Sample size determination for individual bioequivalence inference.

PLoS One

Division of Biometry, Department of Agronomy, National Taiwan University, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.

Published: September 2015

AI Article Synopsis

  • The text discusses how the FDA evaluates individual bioequivalence (IBE) between generic and innovative products using statistical methods based on normal distributions' second moments.
  • It highlights the components of the evaluation criteria, including squared mean differences and variances, and mentions that a specific testing procedure was proposed in the 2001 FDA guidance.
  • The authors derive the asymptotic distribution for sample size determination under a specific crossover design and offer numerical study results to aid in practical applications of IBE evaluation.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4195669PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109746PLOS

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