adolescents (aged 15.9 ± 1.6 years; A1C 7.1 ± 0.8%) underwent 34 h of closed-loop control; 8 with full closed-loop (FCL) control and 9 with hybrid closed-loop (HCL) control (premeal priming bolus). RESULTS—Mean glucose levels were 135 ± 45 mg/dl in the HCL group versus 141 ± 55 mg/dl in the FCL group (P = 0.09); daytime glucose levels averaged 149 ± 47 mg/dl in the HCL group versus 159 ± 59 mg/dl in the FCL group (P = 0.03). Peak postprandial glucose levels averaged 194 ± 47 mg/dl in the HCL group versus 226 ± 51 mg/dl in the FCL group (P = 0.04). Nighttime control was similar in both groups (111 ± 27 vs. 112 ± 28 mg/dl). CONCLUSIONS—Closed-loop glucose control using an external sensor and insulin pump provides a means to achieve near-normal glucose concentrations in youth with type 1 diabetes during the overnight period. The addition of small manual priming bolus doses of insulin, given 15 min before meals, improves postprandial glycemic excursions.