Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise

Abstract

Background: We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. This constitutes a dynamic adaptation of the controller's parameters in contrast with the widespread AP implementation of individualized fixed controller tuning.

Materials and methods: After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, <70, >180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.

Results: Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), <70 mg/dL (1.5% ± 1.9% vs. 7.8% ± 6.0%), and number of hypoglycemic events (0.6 ± 0.6 vs. 6.3 ± 3.4), all showed statistically significant improvement during AP use compared with the SAP run-in (P < 0.001). On average, the trust index enhanced controller responsiveness to predicted hyper- and hypoglycemia by 26% (P < 0.005).

Conclusions: In this population of well-controlled patients, we conclude that eMPC with trust index AP achieved nearly 90% time in the target glucose range. Additional studies will further validate these results.

Keywords: Artificial pancreas; Automated insulin delivery; Glucose prediction; Hyperglycemia; Hypoglycemia; Type 1 diabetes.

Conflict of interest statement

E.D. has received consulting fees from Insulet; has received research support from Dexcom, Insulet, Roche, Xeris, and Animas; and receives royalty payments on intellectual property related to the MPC algorithm used in this study. F.J.D. is an advisor to Mode AGC; has received research support from Dexcom, Insulet, Roche, and Xeris; and receives royalty payments on intellectual property related to the MPC algorithm used in this study. J.E.P has conducted AP research sponsored by Insulet Corporation, Tandem Diabetes Care, and Bigfoot Biomedical, and has received product support to his institution from Insulet Corporation, Animas, LifeScan, Roche, and Dexcom. J.B.L. is currently an employee of the Insulet Corporation. A.J.L.S, M.C., C.A., and L.E.L. report no competing financial interests.

Figures

FIG. 1.

AP system scheme. Closed-loop system parts and communication channels. AP, artificial pancreas.

FIG. 2.

A 48-h AP session timeline. Subjects started AP use at ∼17:00, then proceeded to the dinner meal at ∼19:00. The next day, ∼3 h after the breakfast meal, subjects did a 1 h outdoor walking session. The lunch meal was served at ∼12:00, with dinner at ∼17:00 on day 2. Subjects ate breakfast and lunch on day 3 while using AP, and were discharged at ∼17:00 day 3. All meals during the study contained between 30 and 90 g carbohydrates, and subjects received a bolus for all meals as per the study protocol.

FIG. 3.

Median and interquartile CGM plot. Timeline of the median CGM of every 5-min interval across all 15 participants in the closed-loop ∼48 h study. Quartile lines are calculated as 25% and 75% percentiles of the CGM at every 5-min samples. CGM, continuous glucose monitor.

FIG. 4.

Individual metric improvement. Every line represents a participant in the AP study. Progress from the SAP run-in week to the AP system can be read from left to right in the plot. Bubble size represents the time spent below 70 mg/dL. The red line and circles represent mean values. SAP, sensor-augmented pump. (Color graphics available at www.liebertonline.com/dia)

FIG. 5.

Box-plot distributions of R̂ and . distributions are shown in the top panels, and Ř at the bottom. Distributions separated by time periods are shown in the left panels, whereas distributions depending on the CGM range are displayed at the right. Median values are in red, interquartile ranges are shown as a blue box, minimum and maximum values as black bars, and outliers in red. Baseline values for each parameter are imposed in pink. (Color graphics available at www.liebertonline.com/dia)