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Generating Model Integrated Evidence for Generic Drug Development and Assessment
Author(s) -
Zhao Liang,
Kim MyongJin,
Zhang Lei,
Lionberger Robert
Publication year - 2019
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.1282
Subject(s) - drug development , risk analysis (engineering) , drug , food and drug administration , computer science , bioequivalence , regulatory science , management science , pharmacology , medicine , engineering , pharmacokinetics , pathology
Quantitative methods and modeling ( QMM ) covers a broad spectrum of tool sets, of which physiologically based models and quantitative clinical pharmacology are most critical for generic drugs. QMM has been increasingly applied by the US Food and Drug Administration ( FDA ) to facilitating generic drug development and review, and has played a critical role in the modernization of bioequivalence ( BE ) assessment, especially for locally acting drug products, complex products of other types, and modified‐release solid oral dosage forms. QMM has aided the development of novel BE methods, in vitro –only BE approaches, and risk‐based evaluations. The future of QMM is model integrated evidence or virtual BE studies that can potentially provide pivotal information for generic drug approval. In summary, QMM is indispensable in modernizing generic drug development, BE assessment, and regulatory decision makings. Regulatory examples demonstrate how QMM can be used in modernizing generic drug development, addressing challenges in BE assessment, and supporting regulatory decision making.