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Physiologically based pharmacokinetic modeling to predict complex drug–drug interactions: a case study of AZD2327 and its metabolite, competitive and time‐dependent CYP3A inhibitors
Author(s) -
Guo Jian,
Zhou Diansong,
Li Yan,
Khanh Bui H.
Publication year - 2015
Publication title -
biopharmaceutics and drug disposition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.419
H-Index - 58
eISSN - 1099-081X
pISSN - 0142-2782
DOI - 10.1002/bdd.1962
Subject(s) - physiologically based pharmacokinetic modelling , pharmacology , metabolite , pharmacokinetics , cyp3a4 , cmax , chemistry , drug , in silico , active metabolite , cyp3a , midazolam , drug interaction , in vivo , drug drug interaction , cytochrome p450 , medicine , biology , biochemistry , enzyme , microbiology and biotechnology , sedation , gene
4‐{( R )‐(3‐Aminophenyl)[4‐(4‐fluorobenzyl)‐piperazin‐1‐yl]methyl}‐ N , N ‐diethylbenzamide (AZD2327) is a highly potent and selective agonist of the δ ‐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 © 2015 John Wiley & Sons, Ltd.