Adaptive phase I–II clinical trial designs identifying optimal biological doses for targeted agents and immunotherapies

Author:

Zang Yong12ORCID,Guo Beibei3,Qiu Yingjie1ORCID,Liu Hao4,Opyrchal Mateusz5,Lu Xiongbin6

Affiliation:

1. Department of Biostatistics and Health Data Science, School of Medicine, Indiana University, Indianapolis, IN, USA

2. Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA

3. Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA, USA

4. Department of Biostatistics and Epidemiology, Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA

5. Department of Medicine, School of Medicine, Indiana University, Indianapolis, IN, USA

6. Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA

Abstract

Targeted agents and immunotherapies have revolutionized cancer treatment, offering promising options for various cancer types. Unlike traditional therapies the principle of “more is better” is not always applicable to these new therapies due to their unique biomedical mechanisms. As a result, various phase I–II clinical trial designs have been proposed to identify the optimal biological dose that maximizes the therapeutic effect of targeted therapies and immunotherapies by jointly monitoring both efficacy and toxicity outcomes. This review article examines several innovative phase I–II clinical trial designs that utilize accumulated efficacy and toxicity outcomes to adaptively determine doses for subsequent patients and identify the optimal biological dose, maximizing the overall therapeutic effect. Specifically, we highlight three categories of phase I–II designs: efficacy-driven, utility-based, and designs incorporating multiple efficacy endpoints. For each design, we review the dose–outcome model, the definition of the optimal biological dose, the dose-finding algorithm, and the software for trial implementation. To illustrate the concepts, we also present two real phase I–II trial examples utilizing the EffTox and ISO designs. Finally, we provide a classification tree to summarize the designs discussed in this article.

Funder

national institutes of health

R&D Research Competitiveness Sub-program of Louisiana Board of Regents

Ralph W. and Grace M. Showalter Research Trust award

Publisher

SAGE Publications

Subject

Pharmacology,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3