风险分析(工程)
计算机科学
文档
集合(抽象数据类型)
质量(理念)
匹配(统计)
功能(生物学)
多样性(控制论)
钥匙(锁)
过程管理
数据科学
医学
业务
人工智能
认识论
生物
进化生物学
哲学
病理
计算机安全
程序设计语言
作者
B Levitan,EB Andrews,Alicia Gilsenan,John G. Ferguson,RA Noel,Paul Coplan,Filip Mussen
标识
DOI:10.1038/clpt.2010.280
摘要
The BRAT Framework is a set of flexible processes and tools that provides a structured approach to pharmaceutical benefit-risk decision making in drug development and post approval settings. A work in progress, it consists of six steps that produce representations of key tradeoffs, with appropriate documentation of the rationale for decisions and the assumptions made in their development. This article describes insights, gained from case studies, into the Framework's performance in a variety of constructed benefit-risk scenarios, focusing on a hypothetical example of a triptan for migraine. The scenarios described illustrate the challenges inherent in arriving at many of the regulatory decisions, including obtaining data for matching populations for all outcomes, finding data of consistent quality, addressing correlated outcomes (e.g., elevated liver function tests and hepatitis rates), dealing with rare but serious adverse events (AEs), and understanding and making decisions based on information for many outcomes simultaneously. The Framework provides a structure for organizing, interpreting, and communicating relevant information, including heterogeneity in results and the quality and level of uncertainty of data, in order to facilitate benefit-risk decisions.
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