Predicting drug-drug interactions from in vitro drug metabolism data: challenges and recent advances.
Drug-drug interactions (DDI) caused by the inhibition, inactivation or induction of cytochrome P450 enzymes have been an area of intense research. Models to predict DDI from in vitro data have proven useful and accurate. However, some uncertainty remains over several specific parameters used in these models, such as which value best represents the in vivo concentration of the inhibitor/ inactivator/inducer ([I](in vivo)); the rate of degradation of P450 enzymes in vivo (k(deg)); the fraction of clearance for standard probe drugs mediated by a target enzyme (f(CL(enz))) and, for drugs cleared by CYP3A4, the fraction that passes through the intestine unchanged during absorption (F(g)). It is becoming increasingly apparent that the activity of endogenous drug transporter mechanisms can influence DDI, either by altering the concentration of inhibitors available to drug-metabolizing enzymes or by contributing to drug clearance. The findings of research reported over the past few years to address these uncertainties regarding the use of in vitro data to predict DDI are discussed.
Obach
R Scott
RS
Pfizer, Eastern Point Road, Groton, CT 06340, USA. r.scott.obach@pfizer.com
D000818:Animals; D004341:Drug Evaluation / Q000379:methods*; D004347:Drug Interactions; D006801:Humans; D066298:In Vitro Techniques; D007413:Intestinal Mucosa / Q000378:metabolism; D008099:Liver / Q000378:metabolism; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D010599:Pharmacokinetics; D011237:Predictive Value of Tests
D004364:Pharmaceutical Preparations