title: Progress curve mechanistic modeling approach for assessing time-dependent inhibition of CYP3A4.
abstract: A progress curve method for assessing time-dependent inhibition of CYP3A4 is based on simultaneous quantification of probe substrate metabolite and inhibitor concentrations during the experiment. Therefore, it may overcome some of the issues associated with the traditional two-step method and estimation of inactivation rate (k(inact)) and irreversible inhibition (K(I)) constants. In the current study, seven time-dependent inhibitors were investigated using a progress curve method and recombinant CYP3A4. A novel mechanistic modeling approach was applied to determine inhibition parameters using both inhibitor and probe metabolite data. Progress curves generated for clarithromycin, erythromycin, diltiazem, and N-desmethyldiltiazem were described well by the mechanistic mechanism-based inhibition (MBI) model. In contrast, mibefradil, ritonavir, and verapamil required extension of the model and inclusion of competitive inhibition term for the metabolite. In addition, this analysis indicated that verapamil itself causes minimal MBI, and the formation of inhibitory metabolites was responsible for the irreversible loss of CYP3A4 activity. The k(inact) and K(I) estimates determined in the current study were compared with literature data generated using the conventional two-step method. In the current study, the inactivation efficiency (k(inact)/K(I)) for clarithromycin, ritonavir, and erythromycin were up to 7-fold higher, whereas k(inact)/K(I) for mibefradil, N-desmethyldiltiazem, and diltiazem were, on average, 2- to 4.8-fold lower than previously reported estimates. Use of human liver microsomes instead of recombinant CYP3A4 resulted in 5-fold lower k(inact)/K(I) for erythromycin. In conclusion, the progress curve method has shown a greater mechanistic insight when determining kinetic parameters for MBI in addition to providing a more comprehensive experimental protocol.
authors.affiliation: School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, UK.
authors.forename: Howard J
authors.initials: HJ
authors.lastname: Burt
authors.forename: Henry
authors.initials: H
authors.lastname: Pertinez
authors.forename: Carolina
authors.initials: C
authors.lastname: Säll
authors.forename: Claire
authors.initials: C
authors.lastname: Collins
authors.forename: Ruth
authors.initials: R
authors.lastname: Hyland
authors.forename: J Brian
authors.initials: JB
authors.lastname: Houston
authors.forename: Aleksandra
authors.initials: A
authors.lastname: Galetin
mesh_terms: D001711:Biotransformation; D051544:Cytochrome P-450 CYP3A / Q000378:metabolism; D065692:Cytochrome P-450 CYP3A Inhibitors; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D004791:Enzyme Inhibitors / Q000378:metabolism / Q000494:pharmacology*; D005260:Female; D006801:Humans; D007700:Kinetics; D008099:Liver / Q000187:drug effects* / Q000201:enzymology; D008297:Male; D008862:Microsomes, Liver / Q000201:enzymology; D008954:Models, Biological; D015203:Reproducibility of Results; D013379:Substrate Specificity
chemical_list: D065692:Cytochrome P-450 CYP3A Inhibitors; D004791:Enzyme Inhibitors; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human