Fully Integrated Artificial Pancreas in Type 1 Diabetes

Abstract

Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous insulin infusion [CSII]), known as artificial pancreas, can help optimize glycemic control in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, and Montpellier. We tested two modular CLC constructs: standard control to range (sCTR), designed to augment pump plus CGM by preventing extreme glucose excursions; and enhanced control to range (eCTR), designed to truly optimize control within near normoglycemia of 3.9–10 mmol/L. The CLC system was fully integrated using automated data transfer CGM→algorithm→CSII. All studies used randomized crossover design comparing CSII versus CLC during identical 22-h hospitalizations including meals, overnight rest, and 30-min exercise. sCTR increased significantly the time in near normoglycemia from 61 to 74%, simultaneously reducing hypoglycemia 2.7-fold. eCTR improved mean blood glucose from 7.73 to 6.68 mmol/L without increasing hypoglycemia, achieved 97% in near normoglycemia and 77% in tight glycemic control, and reduced variability overnight. In conclusion, sCTR and eCTR represent sequential steps toward automated CLC, preventing extremes (sCTR) and further optimizing control (eCTR). This approach inspires compelling new concepts: modular assembly, sequential deployment, testing, and clinical acceptance of custom-built CLC systems tailored to individual patient needs.

Algorithms for a Closed-Loop Artificial Pancreas: The Case for Proportional-Integral-Derivative Control

“…These include the nighttime-only results obtained by Phillip and coauthors 23 using MD-Logic (a type of fuzzy-logic control) and results obtained by Breton and coauthors 24 comparing what the authors refer to as standard control-to-range (sCTR) and enhanced control-to-range (eCTR)-the latter being modified to include an MPC component. While a complete discussion of the relative advantages and disadvantages of controlling to a range versus controlling to a target is beyond the scope of this article, as is any theoretical discussion of fuzzy logic, the results obtained with the approaches are included for completeness.…”

“…4 The IQR of glucose values was higher ( Figure 3A) as was the reported incidence of hypoglycemia (7 events in 27 nights with MD-Logic versus 0 events in 9 nights of control with PID IFB , 4 or 6 events in 35 nights if the first three PID studies [2][3][4] shown in Figure 1 are combined). While the sCTR algorithm 24 had the lowest incidence of nighttime hypoglycemia (Figure 3C), the rate was achieved at the expense of having the highest nighttime glucose IQR ( Figure 3B). The eCTR algorithm reduced the nighttime glucose IQR 24 but did so with a nighttime incidence of hypoglycemia more than twice that observed with MD-Logic 23 or the first three PID studies combined.…”

“…While the sCTR algorithm 24 had the lowest incidence of nighttime hypoglycemia (Figure 3C), the rate was achieved at the expense of having the highest nighttime glucose IQR ( Figure 3B). The eCTR algorithm reduced the nighttime glucose IQR 24 but did so with a nighttime incidence of hypoglycemia more than twice that observed with MD-Logic 23 or the first three PID studies combined. [2][3][4] A comparison of the dinner glucose response with eCTR algorithm 24 with that obtained with PID IFB 4 shows that the eCTR also had an upper IQR well above that obtained with PID IFB despite the two studies having comparable carbohydrate loads (1.08 ± 0.24 g/kg body weight for eCTR versus a median of 59.5 g with a range of 35-103 g for PID; body mass index but not body weight is reported in Reference 24).…”

“…While a complete discussion of the relative advantages and disadvantages of controlling to a range versus controlling to a target is beyond the scope of this article, as is any theoretical discussion of fuzzy logic, the results obtained with the approaches are included for completeness. shows the glucose interquartile ranges (IQRs) obtained with MD-Logic 23 (red-shaded area), eCTR 24 (gray-shaded area), and PID IFB 4 (magenta-shaded area).…”

Multinight “Bedside” Closed-Loop Control for Patients with Type 1 Diabetes

“…Between 2008 and 2012, promising results from inpatient CLC studies were reported by several groups. [3][4][5][6][7][8] A summary can be found in a 2011 review of the artificial pancreas field, pointing out the superiority of CLC over insulin pump therapy in terms of (1) increased time within target glucose range, (2) reduced incidence of hypoglycemia, and (3) better overnight control. 9 The transition of CLC to a wearable outpatient system began in 2012 with the introduction of the Diabetes Assistant (DiAs)-the first wearable CLC system using a smartphone as a computational platform for its control algorithm.…”