Quantitative prediction of transporter-mediated drug-drug interactions using the mechanistic static pharmacokinetic (MSPK) model

Abstract

Guidance/guidelines on drug-drug interactions (DDIs) have been issued in Japan, the United States, and Europe. These guidance/guidelines provide decision trees for conducting metabolizing enzyme-mediated clinical DDI studies; however, the decision trees for transporter-mediated DDIs lack quantitative prediction methods. In this study, the accuracy of a net-effect mechanistic static pharmacokinetics (MSPK) model containing the fraction transported (ft) of transporters was examined to predict transporter-mediated DDIs. This study collected information on 25 oral drugs with new active reagents that were used in clinical DDI studies as perpetrators (42 cases) from drugs approved in Japan between April 2016 and June 2020. The AUCRs (AUC ratios with and without perpetrators) of victim drugs were predicted using the net-effect MSPK model. As a result, 83 and 95% of the predicted AUCRs were within 1.5- and 2-fold error in the observed AUCRs, respectively. In cases where the victims were statins in which pharmacokinetics several transporters are involved, 70 and 91% of the predicted AUCRs were within 1.5- and 2-fold errors, respectively. Therefore, the net-effect MSPK model was applicable for predicting the AUCRs of victims, which are substrates for multiple transporters.