Relative contributions of metabolic enzymes to systemic elimination can be estimated from clinical DDI studies: Validation using an in silico approach

Objective: The contribution ratios (CR) of metabolic enzymes to the systemic clearance of a drug can be estimated from in vitro studies. Another feasible approach is to calculate them based on the increase in the area under the time-concentration curve (AUC) caused by the co-administration of a potent and selective inhibitor in a clinical drug-drug interaction (DDI) study. However, some factors, such as the inhibitory potency of the inhibitor and the inhibition of first-pass metabolism, might affect the estimation of CR based on clinical DDI studies. We aimed to validate the accuracy of the DDI-based estimation of CR using an in silico approach. Materials and methods: An in silico DDI study was conducted using a population-based physiological pharmacokinetic simulator to estimate the CR of cytochrome P450 (CYP)3A4 for zolpidem, sildenafil, omeprazole, triazolam, and repaglinide. The ratio of the AUC value seen in the presence of an inhibitor (ketoconazole or itraconazole) to that observed in the absence of the inhibitor (AUC ratio) was also calculated. The CR for CYP3A4 obtained using the simulator (CR_def) were compared with those calculated from the AUC ratio (CR_est). Results: When ketoconazole was used, good correlations between the CR_est and CR_def were obtained for all examined substrates (inconsistencies were seen in < 10% of subjects). CR estimates derived from the AUC ratio were found to be accurate. Some underestimation was observed, possibly due to incomplete inhibition, and some overestimation caused by extensive first-pass metabolism was noted. Conclusion: This study verified that CR obtained from AUC ratios in DDI studies are quite reliable.