title: Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically Based Pharmacokinetic Model.
abstract: An orally available multiple tyrosine kinase inhibitor, crizotinib (Xalkori), is a CYP3A substrate, moderate time-dependent inhibitor, and weak inducer. The main objectives of the present study were to: 1) develop and refine a physiologically based pharmacokinetic (PBPK) model of crizotinib on the basis of clinical single- and multiple-dose results, 2) verify the crizotinib PBPK model from crizotinib single-dose drug-drug interaction (DDI) results with multiple-dose coadministration of ketoconazole or rifampin, and 3) apply the crizotinib PBPK model to predict crizotinib multiple-dose DDI outcomes. We also focused on gaining insights into the underlying mechanisms mediating crizotinib DDIs using a dynamic PBPK model, the Simcyp population-based simulator. First, PBPK model-predicted crizotinib exposures adequately matched clinically observed results in the single- and multiple-dose studies. Second, the model-predicted crizotinib exposures sufficiently matched clinically observed results in the crizotinib single-dose DDI studies with ketoconazole or rifampin, resulting in the reasonably predicted fold-increases in crizotinib exposures. Finally, the predicted fold-increases in crizotinib exposures in the multiple-dose DDI studies were roughly comparable to those in the single-dose DDI studies, suggesting that the effects of crizotinib CYP3A time-dependent inhibition (net inhibition) on the multiple-dose DDI outcomes would be negligible. Therefore, crizotinib dose-adjustment in the multiple-dose DDI studies could be made on the basis of currently available single-dose results. Overall, we believe that the crizotinib PBPK model developed, refined, and verified in the present study would adequately predict crizotinib oral exposures in other clinical studies, such as DDIs with weak/moderate CYP3A inhibitors/inducers and drug-disease interactions in patients with hepatic or renal impairment.
authors.affiliation: Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, San Diego, California shinji.yamazaki@pfizer.com.
authors.forename: Shinji
authors.initials: S
authors.lastname: Yamazaki
authors.affiliation: Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, San Diego, California.
authors.forename: Theodore R
authors.initials: TR
authors.lastname: Johnson
authors.affiliation: Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, San Diego, California.
authors.forename: Bill J
authors.initials: BJ
authors.lastname: Smith
mesh_terms: D000328:Adult; D000077547:Crizotinib; D018592:Cross-Over Studies; D051544:Cytochrome P-450 CYP3A / Q000097:blood*; D004347:Drug Interactions / Q000502:physiology; D005260:Female; D005544:Forecasting; D006801:Humans; D007654:Ketoconazole / Q000008:administration & dosage / Q000097:blood*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011720:Pyrazoles / Q000008:administration & dosage / Q000097:blood*; D011725:Pyridines / Q000008:administration & dosage / Q000097:blood*; D012293:Rifampin / Q000008:administration & dosage / Q000097:blood*; D013379:Substrate Specificity / Q000502:physiology
chemical_list: D011720:Pyrazoles; D011725:Pyridines; D000077547:Crizotinib; C104464:CYP3A protein, human; D051544:Cytochrome P-450 CYP3A; D007654:Ketoconazole; D012293:Rifampin