Sample Size Determination for Individual Bioequivalence Inference

Statistical criterion for evaluation of individual bioequivalence (IBE) between generic and innovative products often involves a function of the second moments of normal distributions. Under replicated crossover designs, the aggregate criterion for IBE proposed by the guidance of the U.S. Food and Drug Administration (FDA) contains the squared mean difference, variance of subject-by-formulation interaction, and the difference in within-subject variances between the generic and innovative products. The upper confidence bound for the linearized form of the criterion derived by the modified large sample (MLS) method is proposed in the 2001 U.S. FDA guidance as a testing procedure for evaluation of IBE. Due to the complexity of the power function for the criterion based on the second moments, literature on sample size determination for the inference of IBE is scarce. Under the two-sequence and four-period crossover design, we derive the asymptotic distribution of the upper confidence bound of the linearized criterion. Hence the asymptotic power can be derived for sample size determination for evaluation of IBE. Results of numerical studies are reported. Discussion of sample size determination for evaluation of IBE based on the aggregate criterion of the second moments in practical applications is provided.

仿制药与原研药之间个体生物等效性（individual bioequivalence, IBE）的评价统计准则通常涉及正态分布的二阶矩函数。在重复交叉设计下，美国食品药品监督管理局（U.S. Food and Drug Administration, FDA）指南提出的IBE综合准则包含均差平方、受试者-制剂交互作用方差，以及仿制药与原研药间的受试者内方差之差。2001年FDA指南中提出，采用修正大样本（modified large sample, MLS）法推导得到的准则线性形式的置信上限，作为IBE评价的检验程序。由于基于二阶矩的准则其功效函数较为复杂，目前针对IBE推断的样本量确定相关研究较为匮乏。在两序列四周期交叉设计下，我们推导了该线性化准则置信上限的渐近分布，进而可得到用于IBE评价的样本量确定所需的渐近功效。本文报告了数值研究结果，并讨论了基于二阶矩综合准则的IBE评价样本量确定方法在实际应用中的相关问题。