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BOIN Suite: A Software Platform to Design and Implement Novel Early-Phase Clinical Trials
Yanhong Zhou1, Ruitao Lin1, Ying-Wei Kuo1
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
JCO Clinical Cancer Informatics
|January 13, 2021
Summary
A new software suite called Bayesian Optimal Interval (BOIN) makes novel adaptive trial designs accessible for early-phase clinical research. This user-friendly platform enhances drug development efficiency and collaboration by simplifying complex statistical methods.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Pharmaceutical Development
Background:
- Novel Bayesian adaptive designs offer improved efficiency for early-phase clinical trials.
- A significant barrier to adopting these designs is the lack of user-friendly software tools for researchers.
Purpose of the Study:
- To develop an accessible, user-friendly software platform for implementing novel adaptive clinical trial designs.
- To address challenges in early-phase dose-finding studies through innovative software solutions.
Main Methods:
- Developed a web-based software suite using R Shiny.
- The suite, named the Bayesian Optimal Interval (BOIN) suite, incorporates multiple applications for diverse clinical trial settings.
Main Results:
- The BOIN suite supports various trial types: single-agent phase I (with/without prior info), late-onset toxicity, optimal biological dose finding, and drug combination MTD determination.
- Applications share a unified architecture for consistent user experience and adhere to software development standards for accuracy and reproducibility.
- The suite is freely accessible online, requiring only internet access and a web browser.
Conclusions:
- The BOIN suite provides a unified framework for designing diverse early-phase clinical trials.
- This facilitates the adoption of high-performance novel designs, advancing clinical research and drug development.
- It promotes collaboration between biostatisticians and clinicians by disseminating advanced statistical methods through intuitive software.
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