On September 14, 2023, Professor Xiaoying Li from the Institute of Metabolism and Integrative Biology at Fudan University, Associate Professor Ying Chen from the Department of Endocrinology at Zhongshan Hospital affiliated to Fudan University, and Professor Guangyu Wang from Beijing University of Posts and Telecommunications jointly published an article in Nature Medicine entitled “Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial”.

The personalized titration and optimization of insulin regimens for treatment of type 2 diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based reinforcement learning (RL) framework (called RL-DITR), which learns the optimal insulin regimen by analyzing glycemic state rewards through patient model interactions. When evaluated during the development phase for managing hospitalized patients with T2D, RL-DITR achieved superior insulin titration optimization (mean absolute error (MAE) of 1.10 ± 0.03 U) compared to other deep learning models and standard clinical methods. We performed a stepwise clinical validation of the artificial intelligence system from simulation to deployment, demonstrating better performance in glycemic control in inpatients compared to junior and intermediate-level physicians through quantitative (MAE of 1.18 ± 0.09 U) and qualitative metrics from a blinded review. Additionally, we conducted a single-arm, patient-blinded, proof-of-concept feasibility trial in 16 patients with T2D. The primary outcome was difference in mean daily capillary blood glucose during the trial, which decreased from 11.1 (±3.6) to 8.6 (±2.4) mmol L⁻¹ (P < 0.01), meeting the pre-specified endpoint. No episodes of severe hypoglycemia or hyperglycemia with ketosis occurred. These preliminary results warrant further investigation in larger, more diverse clinical studies. ClinicalTrials.gov registration: NCT05409391.

Fig. 1: Schematic illustration of the AI system from development to deployment for dynamic insulin dosage titration for patients with T2D.

Link: https://www.nature.com/articles/s41591-023-02552-9