In silico evaluation of pramlintide dosing algorithms in artificial pancreas systems

TL;DR

This study integrates a pramlintide pharmacokinetics/pharmacodynamics model into a diabetes simulator to evaluate combined insulin and pramlintide control algorithms, showing improved blood glucose regulation in silico.

Contribution

It introduces a novel in silico testing framework for insulin-plus-pramlintide strategies using a recent pharmacological model within an established simulator.

Findings

Improved time in range by up to 10.53% with combined therapy

Validated the model's consistency with clinical trial results

Compared different dosing strategies for pramlintide in artificial pancreas systems

Abstract

Pramlintide's capability to delay gastric emptying has motivated its use in artificial pancreas systems, accompanying insulin as a control action. Due to the scarcity of pramlintide simulation models in the literature, in silico testing of insulin-plus-pramlintide strategies is not widely used. This work incorporates a recent pramlintide pharmacokinetics/pharmacodynamics model into the T1DM UVA/Padova simulator to adjust and validate four insulin-plus-pramlintide control algorithms. The proposals are based on an existing insulin controller and administer pramlintide either as independent boluses or as a ratio of the insulin infusion. The results of the insulin-pramlintide algorithms are compared against their insulin-alone counterparts, showing an improvement in the time in range between 3.00\% and 10.53\%, consistent with results reported in clinical trials in the literature. Future work will focus on individualizing the pramlintide model to the patients' characteristics and evaluating the implemented strategies under more challenging scenarios.