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Statistical and practical considerations in planning and conduct of dose-optimization trials
Ying Yuan1, Heng Zhou2, Suyu Liu1
1Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Clinical Trials (London, England)
|January 20, 2024
Summary
Project Optimus aims to find the optimal biological dose for better benefit-risk balance. This review explores dose optimization trial designs, offering practical guidance and software tools for implementation.
Area of Science:
- Clinical Pharmacology
- Drug Development
- Biostatistics
Background:
- The U.S. Food and Drug Administration's Project Optimus seeks to redefine drug dose selection.
- Current methods often focus on the maximum tolerated dose (MTD), which may not be optimal for benefit-risk.
- Shifting to an optimal biological dose requires new trial designs and strategies.
Purpose of the Study:
- To provide a comprehensive review of dose-optimization trial designs.
- To discuss the advantages and disadvantages of various design strategies.
- To offer practical guidance for planning and executing dose-optimization studies.
Main Methods:
- Review of existing literature on dose-finding and dose-optimization strategies.
- Analysis of phase 1/2 and 2/3 trial designs for dose optimization.
- Discussion of practical considerations and implementation challenges.
- Presentation of freely available software tools for trial design.
Main Results:
- Dose optimization is more complex than MTD identification, requiring careful consideration of design and implementation.
- Various design strategies, including adaptive and platform trials, can be employed for dose optimization.
- Successful implementation involves careful planning, statistical expertise, and appropriate software support.
Conclusions:
- Project Optimus represents a significant shift towards optimizing drug dosage for improved patient outcomes.
- Implementing dose-optimization trials requires a thorough understanding of different design options and practical challenges.
- Available resources and tools can facilitate the design and execution of these complex trials.
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