Sample size determination for individual bioequivalence inference.

Chieh Chiang,Jen-Pei Liu,Chin-Fu Hsiao,Shyamal D Peddada

doi:10.1371/journal.pone.0109746

Chieh Chiang, Jen-Pei Liu + Show 2 more

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https://doi.org/10.1371/journal.pone.0109746

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Abstract

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.

Highlights

The traditional criterion for evaluation and approval of smallmolecular chemical generic drug products is based on average bioequivalence (ABE). ([1] – [4]) On the other hand, biosimilar drugs and most of targeted drugs are biological products which are fundamentally different from traditional small-molecular chemical generic drugs in size, functional structure, physiochemical properties, impurities, immunogenicity and manufacturing processes
The three horizontal panels are presented by the within-subject variance of the test formulation in a descending order from top to bottom
The difference in within-subject variances between the test and reference formulations is set to be 20.005, 0, and 0.005. It follows that the linearized constant-scaled criterion is a function only of mean difference and the variance of the subject-by-formulation as long as the difference in within-subject variances between the test and reference formulations is a constant

Summary

Introduction

The traditional criterion for evaluation and approval of smallmolecular chemical generic drug products is based on average bioequivalence (ABE). ([1] – [4]) On the other hand, biosimilar drugs and most of targeted drugs are biological products which are fundamentally different from traditional small-molecular chemical generic drugs in size, functional structure, physiochemical properties, impurities, immunogenicity and manufacturing processes. The linearized criterion for IBE evaluation suggested in the U.S FDA guidance is the linear combination of the squared mean difference, variance of subject-by-formulation interaction, and the difference in within-subject variances between the generic and innovative products. Generic and innovative products are claimed to be IBE if the MLS 100(1{a)% upper confidence bound of the linearized criterion is less than zero. Under the two-sequence and four period (264) crossover design, we derive the asymptotic distribution of the MLS 100(1{a)% upper confidence bound and the asymptotic power for sample size determination for the IBE evaluation. Our approach is to determine the sample size to provide the asymptotic power for which the MLS 100(1{a)% upper confidence bound for the IBE criterion smaller than zero is greater than 1{b

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Results

Conclusion