Use of a Double-Transfected System to Predict hOCT2/hMATE1-Mediated Renal Drug-Drug Interactions

Accurate predictions of renal drug-drug interactions (DDIs) mediated by the human organic cation transporter 2 (hOCT2) and multidrug and toxin extrusion proteins (hMATEs) remain challenging. Current DDI evaluation using plasma maximal unbound inhibitor concentrations (Imax,u) and IC50 values determined in single transporter-transfected cells frequently leads to false or overprediction especially for hMATE1. Emerging evidence suggests intracellular unbound inhibitor concentration may be more relevant for hMATE1 inhibition in vivo. However, determination of intrarenal inhibitor concentrations is impractical. Here, we explored the use of hOCT2/hMATE1 double-transfected Madin-Darby canine kidney (MDCK) cells as a new in vitro tool for DDI risk assessment. Our results showed that potent in vitro hMATE1 inhibitors (hydroxychloroquine, brigatinib, and famotidine) failed to inhibit metformin B-to-A flux in the double-transfected system. On the other side, the classic hOCT2/hMATE1 inhibitors, pyrimethamine and cimetidine, dose-dependently inhibited metformin apparent B-to-A permeability (Papp). The different behaviors of these hMATE1 inhibitors in the double-transfected system can be explained by their different ability to gain intracellular access either via passive diffusion or transporter-mediated uptake. A new parameter (IC50,flux) was proposed reflecting the inhibitor's potency on overall hOCT2/hMATE1-mediated tubular secretion. The IC50,flux values significantly differ from the IC50 values determined in single transporter-transfected cells. Importantly, the IC50,flux accurately predicted in vivo DDIs (within 2-fold) when used in a static model. Our data demonstrated that the IC50,flux approach circumvents the need to measure intracellular inhibitor concentrations and more accurately predicted hOCT2/hMATE1-mediated renal DDIs. This system represents a new approach that could be used for improved DDI assessment during drug development. SIGNIFICANCE STATEMENT: This study demonstrated that flux studies in double-transfected MDCK cells and the IC50,flux represents a better approach to assess in vivo DDI potential for the renal organic cation secretion system. This study highlights the importance of inhibitor intracellular accessibility for accurate prediction of hMATE1-mediated renal DDIs. This approach has the potential to identify in vitro hMATE1 inhibitors that are unlikely to result in in vivo DDIs, thus reducing the burden of unnecessary and costly clinical DDI investigations.

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

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.

Transport Turnover Rates for Human OCT2 and MATE1 Expressed in Chinese Hamster Ovary Cells

MATE1 (multidrug and toxin extruder 1) and OCT2 (organic cation transporter 2) play critical roles in organic cation excretion by the human kidney. The transporter turnover rate (TOR) is relevant to understanding both their transport mechanisms and interpreting the in vitro-in vivo extrapolation (IVIVE) required for physiologically-based pharmacokinetic (PBPK) modeling. Here, we use a quantitative western blot method to determine TORs for MATE1 and OCT2 proteins expressed in CHO cells. MATE1 and OCT2, each with a C-terminal V-5 epitope tag, were cell surface biotinylated and the amount of cell surface MATE1 and OCT2 protein was quantified by western analysis, using standard curves for the V5 epitope. Cell surface MATE1 and OCT2 protein represented 25% and 24%, respectively, of the total expression of these proteins in CHO cells. The number of cell surface transporters was ~55 fmol cm^-2 for MATE1 and ~510 fmol cm^-2 for OCT2. Dividing these values into the different J_max values for transport of MPP, metformin, and atenolol mediated by MATE1 and OCT2 resulted in calculated TOR values (±SE, n = 4) of 84.0 ± 22.0 s^-1 and 2.9 ± 0.6 s^-1; metformin, 461.0 ± 121.0 s^-1 and 12.6 ± 2.4 s^-1; atenolol, 118.0 ± 31.0 s^-1, respectively. These values are consistent with the TOR values determined for a variety of exchangers (NHEs), cotransporters (SGLTs, Lac permease), and uniporters (GLUTs, ENTs).