Quantitative Prediction of Transporter- and Enzyme-Mediated Clinical Drug-Drug Interactions of Organic Anion-Transporting Polypeptide 1B1 Substrates Using a Mechanistic Net-Effect Model

Quantitative prediction of complex drug-drug interactions (DDIs) involving hepatic transporters and cytochromes P450 (P450s) is challenging. We evaluated the extent of DDIs of nine victim drugs-which are substrates to organic anion-transporting polypeptide 1B1 and undergo P450 metabolism or biliary elimination-caused by five perpetrator drugs, using in vitro data and the proposed extended net-effect model. Hepatobiliary transport and metabolic clearance estimates were obtained from in vitro studies. Of the total of 62 clinical interaction combinations assessed using the net-effect model, 58 (94%) could be predicted within a 2-fold error, with few false-negative predictions. Model predictive performance improved significantly when in vitro active uptake clearance was corrected to recover in vivo clearance. The basic R-value model yielded only 63% predictions within 2-fold error. This study demonstrates that the interactions involving transporter-enzyme interplay need to be mechanistically assessed for quantitative rationalization and prospective prediction.