Predicting OCT2/MATEs-Mediated Drug Interactions in Healthy Volunteers and Patients with Chronic Kidney Disease: Insights from Extended Clearance Concept, Endogenous Biomarkers, and In Vitro Inhibition Studies (Perspectives from the International Transporter Consortium).

Abstract

Organic cation transporter (OCT) 2 and multidrug and toxin extrusion (MATE) transporters play significant roles in the renal secretion of organic cations and drug-drug interactions (DDIs). Recent in vitro studies indicate that the K_i values for OCT2 exhibit substrate dependency and increase in potency with pre-incubation. However, consensus is lacking on whether these factors should be considered in predicting in vivo inhibition. Physiologically based pharmacokinetic models, combined with the extended clearance concept, have been used and are discussed here for OCT2/MATEs probes. In addition to modeling, early clinical studies use endogenous biomarkers to evaluate transporter-mediated DDI risk, with the aim of avoiding unnecessary clinical DDI studies. Identified biomarkers for OCT2/MATEs, such as creatinine, N¹-methylnicotinamide, and N¹-methyladenosine, have proven useful in confirming clinically relevant OCT2/MATEs-mediated DDIs when renal clearance (CLr) is used as an endpoint; their application is discussed further. From a clinical perspective, the intact nephron hypothesis (INH), which postulates that the decrease in CLr in chronic kidney disease (CKD) is proportional to that in nephron numbers, has been proposed. However, reports suggest that the secretion clearance of creatinine and substrates of organic anion transporters (OATs) does not follow this proportionality in patients with CKD. This state-of-the-art review highlights key developments in predicting OCT2/MATEs-mediated DDIs in healthy volunteers and explores the prediction of clinical OCT2/MATEs DDI risk in patients with CKD by comparing substrate-dependent changes in secretion clearance for substrates of OCT2/MATEs and OATs. Recommendations for the prediction of OCT2/MATEs-mediated DDI risk, together with the current knowledge gaps and future directions, are discussed.