Model-based Pre-clinical Trials for Medical Devices Using Statistical Model Checking

TL;DR

This paper introduces a model-based pre-clinical trial framework utilizing statistical model checking to enhance medical device validation, allowing broader hypothesis testing with guaranteed significance, as demonstrated on implantable cardioverter defibrillators.

Contribution

It presents a novel framework combining physiological modeling and statistical model checking for pre-clinical trials, supplementing traditional clinical trials with broader hypothesis testing capabilities.

Findings

Broader hypotheses can be tested with guaranteed statistical significance.

The framework effectively evaluates implantable cardioverter defibrillators.

Automated adjudication improves trial efficiency.

Abstract

Clinical trials are considered as the golden standard for medical device validation. However, many sacrifices have to be made during the design and conduction of the trials due to cost considerations and partial information, which may compromise the significance of the trial results. In this paper, we proposed a model-based pre-clinical trial framework using statistical model checking. Physiological models represent disease mechanism, which enable automated adjudication of simulation results. Sampling of the patient parameters and hypothesis testing are performed by statistical model checker. The framework enables a broader range of hypothesis to be tested with guaranteed statistical significance, which are useful complements to the clinical trials. We demonstrated our framework with a pre-clinical trial on implantable cardioverter defibrillators.