Bioequivalence evaluation of sparse sampling pharmacokinetics data using bootstrap resampling method

Abstract

Bioequivalence studies are an essential part of the evaluation of generic drugs. The most common in vivo bioequivalence study design is the two-period two-treatment crossover design. The observed drug concentration-time profile for each subject from each treatment under each sequence can be obtained. AUC (the area under the concentration-time curve) and C (the maximum concentration) are obtained from the observed drug concentration-time profiles for each subject from each treatment under each sequence. However, such a drug concentration-time profile for each subject from each treatment under each sequence cannot possibly be available during the development of generic ophthalmic products since there is only one-time point measured drug concentration of aqueous humor for each eye. Instead, many subjects will be assigned to each of several prespecified sampling times. Then, the mean concentration at each sampling time can be obtained by the simple average of these subjects' observed concentration. One profile of the mean concentration vs. time can be obtained for one product (either the test or the reference product). One AUC value for one product can be calculated from the mean concentration-time profile using trapezoidal rules. This article develops a novel nonparametric method for obtaining the 90% confidence interval for the ratio of AUC and AUC (or C/C) in crossover studies by bootstrapping subjects at each time point with replacement or bootstrapping subjects at all sampling time points with replacement. Here T represents the test product, and R represents the reference product. It also develops a novel nonparametric method for estimating the standard errors (SEs) of AUC and C in parallel studies by bootstrapping subjects treated by the hth product at each time point with replacement or bootstrapping subjects treated by the hth product at all sampling time points with replacement, h = T, R. Then, 90% confidence intervals for AUC/AUC and C/C are obtained from the nonparametric bootstrap resampling samples and are used for the evaluation of bioequivalence study for one-time sparse sampling data.

Hydroxynorketamine Pharmacokinetics and Antidepressant Behavioral Effects of (2,6)- and (5R)-Methyl-(2R,6R)-hydroxynorketamines

“…The experimental design (in which plasma and brain for a single experimental time point came from independent groups of mice, representing a between-group comparison as a function of time) resulted in a single experimentally derived AUC per compound and sex. Thus, to enable the comparison of AUCs between sexes, a previously described bootstrapping method 36 was utilized to estimate the mean and SEM for each AUC. Briefly, to calculate the mean and SEM of the AUC, N = 1000 of 1024 possible combinations were randomly selected to form N time series, and then 1000 AUCs and the corresponding mean and SEM were determined for each sex.…”

A Bioequivalence Study With Pharmacokinetic Endpoints for Azithromycin Eye Drops

“…The PSG guidelines recommend the bootstrapping technique for determining the variability in AUC, C max , and T max when assessing bioequivalence. In previous in vivo ocular pharmacokinetic studies using a similar design, the nonparametric bootstrap methods were successfully used for the pharmacokinetic calculation and bioequivalence evaluation 7,8,23 . In this study, by bootstrapping all participants at each time point with replacement, 90%CIs for the test/reference ratios of the main pharmacokinetic parameters were obtained from the resampling samples, finally contributing to the determination of bioequivalence.…”

Regulating Generic Ophthalmologic Drug Bioequivalence—Envisioning Accessibility for Patients

“…Sparse sampling, that is, a single sample per subject, sometimes gives rise to the need for a large study population and statistical bootstrapping. 18 In addition, the ethnicity and age of study subjects can affect transcorneal drug absorption rates, which gives rise to subject-dependent aqueous humor drug concentrations. 19 Regardless, in vivo PK studies can be very sensitive to support BE or assess potential BE issues due to permissible differences in the formulation, for example, different preservatives.…”