Physiologically based pharmacokinetic modeling to predict complex drug-drug interactions: a case study of AZD2327 and its metabolite, competitive and time-dependent CYP3A inhibitors

4-{(R)-(3-Aminophenyl)[ 4-(4-fluorobenzyl)-piperazin-1-yl] methyl}-N, N-diethylbenzamide (AZD2327) is a highly potent and selective agonist of the delta-opioid receptor. AZD2327 and N-deethylated AZD2327 (M1) are substrates of cytochrome P450 3A (CYP3A4) and comprise a complex multiple inhibitory system that causes competitive and time-dependent inhibition of CYP3A4. The aim of the current work was to develop a physiologically based pharmacokinetic (PBPK) model to predict quantitatively the magnitude of CYP3A4 mediated drug-drug interaction with midazolam as the substrate. Integrating in silico, in vitro and in vivo PK data, a PBPK model was successfully developed to simulate the clinical accumulation of AZD2327 and its primary metabolite. The inhibition of CYP3A4 by AZD2327, using midazolam as a probe drug, was reasonably predicted. The predicted maximum concentration (C-max) and area under the concentration-time curve (AUC) for midazolam were increased by 1.75 and 2.45-fold, respectively, after multiple dosing of AZD2327, indicating no or low risk for clinically relevant drug-drug interactions (DDI). These results are in agreement with those obtained in a clinical trial with a 1.4 and 1.5-fold increase in C-max and AUC of midazolam, respectively. In conclusion, this model simulated DDI with less than a two-fold error, indicating that complex clinical DDI associated with multiple mechanisms, pathways and inhibitors (parent and metabolite) can be predicted using a well-developed PBPK model. Copyright (C) 2015 John Wiley & Sons, Ltd.