Chen Cong, Beckman Robert A
Biostatistics and Research Decision Sciences, Merck Research Laboratories (MRL), Upper Gwynedd, PA 19454, USA.
J Biopharm Stat. 2009;19(3):424-36. doi: 10.1080/10543400902800478.
This manuscript discusses optimal cost-effective designs for Phase II proof of concept (PoC) trials. Unlike a confirmatory registration trial, a PoC trial is exploratory in nature, and sponsors of such trials have the liberty to choose the type I error rate and the power. The decision is largely driven by the perceived probability of having a truly active treatment per patient exposure (a surrogate measure to development cost), which is naturally captured in an efficiency score to be defined in this manuscript. Optimization of the score function leads to type I error rate and power (and therefore sample size) for the trial that is most cost-effective. This in turn leads to cost-effective go-no go criteria for development decisions. The idea is applied to derive optimal trial-level, program-level, and franchise-level design strategies. The study is not meant to provide any general conclusion because the settings used are largely simplified for illustrative purposes. However, through the examples provided herein, a reader should be able to gain useful insight into these design problems and apply them to the design of their own PoC trials.
本手稿讨论了用于II期概念验证（PoC）试验的最优成本效益设计。与确证性注册试验不同，PoC试验本质上是探索性的，此类试验的申办者有权选择I型错误率和检验效能。该决策很大程度上取决于每位患者暴露时具有真正有效治疗方法的感知概率（开发成本的替代指标），这自然会体现在本手稿中定义的效率得分中。得分函数的优化会得出试验的I型错误率和检验效能（进而得出样本量），使其最具成本效益。这反过来又会得出用于开发决策的成本效益型通过/不通过标准。该理念被应用于推导最优的试验层面、项目层面和产品线层面的设计策略。本研究并非旨在提供任何一般性结论，因为所使用的设置在很大程度上是为了说明目的而简化的。然而，通过本文提供的示例，读者应该能够对这些设计问题获得有用的见解，并将其应用于自己的PoC试验设计中。
