In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development

生物制药 药物开发 生物信息学 决策树 生化工程 鉴定(生物学) 计算机科学 风险分析(工程) 药物发现 生物技术 药品 计算生物学 管理科学 运筹学 医学 药理学 生物信息学 工程类 人工智能 化学 生物 基因 植物 生物化学
作者
Patricia Zane,Hille Gieschen,Elisabeth Kersten,Neil Mathias,Céline Ollier,Pernilla Johansson,An Van Den Bergh,Sandy Van Hemelryck,Andreas Reichel,Andrea Rotgeri,Kerstin Schäfer,Anette Müllertz,Peter Langguth
出处
期刊:European Journal of Pharmaceutics and Biopharmaceutics [Elsevier]
卷期号:142: 222-231 被引量:14
标识
DOI:10.1016/j.ejpb.2019.06.010
摘要

The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interface responsible for lead optimization and candidate selection contributed to an overall picture of how formulation decisions are progressed. A small data set containing compound information from the database designed for the IMI funded OrBiTo project is examined for interrelationships between measured physicochemical, dissolution and relative bioavailability parameters. In vivo behavior of the drug substance and its formulation in First in human (FIH) studies cannot always be well predicted from in vitro and/or in silico tools alone at the time of selection of a new chemical entity (NCE). Early identification of the risks, challenges and strategies to prepare for formulations that provide sufficient preclinical exposure in animal toxicology studies and in FIH clinical trials is needed and represents an essential part of the IMI funded OrBiTo project. This article offers a perspective on the use of in vivo models and biopharmaceutical decision trees in the development of new oral drug products.
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