AI 中文总结
制药行业统计学家欧洲联合会CMC统计网络欧洲特别兴趣小组，对‘预期f2’方法进行批判性评估。指出该方法公式无出处、无数学依据、统计属性差且有符号歧义，经调查无科学优势，结论是不推荐用于溶出度曲线比较。
AI 中文摘要
由Noce等人（2020年）和Xu等人（2021年）提出的‘预期f2’（$\hat{f}_{2,\exp}$）方法，已被两个卫生当局指南采用，用于在变异性排除常规相似因子$\hat{f}_2$使用时的溶出度曲线比较。本文由欧洲制药行业统计学家联合会CMC统计网络欧洲特别兴趣小组（EFSPI CMCSNE SIG）的一个工作组撰写，对该方法进行了批判性评估。确定了一些基本问题。首先，$\hat{f}_{2,\exp}$的公式在其支持者引用的参考文献中没有可追溯的来源。Noce等人（2020年）和Xu等人（2021年）将$\hat{f}_{2,\exp}$归因于Shah等人（1998年）和Ma等人（1999年、2000年），但两者都未提及或暗示过它。其次，该公式没有提供数学依据。Shah等人（1998年）减去一个方差项以减少$\hat{f}_2$的向上偏差，而$\hat{f}_{2,\exp}$公式却加上了这个项，从而增加而不是纠正了偏差。美国食品药品监督管理局的统计学家Liu等人（2024年）也指出了这一点。第三，该方法的统计属性较差：对于高度可变的曲线，方差项主导统计量，即使曲线之间的真实差异接近零，功效也很低。当曲线相同时，该方法可能会拒绝等效性。第四，Noce等人（2020年）发表的公式存在符号歧义，使得项的预期分组不明确。这种歧义已经传播到监管指南中。对工作组成员的一项调查旨在引出支持和反对该方法的论据，但未发现有科学意义的优势。EFSPI CMCSNE SIG得出结论，不建议将$\hat{f}_{2,\exp}$用于溶出度曲线比较。
英文摘要
The method called 'expected $f_2$' ($\hat{f}_{2,\exp}$), as proposed by Noce et al. (2020) and Xu et al. (2021), has been adopted in two health authority guidelines for dissolution profile comparison when variability precludes the use of the conventional similarity factor $\hat{f}_2$. This position paper, developed by a working group of the European Federation of Statisticians in the Pharmaceutical Industry CMC Statistical Network Europe Special Interest Group (EFSPI CMCSNE SIG), presents a critical evaluation of this method. Fundamental concerns are identified. First, the formula for $\hat{f}_{2,\exp}$ has no traceable origin in the references cited by its proponents. Noce et al. (2020) and Xu et al. (2021) attribute $\hat{f}_{2,\exp}$ to Shah et al. (1998) and Ma et al. (1999, 2000), but neither mentions nor suggests it. Second, no mathematical justification has been provided for the formula. Where Shah et al. (1998) subtract a variance term to reduce the upward bias of $\hat{f}_2$, the $\hat{f}_{2,\exp}$ formula adds this term, thereby increasing rather than correcting the bias. This has also been noted by FDA statisticians Liu et al. (2024). Third, the method exhibits poor statistical properties: for highly variable profiles, the variance term dominates the statistic, resulting in low power even as the true difference between profiles approaches zero. The method can reject equivalence when profiles are identical. Fourth, the formula as published by Noce et al. (2020) contains a notation ambiguity that renders the intended grouping of terms unclear. This ambiguity has propagated into regulatory guidance. A survey of working group members, designed to elicit arguments both for and against the method, found no scientifically meaningful advantage. The EFSPI CMCSNE SIG concludes that $\hat{f}_{2,\exp}$ should not be recommended for dissolution profile comparison.
Comments16 pages, 1 figure. Position paper of a working group of the European Federation of Statisticians in the Pharmaceutical Industry (EFSPI), CMC Statistical Network Europe Special Interest Group (CMCSNE SIG)
