Large-scale Virtual Clinical Trials of Closed-loop Treatments for People with Type 1 Diabetes

TL;DR

This paper introduces a large-scale virtual clinical trial framework for evaluating closed-loop treatments for Type 1 Diabetes, enabling rapid, risk-free testing of algorithms across diverse populations using high-performance simulations.

Contribution

It presents a novel virtual trial methodology using mathematical models and Monte Carlo simulations to assess treatment safety and efficacy before real-world trials.

Findings

Simulated one million participants over 52 weeks in just over 2 hours.

Demonstrated rapid, large-scale evaluation of treatment algorithms.

Enabled comparison of multiple treatment variations efficiently.

Abstract

We propose a virtual clinical trial for assessing the safety and efficacy of closed-loop diabetes treatments prior to an actual clinical trial. Such virtual trials enable rapid and risk-free pretrial testing of algorithms, and they can be used to compare different treatment variations for large and diverse populations. The participants are represented by multiple mathematical models, consisting of stochastic differential equations, and we use Monte Carlo closed-loop simulations to compute detailed statistics of the closed-loop treatments. We implement the virtual clinical trial using high-performance software and hardware, and we present an example trial with two mathematical models of one~million participants over 52~weeks (i.e., two~million simulations), which can be completed in 2~h 9~min.