Aligning Insulin Therapy with Individual Preferences: A Multi-objective Decision Support System

Despite advances in automatic insulin delivery systems, therapy optimization in type 1 diabetes remains constrained by one-size-fits-all strategies that don’t account for individual patient preferences. This work presents a novel approach that leverages the University of Virginia Replay Simulator (UVA-RS) within a multi-objective optimization framework to address this limitation. This method enables the systematic exploration of trade-offs between competing objectives in diabetes management, such as reducing time in hypoglycemia range versus reducing time in hyperglycemia. By generating patient-specific digital twins and visualizing the Pareto front of possible outcomes, the proposed approach allows patients and healthcare providers to identify therapy configurations that best suit individual preferences and needs. Initial results demonstrate the feasibility of visualizing and selecting among different treatment configurations based on individual risk tolerance and management priorities.