Will the Number of Replicates In Bootstrapped Data Alter the Bioequivalence Results'

The estimation of 90 % parametric confidence intervals (CIs) of mean Cmax and AUCs ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects of test and reference drug are comparable. Bootstrap nonparametric 90 % CIs of formulation effects were estimated with the different replicates (500, 1000, 2000 and 5000) and then compared with the parametric 90 % CIs of the original datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. Currently, the 80 - 125 % rule based upon the parametric 90 % CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, number of replicates in the bootstrapping has significant impact on altering the study results