Evaluation of a Scenario in Which Estimates of Bioequivalence Are Biased and a Proposed Solution: t(last) (Common)

In bioequivalence (BE) testing, it is the convention to identify t(last) separately for each concentration‐vs‐time profile. Within‐subject differences in t(last) between treatments can arise when assay sensitivity is reached during washout, causing profiles to fall below the limit of quantitation (LOQ) at different sampling times. The resulting t(last) difference may be systematic, due to true differences in exposure, and/or random, due to measurement noise. The conventional profile‐specific t(last) approach assumes that concentrations in the terminal phase are sufficiently low that use of different t(last) values between treatments within a subject causes negligible bias in the AUC(0‐t) geometric mean ratio (GMR). Here we investigate the validity of this assumption. Using concentration‐vs‐time data following oral inhalation of 50 μg salmeterol as an example data set, we conducted simulations to evaluate whether use of different test/reference AUC timeframes arising from a systematic difference in exposure causes sufficient AUC(0‐t) GMR bias to influence the determination of BE. To ensure that results would be relevant to BE testing, we considered only test/reference relative systemic exposures within the BE window (80.00%–125.00%). We show that use of conventional profile‐specific t(last) exaggerates true differences in systemic exposure; the resulting AUC(0‐t) ratios are biased from true relative exposure by an amount large enough to impact the conclusion of BE. Thus, drugs whose concentrations fall below LOQ during washout may fail BE inappropriately using conventional methods. AUC(0‐t) calculated over a common timeframe within each subject (t(last)[common]) minimizes this bias and harmonizes the statistical analysis of BE.