Ekhlaspour, Laya

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70–180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70–180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: −1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (−1.5% [−2.4% to −0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (−8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

OBJECTIVE Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system. RESEARCH DESIGN AND METHODS After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14–72 years; mean HbA1c, 7.1% [54 mmol/mol]) were randomly assigned to CLC (N = 54, Control-IQ) or PLGS (N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70–180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study. RESULTS All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P &lt; 0.001). Time &gt;180 mg/dL was lower in the CLC group than PLGS group (difference = −6.0%; 95% CI −8.4%, −3.7%; P &lt; 0.001) while time &lt;54 mg/dL was similar (0.04%; 95% CI −0.05%, 0.13%; P = 0.41). HbA1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference −0.34% [−3.7 mmol/mol]; 95% CI −0.57% [−6.2 mmol/mol], −0.11% [1.2 mmol/mol]; P = 0.0035). CONCLUSIONS Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS.

OBJECTIVE Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system. RESEARCH DESIGN AND METHODS This protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ≥14 years, and baseline HbA1c &lt;10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)–measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L. RESULTS Between November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC (n = 65) versus SAP (n = 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference −1.7% [95% CI −2.4, −1.0]; P &lt; 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference −3.0% [95% CI −6.1, 0.1]; P &lt; 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device. CONCLUSIONS In meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable.