Background: MiniMed™ 670G system user-dependent settings influence glycemic outcomes in persons with type 1 diabetes. The ability of a mathematical model-based digital-twin program to personalize and automate user-dependent MiniMed™ 670G settings was assessed.
Method: A small feasibility study recruited experienced MiniMed™ 670G system users (N=19 users, >14yrs) to complete an at-home 3-weeks run-in phase with Auto Mode enabled followed by a 2-weeks study phase. Run-in data were used to generate a digital twin that personalized system settings during the study phase that comprised a non-randomized Auto Mode and Manual Mode arm. System use and glycemic outcomes were assessed.
Results: Personalized Auto Mode (Auto Mode+) reduced the mean(SD) of sensor glucose (SG) from 151.1(12.3)mg/dL to 149.3(11.6)mg/dL and increased time spent in target SG range from 74.0% to 75.9% (Table). Personalized Manual Mode (Manual Mode+) demonstrated a mean SG and TIR of 150.1mg/dL and 67.4%, respectively.
Conclusions: Improved Auto Mode therapy and acceptable Manual Mode (sensor-augmented pump) therapy were observed utilizing a digital-twin program to personalize MiniMed™ 670G system settings in subjects whose glycemic control was excellent at baseline. This is the first demonstration that a digital-twin can successfully automate and personalize insulin pump therapy.
B. Grosman: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic. D. Wu: None. N. Parikh: None. L.J. Lintereur: Employee; Self; Medtronic. N. Schneider: None. R.L. Brazg: None. S.K. Garg: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk A/S, Roche Diagnostics France. Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Medtronic. R. Vigersky: Employee; Self; Medtronic.