Adjustment of the area under the concentration curve by terminal rate constant for bioequivalence assessment in a parallel-group study of lamotrigine

Proof of Concept in Assignment of Within-Subject Variability During Virtual Bioequivalence Studies: Propagation of Intra-Subject Variation in Gastrointestinal Physiology Using Physiologically Based Pharmacokinetic Modeling

While the concept of ‘Virtual Bioequivalence’ (VBE) using a combination of modelling, in vitro tests and integration of pre-existing data on systems and drugs is growing from its infancy, building confidence on VBE outcomes requires demonstration of its ability not only in predicting formulation-dependent systemic exposure but also the expected degree of population variability. The concept of variation influencing the outcome of BE, despite being hidden with the cross-over nature of common BE studies, becomes evident when dealing with the acceptance criteria that consider the 90% confidence interval (CI) around the relative bioavailability. Hence, clinical studies comparing a reference product against itself may fail due to within-subject variations associated with the two occasions that the individual receives the same formulation. In this proof-of-concept study, we offer strategies to capture the most realistic predictions of CI around the pharmacokinetic parameters by propagating physiological variations through physiologically based pharmacokinetic modelling. The exercise indicates feasibility of the approach based on comparisons made between the simulated and observed WSV of pharmacokinetic parameters tested for a clinical bioequivalence case study. However, it also indicates that capturing WSV of a large array of physiological parameters using backward translation modelling from repeated BE studies of reference products would require a diverse set of drugs and formulations. The current case study of delayed-release formulation of posaconazole was able to declare certain combinations of WSV of physiological parameters as ‘not plausible’. The eliminated sets of WSV values would be applicable to PBPK models of other drugs and formulations.

Evaluation of the estimation and classification performance of NONMEM when applying mixture model for drug clearance

Maximum likelihood estimation of parameters involving mixture model is known to have significant and specific patterns of errors. Population pharmacokinetic (PopPK) modeling using NONMEM is no exception. A few relevant studies on estimation and classification performance were done, but a comprehensive study was not yet available. The current study aims to evaluate performance and likelihood ratio test (LRT)‐based true covariate detection rate when fitting a bimodal mixture of drug clearance (CL) in NONMEM. A large number of PopPK datasets with various settings were simulated and then estimated. The estimates were compared to the simulated values and summarized. The separation between the CL distributions of the two subpopulations is systematically overestimated. The major factor associated with the performance is the change in the minimum objective function value after removing the mixture component (dOFV). Other significant factors include estimated disparity index (DI), estimated mixing proportion, and number of subjects in the dataset. Small dOFV and large estimated DI are associated with the worst performance. Omitting a true mixture resulted in reduced true covariate detection rates. It is recommended that on top of routinely generated standard errors and model diagnostics, dOFV, and other factors when necessary, should be taken into account for the evaluation of performance when fitting mixture model using NONMEM. In addition, when fitting mixture model for CL is intended, the mixture component should be introduced prior to LRT‐based covariate model development for CL.

Evaluation of area under the concentration curve adjusted by the terminal-phase as a metric to reduce the impact of variability in bioequivalence testing

AIM

To quantify the utility of a terminal-phase adjusted area under the concentration curve method in increasing the probability of a correct and conclusive outcome of a bioequivalence (BE) trial for highly variable drugs when clearance (CL) varies more than the volume of distribution (V).

METHODS

Data from a large population of subjects were generated with variability in CL and V, and used to simulate a two-period, two-sequence crossover BE trial. The 90% confidence interval for formulation comparison was determined following BE assessment using the area under the concentration curve (AUC) ratio test, and the proposed terminal-phase adjusted AUC ratio test. An outcome of bioequivalent, nonbioequivalent or inconclusive was then assigned according to predefined BE limits.

RESULTS

When CL varied more than V, the proposed approach enhanced the probability of correctly assigning bioequivalent or nonbioequivalent and reduced the risk of an inconclusive trial. For a hypothetical drug with between-subject variability of 35% for CL and 10% for V, when the true test-reference ratio of bioavailability was 1.15, a crossover study of n = 14 subjects analysed by the proposed method would have 80% or 20% probability of claiming bioequivalent or nonbioequivalent, compared to 22%, 46% or 32% probability of claiming bioequivalent, nonbioequivalent or inconclusive using the standard AUC ratio test.

CONCLUSIONS

The terminal-phase adjusted AUC ratio test represents a simple and readily applicable approach to enhance the BE assessment of drug products when CL varies more than V.

Adjustment of the area under the concentration curve by terminal rate constant for bioequivalence assessment in a parallel-group study of lamotrigine

AIM

A new strength of lamotrigine extended-release formulation unexpectedly failed to show bioequivalence with the existing strengths at the same dose in a parallel-group study. We report the post-hoc analyses conducted to identify the cause and propose an approach for future evaluations in similar situations.

METHODS

A seemingly bimodal distribution of the half-life among the study participants prompted the use of terminal-phase-rate-constant-adjusted area under the concentration curve as the endpoint for bioequivalence assessment. Population pharmacokinetic modelling was also performed to assess the bimodal distribution of apparent clearance and the potential treatment effects on bioavailability.

RESULTS

The cause for failing to achieve bioequivalence appeared to be a biased representation of a bimodal clearance distribution between the groups. The pharmacokinetic modelling with a mixture routine identified two subpopulations: 88% had a mean clearance of 1.99 l h-1 ; 12% had a mean clearance of 0.64 l h-1 . The low-clearance population was unequally represented by 13% and 4% of subjects in the reference and test groups, respectively, and treatment appeared to have no significant effect on oral bioavailability. The bioequivalence comparison using the adjusted area concluded with a 90% confidence interval of 0.91-1.06, suggesting that treatment had no significant effect on bioavailability and the formulations would meet regulatory criteria for bioequivalence.

CONCLUSIONS

The adjustment of the area under the concentration curve adjusted by terminal-phase rate constant should be considered for situational application in bioequivalence assessment when there are multiple clearance subpopulations in a parallel-group study.