Received for publication December 2, 2005.
Revised April 4, 2006.
Accepted for publication April 5, 2006.

Stochastic Prediction of CYP3A-Mediated Inhibition of Midazolam Clearance by Ketoconazole

Abstract

Conventional methods to forecast CYP3A mediated drug-drug interactions have not employed stochastic approaches that integrate pharmacokinetic (PK) variability and relevant covariates to predict inhibition in terms of probability and uncertainty. Empirical approaches to predict the extent of inhibition may not account for nonlinear or non-steady-state conditions, such as first-pass effects or accumulation of inhibitor concentration with multiple dosing. A physiologically-based PK model was developed to predict the inhibition of CYP3A by ketoconazole (KTZ), using midazolam (MDZ) as the substrate. The model integrated PK models of MDZ and KTZ, in vitro inhibition kinetics of KTZ and the variability and uncertainty associated with these parameters. This model predicted the time- and dose-dependent inhibitory effect of KTZ on MDZ oral clearance. The predictive performance of the model was validated using the results of 5 published KTZ-MDZ studies. The model improves the accuracy of predicting inhibitory effect of increasing KTZ dosing on MDZ PK by incorporating a saturable KTZ efflux from the site of enzyme inhibition in the liver. The results of simulations utilizing the model supported the KTZ dose of 400 mg once-daily as the optimal regimen to achieve maximum inhibition by KTZ. Sensitivity analyses revealed the most influential variable on the prediction of inhibition was the fractional clearance of MDZ mediated by CYP3A. The model may be used prospectively to improve the quantitative prediction of CYP3A inhibition and aid the optimization of study designs for CYP3A mediated drug-drug interaction studies in drug development.

Key words: clinical pharmacokinetics, CYP3A, drug-drug interactions, first-pass metabolism, hepatic uptake, Monte Carlo simulations, pharmacokinetic/pharmacodynamic modeling, physiologically-based pharmacokinetics

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