A one-size-fits-all artificial pancreas for people with type 1 diabetes based on physiological insight and feedback control

TL;DR

This paper introduces a universal, model-free artificial pancreas system for type 1 diabetes that automatically adjusts insulin without individual customization, based on physiological data and feedback control, demonstrating high efficacy in virtual trials.

Contribution

The study presents a novel, universally applicable artificial pancreas algorithm that requires no personalized tuning, using physiological insights and feedback control for effective glucose regulation.

Findings

Achieved over 87% time in target glucose range in virtual trials.

Nearly 89% of virtual patients met glycemic targets.

System performs well across a large, diverse virtual population.

Abstract

We propose a model-free artificial pancreas (AP) for people with type 1 diabetes. The algorithmic parameters are tuned to a virtual population of 1,000,000 individuals, and the AP repeatedly estimates the basal and bolus insulin requirements necessary for maintaining normal blood glucose levels. Therefore, the AP can be used without healthcare personnel or engineers customizing the algorithm to each user. The estimates are based on bodyweight, measurements from a continuous glucose monitor (CGM), and estimates of the meal carbohydrate contents. In a virtual clinical trial with all 1,000,000 individuals (i.e., a Monte Carlo closed-loop simulation), the AP achieves a mean time in range of more than 87% and almost 89% of the participants satisfy several glycemic targets.