Drug-Drug Interactions via Mechanism-Based Cytochrome P450 Inactivation: Points to Consider for Risk Assessment from In Vitro Data and Clinical Pharmacologic Evaluation

Abstract

This commentary discusses the approaches to, and key considerations in the in vitro-in vivo extrapolation of drug-drug interactions (DDI) resulting from mechanism-based inactivation (MBI) of cytochrome P450 (CYP) enzymes and clinical pharmacologic implications. In vitro kinetic assessment and prediction of DDI produced via reversible inhibition and MBI rely on operationally and conceptually distinct approaches. DDI risk assessment for inactivators requires estimation of maximal inactivation rate (k(inact)) and inactivator potency (KI) in vitro, that need to be considered in context of the biological turnover rate of the enzyme (kdeg) and clinical exposures of the inactivator (I), respectively, to predict interaction magnitude. Risk assessment cannot be performed by a simple comparison of inactivator potency against in vivo exposure since inactivation is both concentration and time-dependent. MBI contour plots tracking combinations of I:KI and k(inact):k(deg) resulting in identical fold-reductions in intrinsic clearance are proposed as a useful framework for DDI risk assessment. Additionally, substrate-specific factors like fraction of the total clearance of the object drug via the enzyme being inactivated (f(m(CYP) )) and the bioavailability fraction across the intestine for CYP3A substrates (F(G)) are important determinants of interaction magnitude. Sensitivity analysis of predicted DDI magnitude to uncertainty in input parameters is recommended to inform confidence in predictions. The time course of reversal of DDI resulting from CYP inactivation is determined by the half-life of the enzyme which is an important consideration in the design and interpretation of clinical DDI studies with inactivators.

Perpetrators of pharmacokinetic drug–drug interactions arising from altered cytochrome P450 activity: a criteria‐based assessment

“…For example, erlotinib and dasatinib are mechanism-based inactivators of CYP3A [15,16], a characteristic of many important inhibitors of drug metabolism [17,18]. Product information for these drugs indicates minor impact on the clearance of CYP3A substrates [Sprycel® (dasatinib), labelling,Tarceva® (erlotinib) labelling], but these data are not in the public domain.…”

A Combined Model for Predicting CYP3A4 Clinical Net Drug-Drug Interaction Based on CYP3A4 Inhibition, Inactivation, and Induction Determined in Vitro

“…Frequently, mathematical models are also used that enable scaling of these and other pertinent information into a quantitative prediction of the expected magnitude of DDI (typically expressed as an AUC ratio of the object in the presence and absence of the precipitant). Prior work has demonstrated that this approach can indeed yield accurate DDI predictions (Ito et al, 1998(Ito et al, , 2004Mayhew et al, 2000;Wang et al, 2004;Venkatakrishnan and Obach, 2007). However, to date, such quantitative approaches have not been comprehensive in that they assume a singular mechanism of action.…”

“…Many drug-drug interactions (DDIs) result from altering the activities of these enzymes. A considerable effort in the area of drug metabolism is dedicated toward predicting clinical pharmacokinetics and DDIs from in vitro data (Ito et al, 1998(Ito et al, , 2004Mayhew et al, 2000;Wang et al, 2004;Venkatakrishnan and Obach, 2007). The prediction of DDIs based on an assumption of reversible P450 inhibition has been a standard part of preclinical programs in the pharmaceutical industry for many years.…”

An Inhibitory Metabolite Leads to Dose- and Time-Dependent Pharmacokinetics of (R)-N-{1-[3-(4-Ethoxy-phenyl)-4-oxo-3,4-dihydro-pyrido[2,3-d]pyrimidin-2-yl]-ethyl}-N-pyridin-3-yl-methyl-2-(4-trifluoromethoxy-phenyl)-acetamide (AMG 487) in Human Subjects After Multiple Dosing

“…A key parameter used in these models is the inhibitor concentration at the enzyme active site (I u ) (Mayhew et dmd.aspetjournals.org these concentrations cannot be directly measured, surrogates based on plasma levels are often used. Retrospective analysis has shown that C max or average plasma concentrations have been successfully used in predicting the magnitude of DDIs resulting from coadministered inhibitors (Brown et al, 2006;Galetin et al, 2006;Venkatakrishnan and Obach, 2007).…”