Division of Biopharmaceutics, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, 20993, USA.
Regulatory affairs, Simulations Plus Inc, 42505 10th Street West, Lancaster, California, 93534, USA.
AAPS J. 2020 May 19;22(4):74. doi: 10.1208/s12248-020-00458-9.
The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product performance decisions as part of drug product life cycle management. Accordingly, the application of mathematical approaches to evaluate dissolution profile similarity is described in regulatory guidance. However, the requirements (e.g., which time points, number of time points, %CV) to apply the widely known similarity factor f and other alternative statistical approaches diverge noticeably across regulatory agencies. In an effort to highlight current practices to assess dissolution profile similarity and to strive towards global harmonization, a workshop entitled "in vitro dissolution similarity assessment in support of drug product quality: what, how, when" was held May 21-22, 2019, at the University of Maryland, Baltimore. This article summarizes key points from the podium presentations and breakout (BO) sessions focusing on (1) contrasting the advantages and disadvantages of several statistical methods; (2) the importance of experimental design for successful similarity evaluation; (3) the value of similarity evaluation in light of clinically relevant specifications; and (4) the need for creating a robust and scientifically appropriate path (e.g., non-prescriptive decision tree) for dissolution profile similarity assessment as a stepping stone for global harmonization.
制药行业和监管机构依赖于溶出度相似性测试来做出关键的产品性能决策，这是药物产品生命周期管理的一部分。因此，监管指南中描述了应用数学方法来评估溶出曲线相似性。然而，在应用广泛使用的相似因子 f 和其他替代统计方法时，各监管机构的要求（例如，应用哪些时间点、时间点数量、%CV）存在明显差异。为了突出目前评估溶出曲线相似性的实践，并努力实现全球协调，2019 年 5 月 21 日至 22 日，在马里兰大学巴尔的摩分校举行了题为“支持药物产品质量的体外溶出度相似性评估：是什么、如何、何时”的研讨会。本文总结了专题介绍和分组讨论的要点，重点讨论了：（1）几种统计方法的优缺点对比；（2）成功进行相似性评估的实验设计的重要性；（3）根据临床相关规格进行相似性评估的价值；（4）需要建立一个稳健且科学合理的路径（例如，非规定性决策树）来进行溶出度相似性评估，作为全球协调的垫脚石。
