Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
JCO Clin Cancer Inform. 2021 Jan;5:91-101. doi: 10.1200/CCI.20.00122.
Using novel Bayesian adaptive designs has great potential to improve the efficiency of early-phase clinical trials. A major barrier for clinical researchers to adopt novel designs is the lack of easy-to-use software. Our purpose is to develop a user-friendly software platform to implement novel clinical trial designs that address various challenges in early-phase dose-finding trials.
We used to develop a web-based software platform to facilitate the use of recent novel adaptive designs.
We developed a web-based software suite, called Bayesian optimal interval (BOIN) suite, which includes R Shiny applications to handle various clinical settings, including single-agent phase I trials with and without prior information, trials with late-onset toxicity, trials to find the optimal biological dose based on risk-benefit trade-off, and drug combination trials to find a single maximum tolerated dose (MTD) or the MTD contour. The applications are built using the same software architecture to ensure the best and a uniform user experience, and they are developed using a proven software development standard operating procedure to ensure accuracy, robustness, and reproducibility. The suite is freely available with internet access and a web browser without the need of installing any other software.
The BOIN suite allows clinical researchers to design various types of early-phase clinical trials under a unified framework. This work is extremely important because it not only advances the clinical research and drug development by facilitating the use of novel trial designs with optimal performance but also enhances collaborations between biostatisticians and clinicians by disseminating novel statistical methodology to broader scientific communities through user-friendly software. The BOIN suite establishes a KISS principle: keep it simple, but smart.
使用新颖的贝叶斯自适应设计具有提高早期临床试验效率的巨大潜力。临床研究人员采用新颖设计的主要障碍是缺乏易于使用的软件。我们的目的是开发一个用户友好的软件平台，以实施解决早期剂量发现试验中各种挑战的新临床试验设计。
我们使用 来开发一个基于网络的软件平台，以促进最近新颖自适应设计的使用。
我们开发了一个基于网络的软件套件，称为贝叶斯最优区间（BOIN）套件，它包括 R Shiny 应用程序，用于处理各种临床环境，包括有/无先验信息的单药 I 期试验、迟发性毒性试验、基于风险-效益权衡寻找最佳生物学剂量的试验，以及寻找单一最大耐受剂量（MTD）或 MTD 轮廓的药物组合试验。这些应用程序使用相同的软件架构构建，以确保最佳和统一的用户体验，并且它们使用经过验证的软件开发标准操作程序开发，以确保准确性、鲁棒性和可重复性。该套件可通过互联网访问和网络浏览器免费获得，无需安装任何其他软件。
BOIN 套件允许临床研究人员在统一框架下设计各种类型的早期临床试验。这项工作非常重要，因为它不仅通过使用具有最佳性能的新颖试验设计来推进临床研究和药物开发，而且还通过向更广泛的科学界传播新颖的统计方法，通过用户友好的软件增强统计学家和临床医生之间的合作。BOIN 套件确立了一个 KISS 原则：保持简单，但要聪明。
