Work

POGO: A Method for individualization of Automated Insulin Delivery Systems

Year: 2025

Type: article

Abstract: Over the past few years, automated Insulin Delivery (AID) systems have rapidly revolutionized the management of type 1 diabetes (T1D). As the vast majority of first and second generation AID systems are based on mathematical models, it can be difficult to account for the large variability in insulin needs between patients. Therefore, many AID systems are optimized for an average patient, with limited adaptation to individual insulin requirements. We propose a simple wrapper function, POGO, to adjust an AID system to the insulin needs of any user, by rescaling of the insulin inputs and the controller output linearly based on a ratio of insulin needs. We then demonstrate improvement, in silico, in model prediction and glycemic control performances across a wide range of insulin needs while avoiding the need for complex personalization.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.06.008

Authors: Elliott C. Pryor, Marcela Moscoso-Vasquez, Marc D. Breton

Institution: University of Virginia

Language: English

Topic: Diabetes Management and Research

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

Funders: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases