Department of Mathematics, Ruhr-Universität Bochum, Bochum, 44801, Germany.
European Medicines Agency, 30 Churchill Place, Canary Wharf, London, E14 5EU, UK.
Stat Med. 2018 Sep 10;37(20):2968-2981. doi: 10.1002/sim.7689. Epub 2018 Jun 3.
In drug development, comparability of dissolution profiles of 2 different formulations is usually assessed using the similarity factor f . In practice, the drug dissolution profiles are deemed similar if the f exceeds 50, which occurs when a 10% maximum difference in the mean percentage of the dissolved drug at each time point between test and reference formulation is obtained. According to the Guideline on the Investigation of Bioequivalence (CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **) use of the f is however restricted by a set of validity conditions. If some of these conditions are not satisfied, the f is not considered suitable, and alternative statistical methods are needed. In this article, we propose an inferential framework based on the maximum deviation between curves to test the comparability of drug dissolution profiles. The new methodology is applicable regardless whether the validity criteria of the f are met or not. Contrary to the f , this approach also integrates the variability of the measurements over time and not only their average. To benchmark our method, we performed simulations informed by 3 real case studies provided by the European Medicines Agency and extracted from dossiers submitted to the Centralised Procedure for Marketing Authorisation Application. In the scenarios of the simulation study, the new method controlled its type I error rate when the maximum deviation was greater than the similarity acceptance limit of 10%. The power exceeded 80% for small values of the maximum deviation, while the test was more conservative for intermediate ones. Our results were also very robust to sampling variations. Based on these positive findings, we encourage applicants to consider the new maximum deviation-based method as a valid alternative to the f , especially when the validity criteria of the latter are not met.
在药物开发中，通常使用相似因子 f 来评估两种不同制剂的溶出曲线的可比性。在实践中，如果测试和参比制剂在每个时间点的溶出药物的平均百分比的最大差异不超过 10%，则认为药物溶出曲线具有相似性，此时 f 超过 50。根据生物等效性研究指南（CPMP/EWP/QWP/1401/98 Rev. 1/Corr **），f 的使用受到一系列有效性条件的限制。如果这些条件中的一些不满足，则认为 f 不合适，需要使用替代的统计方法。在本文中，我们提出了一种基于曲线间最大偏差的推断框架，用于检验药物溶出曲线的可比性。无论 f 的有效性标准是否得到满足，新方法都适用。与 f 不同，该方法还整合了随时间变化的测量值的变异性，而不仅仅是它们的平均值。为了验证我们的方法，我们根据欧洲药品管理局提供的 3 个真实案例研究以及从集中程序营销授权申请文件中提取的数据进行了模拟。在模拟研究的场景中，当最大偏差大于相似度接受限 10%时，新方法控制了其第一类错误率。当最大偏差较小时，功效超过 80%，而当最大偏差处于中间值时，检验更为保守。我们的结果对抽样变化也非常稳健。基于这些积极的发现，我们鼓励申请人考虑新的基于最大偏差的方法作为 f 的有效替代方法，尤其是当后者的有效性标准不满足时。
