范围(计算机科学)
药物开发
多样性(控制论)
过程(计算)
药品
计算机科学
风险分析(工程)
管理科学
药品审批
工程伦理学
业务
数据科学
知识管理
医学
过程管理
药理学
经济
人工智能
工程类
操作系统
程序设计语言
作者
Yaning Wang,Hao Zhu,Rajanikanth Madabushi,Qi Liu,Shiew‐Mei Huang,Issam Zineh
摘要
Model‐informed drug development (MIDD) refers to the application of a wide range of quantitative models in drug development to facilitate the decision‐making process. MIDD was formally recognized in Prescription Drug User Fee Act (PDUFA) VI. There have been many regulatory applications of MIDD to address a variety of drug development and regulatory questions. These applications can be broadly classified into four categories: dose optimization, supportive evidence for efficacy, clinical trial design, and informing policy. Case studies, literature papers, and published regulatory documents are reviewed in this article to highlight some common features of these applications in each category. In addition to the further development and investment in these established domains of application, new technology, and areas, such as more mechanistic models, neural network models, and real‐world data/evidence, are gaining attention, and more submissions and experiences are being accumulated to expand the application of model‐based analysis to a wider scope.
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