DRUG-DRUG INTERACTIONS : CYP 2 D 6 PARADIGM

The success of in vitro derived Ki values for predicting drug-drug interactions in vivo has been mixed. For example, the use of hepatic input concentration of inhibitor has resolved the negative and positive interactions on the qualitative level, eliminating false negative predictions. However, several examples of false positives and a high incidence of over-predictions of true positive interactions indicated a need for incorporation of additional factors. The aim of this study was to investigate the effect of parallel elimination pathways as a possible reason for false positives and over-predictions. Simulation studies indicated that the degree of interaction (assessed by area under the plasma concentration-time curve ratio in the presence and absence of inhibitor) depends largely on the fraction of substrate metabolized by the particular P450 enzyme (fmCYPi) that is inhibited. The current analysis focused on CYP2D6 interactions due to the well documented genetic polymorphism and the ability to estimate fmCYP2D6 readily from in vivo data obtained in extensive and poor metabolizers. Based on either a phenotype study or an alternative regression analysis approach, the fmCYP2D6 values of 0.37 to 0.94 and 0.25 to 0.89, respectively, were obtained for nine substrates. Prediction of 44 drug-drug interaction studies was improved by the combination of parallel pathways of elimination and their susceptibility to inhibition. The overall success of predicting positive and negative interactions was increased from 54% to 84%, and the number of over-predictions was substantially reduced. It is concluded that incorporating parallel pathways provides a valuable step forward in making quantitative predictions of drug-drug interactions from in vitro data. Drug-drug interactions (DDIs) resulting from inhibition of P450mediated drug metabolism by a coadministered drug continue to be a major cause of serious toxicities. The design of in vitro studies to predict the inhibition potential of a drug has benefited from substantial technological advances in recent years, yet the interpretation of the kinetic parameters generated from these studies remains problematic (Houston and Galetin, 2003), and hence there is a lack of confidence in in vivo predictions from in vitro data (Tucker et al., 2001; Bjornsson et al., 2003). A statistically significant increase in the area under the plasma concentration-time curve (AUC) of the victim drug in the presence of inhibitor (administered by multiple oral dosing) is the commonly used metric for an in vivo drug-drug interaction. Assuming that hepatic metabolism of the victim drug by a single pathway is the only route of elimination, the AUC ratio for an orally administered substrate in the presence and absence of inhibitor reflects the ratio of the control and inhibited intrinsic clearances. It is also assumed that the conditions of the “well stirred” liver model apply and that there is no impact of inhibitor on either the fraction absorbed (Fa) or the fraction unbound in plasma (fu) for the substrate. Thus, in theory, the change in clearance, and hence AUC, may be predicted from the inhibitor concentration available to the hepatic enzymes in vivo [I] and the in vitro Ki (Ito et al., 1998, 2004; Yao and Levy 2002). AUCI AUC FaI DI Fa D fuB CLint fuBI CLintI CLint