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arXiv · 2201.11267

A Comprehensive Toolbox to Facilitate Quantitative Decision Science in Drug Development: A web-based R shiny application GOahead

Bo Wei·Weibin Zhong·Rong Liu·Alan Wu·Alan Chiang·Michael Branson·Nanxiang Ge
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Abstract

Decision-making is critical at each stage of drug development and making informed and transparent Go/No-Go decisions require a sound quantitative decision framework. We designed and implemented GOahead, a comprehensive web-based tool to improve how statisticians and collaborators could prospectively plan and implement the selected Go/No-Go decision approach in real-time. In the paper, we conducted a comprehensive overview of dual-criterion and confidence interval-based approaches to enable quantitative decision-making. illustrative examples are demonstrated for single and two arms designs in both Bayesian and frequentist frameworks, multiple arms design with MCP-MOD is also demonstrated. GOahead can be found on shinyapps server.

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Bo Wei, Weibin Zhong, Rong Liu, Alan Wu, Alan Chiang, Michael Branson, Nanxiang Ge. 2022-01-27. A Comprehensive Toolbox to Facilitate Quantitative Decision Science in Drug Development: A web-based R shiny application GOahead. https://arxiv.org/abs/2201.11267

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