Simulation models for in silico testing of closed-loop glucose controllers in type 1 diabetes

Models of glucose regulation have a longstanding history dating back 40 years. Various modelling approaches have been adopted providing models of varied complexity ranging from simple data-driven to more detailed knowledge-driven physiological models. The glucoregulatory models can be useful in the development and refinement of new treatments in diabetes. A validated model is capable to predict patients’ glycaemic responses to new drugs and new technologies. One such promising technology is a wearable artificial pancreas – a minimally invasive closed-loop system for titrating subcutaneous insulin infusion utilising continuous glucose measurements provided by a subcutaneous sensor. Simulation models have the capability to accelerate the development of the artificial pancreas by predicting the outcome of clinical trials with different glucose controllers under different clinical conditions. This review focuses on such simulation models representing virtual populations of subjects with type 1 diabetes.

Section editor:Paolo Vicini – Pfizer Global Research and Development, Department of Pharmacokinetics, Dynamics and Metabolism, San Diego, CA, USA