Model-Informed Drug Development: Current US Regulatory Practice and Future Considerations

被引：159
作者：
Wang, Yaning [1 ]
Zhu, Hao [1 ]
Madabushi, Rajanikanth [1 ]
Liu, Qi [1 ]
Huang, Shiew-Mei [1 ]
Zineh, Issam [1 ]
机构：
[1] US FDA, Off Clin Pharmacol, Off Translat Sci, Silver Spring, MD 20993 USA
来源：
CLINICAL PHARMACOLOGY & THERAPEUTICS | 2019年 / 105卷 / 04期
关键词：
EDITOR STATISTICAL ISSUES; THOROUGH QT; SCIENCE; OPPORTUNITIES; PHARMACOLOGY; DISEASE; FDA;
D O I：
10.1002/cpt.1363
中图分类号：
R9 [药学];
学科分类号：
1007 ;
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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收藏
页码：899 / 911
页数：13
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