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在口服药物制剂开发中从体外到体内的相关性:过去二十年的一个截图。

In vitro - In vivo correlation in the development of oral drug formulation: A screenshot of the last two decades.

机构信息

Universidade São Francisco, Programa de Pós-graduação Stricto Sensu em Ciências da Saúde, Bragança Paulista, São Paulo, Brazil.

出版信息

Int J Pharm. 2020 Apr 30;580:119210. doi: 10.1016/j.ijpharm.2020.119210. Epub 2020 Mar 12.

DOI:10.1016/j.ijpharm.2020.119210
PMID:32173499
Abstract

In vitro - in vivo correlation (IVIVC) allows prediction of the in vivo performance of a pharmaceutical product based on its in vitro drug release profiles and can be used to optimize formulations, set dissolution limits, reduce the number of bioequivalence studies during product development, and facilitate certain regulatory decisions. This review article aimed to assess papers published in the last two decades regarding the use of the IVIVC in the development of oral formulations, to demonstrate the scenario in this area, as well as to describe the main characteristics of the assessed studies. A systematic search of PubMed and Web of Science databases was conducted to retrieve articles reporting the use of the IVIVC in the oral formulation development in the period from 1998 to 2018. The qualified studies were abstracted regarding drug name, dosage form, BCS class, in vitro and in vivo data, level of IVIVC, number of formulations, presence of the validation and predictability. The discussion was supported by these data, which allowed to address broadly strengths and weaknesses in this area. Moreover, a large database has been described in this article containing different IVIVC models, with different substances, providing support to scientists interested in this area.

摘要

体外-体内相关性 (IVIVC) 允许基于药物释放曲线预测药物产品的体内性能,可用于优化制剂、设定溶出度限度、减少产品开发过程中的生物等效性研究数量,并促进某些监管决策。本文旨在评估过去二十年中关于 IVIVC 在口服制剂开发中应用的文献,展示该领域的情况,并描述评估研究的主要特征。通过对 PubMed 和 Web of Science 数据库进行系统检索,检索了 1998 年至 2018 年间报道 IVIVC 在口服制剂开发中应用的文章。对合格的研究进行了摘要,包括药物名称、剂型、BCS 分类、体外和体内数据、IVIVC 水平、制剂数量、验证和预测性。讨论基于这些数据,广泛探讨了该领域的优势和劣势。此外,本文还描述了一个大型数据库,其中包含不同的 IVIVC 模型和不同的物质,为对此领域感兴趣的科学家提供了支持。

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