FCCC LOGO Faculty Publications
Yadav J , Korzekwa K , Nagar S
Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A
Mol Pharm. 2018 Apr 10;15(5) :1979-1995
PMID: 29608318    PMCID: PMC5938745    URL: https://www.ncbi.nlm.nih.gov/pubmed/29608318
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Abstract
Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug-drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N-demethyl erythromycin (NDE), norverapamil (NV), and N-desmethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasi-irreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro-in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000146 min(-1), the average fold difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesis-rate constant of 0.00032 min(-1). These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.
Notes
1543-8392 Yadav, Jaydeep Korzekwa, Ken ORCID: http://orcid.org/0000-0002-7119-9200 Nagar, Swati ORCID: http://orcid.org/0000-0003-2667-7063 R01 GM104178/GM/NIGMS NIH HHS/United States R01 GM114369/GM/NIGMS NIH HHS/United States Journal Article United States Mol Pharm. 2018 Apr 10. doi: 10.1021/acs.molpharmaceut.8b00129.