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体内模型和决策树在早期药物开发中的制剂开发中的应用:对当前实践的综述以及对生物制药开发的建议。

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

机构信息

Sanofi U.S., 55 Corporate Drive, Bridgewater, NJ 08807, United States.

Bayer AG, Research & Development, Pharmaceuticals, Müllerstraße 178, 13353 Berlin, Germany.

出版信息

Eur J Pharm Biopharm. 2019 Sep;142:222-231. doi: 10.1016/j.ejpb.2019.06.010. Epub 2019 Jun 21.

Abstract

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.

摘要

利用体内动物模型预测新化学实体性能的能力已经研究了二十多年。制药公司从早期开发阶段就开始使用自己的策略来决定最合适的制剂。本文讨论了 EFPIA 四家合作伙伴(拜耳、勃林格殷格翰、百时美施贵宝和杨森)的生物制药决策树,其中 7 家公司中有 4 家目前没有定义决策树。讨论了每个决策树的优势、劣势和改进机会。负责先导化合物优化和候选物选择的药物发现和开发界面的药代动力学专家和前配方科学家为制剂决策进展的全貌做出了贡献。使用 IMI 资助的 OrBiTo 项目设计的数据库中的化合物信息的小数据集,研究了测定的物理化学、溶解和相对生物利用度参数之间的相互关系。在选择新化学实体 (NCE) 时,药物物质及其制剂在首次人体 (FIH) 研究中的体内行为并不总是可以仅通过体外和/或计算工具很好地预测。需要及早确定风险、挑战以及制定策略,以确保在动物毒理学研究和 FIH 临床试验中提供足够的临床前暴露的制剂,这是 IMI 资助的 OrBiTo 项目的重要组成部分。本文提供了在新口服药物产品开发中使用体内模型和生物制药决策树的观点。

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