title: Prediction of crizotinib-midazolam interaction using the Simcyp population-based simulator: comparison of CYP3A time-dependent inhibition between human liver microsomes versus hepatocytes.
abstract: Crizotinib (Xalkori) is an orally available potent inhibitor of multiple tyrosine kinases, including anaplastic lymphoma kinase and mesenchymal-epithelial transition factor. Objectives of the present study were as follows: 1) to characterize crizotinib time-dependent inhibition (TDI) potency for CYP3A in human liver microsomes (HLM) and cryopreserved human hepatocytes suspended in human plasma (HSP); 2) to characterize crizotinib enzyme induction potency on CYP3A4 in cryopreserved human hepatocytes; 3) to predict crizotinib steady-state plasma concentrations in patients (e.g., autoinhibition and autoinduction) using the mechanistic dynamic model, Simcyp population-based simulator; and 4) to predict a clinical crizotinib-midazolam interaction using the dynamic model as well as the static mathematical model. Crizotinib inactivation constant (K(I)) and maximum inactivation rate constant (k(inact)) for TDI were estimated as, respectively, 0.37 µM and 6.9 h(-1) in HLM and 0.89 µM and 0.78 h(-1) in HSP. Thus, crizotinib inactivation efficiency (k(inact)/K(I)) was ∼20-fold lower in HSP relative to HLM. Crizotinib E(max) and EC(50) for CYP3A4 induction (measured as mRNA expression) were estimated as 6.4- to 29-fold and 0.47 to 3.1 µM, respectively. Based on these in vitro parameters, the predicted crizotinib steady-state area under plasma concentration-time curve (AUC) with HLM-TDI was 2.1-fold higher than the observed AUC, whereas that with HSP-TDI was consistent with the observed result (≤1.1-fold). The increase in midazolam AUC with coadministration of crizotinib (21-fold) was significantly overpredicted using HLM-TDI, whereas the prediction using HSP-TDI (3.6-fold) was consistent with the observed result (3.7-fold). Collectively, the present study demonstrated the value of HSP to predict in vivo CYP3A-mediated drug-drug interaction.
authors.affiliation: Pharmacokinetics, Dynamics, and Metabolism, Pfizer Worldwide Research and Development, San Diego, CA, USA.
authors.forename: Jialin
authors.initials: J
authors.lastname: Mao
authors.forename: Theodore R
authors.initials: TR
authors.lastname: Johnson
authors.forename: Zhongzhou
authors.initials: Z
authors.lastname: Shen
authors.forename: Shinji
authors.initials: S
authors.lastname: Yamazaki
mesh_terms: D019540:Area Under Curve; D001711:Biotransformation; D003198:Computer Simulation; D000077547:Crizotinib; D051544:Cytochrome P-450 CYP3A / Q000235:genetics / Q000378:metabolism; D065692:Cytochrome P-450 CYP3A Inhibitors; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D004790:Enzyme Induction; D004791:Enzyme Inhibitors / Q000097:blood / Q000493:pharmacokinetics / Q000494:pharmacology*; D005260:Female; D006207:Half-Life; D022781:Hepatocytes / Q000187:drug effects* / Q000201:enzymology; D006801:Humans; D006900:Hydroxylation; D008297:Male; D008657:Metabolic Clearance Rate; D008862:Microsomes, Liver / Q000187:drug effects* / Q000201:enzymology; D008874:Midazolam / Q000097:blood / Q000378:metabolism* / Q000493:pharmacokinetics; D008954:Models, Biological; D011720:Pyrazoles / Q000097:blood / Q000493:pharmacokinetics / Q000494:pharmacology*; D011725:Pyridines / Q000097:blood / Q000493:pharmacokinetics / Q000494:pharmacology*; D012333:RNA, Messenger / Q000378:metabolism; D015203:Reproducibility of Results
chemical_list: D065692:Cytochrome P-450 CYP3A Inhibitors; D004791:Enzyme Inhibitors; D011720:Pyrazoles; D011725:Pyridines; D012333:RNA, Messenger; D000077547:Crizotinib; C104464:CYP3A protein, human; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human; D008874:Midazolam