Nature-inspired metaheuristics for optimizing dose-finding and computationally challenging clinical trial designs...University of Pennsylvania 16th Annual Conference on Statistical Issues in Clinical Trials, April 8, 2024, Philadelphia, Pennsylvania

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 se...

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Published in:Clinical Trials Vol. 22; no. 4; pp. 422 - 430
Main Authors: Wong, Weng Kee, Ryeznik, Yevgen, Sverdlov, Oleksandr, Chen, Ping-Yang, Fang, Xinying, Chen, Ray-Bing, Zhou, Shouhao, Lee, J Jack
Format: equations & formulas proceedings tables/charts Journal Article
Published: Sage Publications, Ltd. Aug2025
Online Access:View this record in EBSCOhost
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        atl: Nature-inspired metaheuristics for optimizing dose-finding and computationally challenging clinical trial designs...University of Pennsylvania 16th Annual Conference on Statistical Issues in Clinical Trials, April 8, 2024, Philadelphia, Pennsylvania
      aug:
        au:
          Wong, Weng Kee
          Ryeznik, Yevgen
          Sverdlov, Oleksandr
          Chen, Ping-Yang
          Fang, Xinying
          Chen, Ray-Bing
          Zhou, Shouhao
          Lee, J Jack
        affil: Department of Biostatistics, University of California, Los Angeles, CA, USA
      sug:
        subj:
          Algorithms
          Clinical Trials
          Dose-Response Relationship
          Probability
          Drug Toxicity
          Drug Efficacy
          Toxicity Tests
          Models, Statistical Pennsylvania
          Congresses and Conferences
          Pennsylvania
      ab: 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.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        proceedings
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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