Reimagining the Framework Supporting the Static Analysis of Transporter Drug Interaction Risk; Integrated Use of Biomarkers to Generate Pan‐Transporter Inhibition Signatures

Solute carrier (SLC) transporters present as the loci of important drug–drug interactions (DDIs). Therefore, sponsors generate in vitro half‐maximal inhibitory concentration (IC 50 ) data and apply regulatory agency‐guided “static” methods to assess DDI risk and the need for a formal clinical DDI study. Because such methods are conservative and high false‐positive rates are likely (e.g., DDI study triggered when liver SLC R value ≥ 1.04 and renal SLC maximal unbound plasma ( C max,u )/IC 50 ratio ≥ 0.02), investigators have attempted to deploy plasma‐ and urine‐based SLC biomarkers in phase I studies to de‐risk DDI and obviate the need for drug probe‐based studies. In this regard, it was possible to generate in‐house in vitro SLC IC 50 data for various clinically (biomarker)‐qualified perpetrator drugs, under standard assay conditions, and then estimate “% inhibition” for each SLC and relate it empirically to published clinical biomarker data (area under the plasma concentration vs. time curve (AUC) ratio (AUCR, AUC inhibitor /AUC reference ) and % decrease in renal clearance (ΔCL renal )). After such a “calibration” exercise, it was determined that only compounds with high R values (> 1.5) and C max,u /IC 50 ratios (> 0.5) are likely to significantly modulate liver (AUCR > 1.25) and renal (ΔCL renal > 25%) biomarkers and evoke DDI risk. The % inhibition approach supports integration of liver and renal SLC data and allows one to generate pan‐SLC inhibition signatures for different test perpetrators (e.g., SLC % inhibition ranking). In turn, such signatures can guide the selection of the most appropriate individual (or combinations of) biomarkers for testing in phase I studies.