Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results

Abstract

Background: In 2008-2009, the first multinational study was completed comparing closed-loop control (artificial pancreas) to state-of-the-art open-loop therapy in adults with type 1 diabetes mellitus (T1DM).

Methods: The design of the control algorithm was done entirely in silico, i.e., using computer simulation experiments with N=300 synthetic "subjects" with T1DM instead of traditional animal trials. The clinical experiments recruited 20 adults with T1DM at the Universities of Virginia (11); Padova, Italy (6); and Montpellier, France (3). Open-loop and closed-loop admission was scheduled 3-4 weeks apart, continued for 22 h (14.5 h of which were in closed loop), and used a continuous glucose monitor and an insulin pump. The only difference between the two sessions was that insulin dosing was performed by the patient under a physician's supervision during open loop, whereas insulin dosing was performed by a control algorithm during closed loop.

Results: In silico design resulted in rapid (less than 6 months compared to years of animal trials) and cost-effective system development, testing, and regulatory approvals in the United States, Italy, and France. In the clinic, compared to open-loop, closed-loop control reduced nocturnal hypoglycemia (blood glucose below 3.9 mmol/liter) from 23 to 5 episodes (p<.01) and increased the amount of time spent overnight within the target range (3.9 to 7.8 mmol/liter) from 64% to 78% (p=.03).

Conclusions: In silico experiments can be used as viable alternatives to animal trials for the preclinical testing of insulin treatment strategies. Compared to open-loop treatment under identical conditions, closed-loop control improves the overnight regulation of diabetes.

Figure 1

Illustration of open-loop versus closed-loop control in one study participant. The grey curve represents primary CGM data. The grey squares represent reference blood glucose data during admission 1 (open-loop control). The black curve shows primary CGM data, and the black triangles show reference blood glucose data during admission 2 (closed-loop control). The bars on the x axis display insulin delivery prior to initiation of closed-loop control before 21:30 and display insulin boluses suggested by the control algorithm during closed-loop control after 21:30. Despite much higher glucose excursions after dinner immediately prior to initiation of closed-loop control, the control algorithm brings the subject within target and avoids any nocturnal hypoglycemia afterward. At 06:00 during closed-loop control, the sensor lost sensitivity for approximately 30 min; nevertheless, the control algorithm (which uses only sensor but not reference blood glucose data) was robust, canceling one insulin bolus until the sensor stabilized. BG, blood glucose; CHO, carbohydrate.

Figure 2

Summary outcome data. Key parameters of glucose control overnight (upper panels) and following breakfast (lower panels) during open-loop (gray bars) and closed-loop control (black bars). Panel A: percentage of time within the target range (3.9–7.8 mmol/liter) overnight was 64% on open-loop control and 78% on closed-loop control. With N = 20 matched pairs, a Wilcoxon nonparametric test was significant, p = .029, for a directional hypothesis: closed-loop > open-loop. Panel B: the number of hypoglycemic episodes overnight decreased from 23 on open-loop control to 5 on closed-loop control. With N = 20 matched pairs, Wilcoxon nonparametric test was significant, p = .01. Panel C: percentage of time within the target range (3.9–10 mmol/liter) after breakfast was not significantly different between open- and closed-loop control. Panel D: the mean of the maximal blood glucose values following breakfast was not different between open- and closed-loop control. SD, standard deviation.