Quantitative Prediction of Renal Transporter-Mediated Clinical Drug-Drug Interactions

Kidney plays a critical role in the elimination of xenobiotics. Drug-drug interactions (DDIs) via inhibition of renal organic anion (OAT) and organic cation (OCT) transporters have been observed in the clinic. This study examined the quantitative predictability of renal transporter-mediated clinical DDIs based on basic and mechanistic models. In vitro transport and clinical pharmacokinetics parameters were used to quantitatively predict DDIs of victim drugs when coadministrated with OAT or OCT inhibitors, probenecid and cimetidine, respectively. The predicted changes in renal clearance (CLr) and area under the plasma concentration-time curve (AUC) were comparable to that observed in clinical studies. With probenecid, basic modeling predicted 61% cases within 25% and 94% cases within SO% of the observed CLr changes in clinic. With cimetidine, basic modeling predicted 61% cases within 25% and 92% cases within 50% of the observed CLr changes in clinic. Additionally, the mechanistic model predicted 54% cases within 25% and 92% cases within 50% of the observed AUC changes with probenecid. Notably, the magnitude of AUC changes attributable to the renal DDIs is generally less than 2-fold, unlike the DDIs associated with inhibition of CYPs and/or hepatic uptake transporters. The models were further used to evaluate the renal DDIs of Pfizer clinical candidates/drugs, and the overall predictability demonstrates their utility in the drug discovery and development settings.