Nature-Inspired Metaheuristics for Optimizing Dose-Finding and Computationally Challenging Clinical Trial Designs

Authors

Weng Kee Wong
Yevgen Ryeznik
Oleksandr Sverdlov
Ping-Yang Chen
Xinying Fang
Ray-Bing Chen
Shouhao Zhou
J Jack Lee

Publication Date

8-1-2025

Journal

Clinical Trials

DOI

10.1177/17407745251346396

PMID

40650489

PMCID

PMC12318163

PubMedCentral® Posted Date

7-12-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Metaheuristics are commonly used in computer science and engineering to solve optimization problems, but their potential applications in clinical trial design have remained largely unexplored. This article provides a brief overview of metaheuristics and reviews their limited use in clinical trial settings. We focus on nature-inspired metaheuristics and apply one of its exemplary algorithms, the particle swarm optimization (PSO) algorithm, to find phase I/II designs that jointly consider toxicity and efficacy. As a specific application, we demonstrate the utility of PSO in designing optimal dose-finding studies to estimate the optimal biological dose (OBD) for a continuation-ratio model with four parameters under multiple constraints. Our design improves existing designs by protecting patients from receiving doses higher than the unknown maximum tolerated dose and ensuring that the OBD is estimated with high accuracy. In addition, we show the effectiveness of metaheuristics in addressing more computationally challenging design problems by extending Simon's phase II designs to more than two stages and finding more flexible Bayesian optimal phase II designs with enhanced power.

Keywords

Humans, Research Design, Algorithms, Maximum Tolerated Dose, Clinical Trials, Phase I as Topic, Clinical Trials, Phase II as Topic, Dose-Response Relationship, Drug, Continuation-ratio model, dose-finding trial, optimal biological dose, particle swarm optimization, phase I/II trial

Published Open-Access

yes

Recommended Citation

Wong, Weng Kee; Ryeznik, Yevgen; Sverdlov, Oleksandr; et al., "Nature-Inspired Metaheuristics for Optimizing Dose-Finding and Computationally Challenging Clinical Trial Designs" (2025). Faculty, Staff and Student Publications. 4680.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/4680