Challenges and Opportunities for Improved Drug–Drug Interaction Predictions for Renal OCT2 and MATE1/2‐K Transporters. Issue 3 (25th June 2022)

• Record Type: Journal Article
• Authors: Krishnan, Srinivasan; Ramsden, Diane; Ferguson, Douglas; Stahl, Simone H.; Wang, Joanne; McGinnity, Dermot F.; Hariparsad, Niresh
• Is Part Of: Clinical pharmacology & therapeutics. Volume 112:Issue 3(2022)
• Page Start: 562
• Page End: 572
• Publication Date: 2022-06-25
• Subjects: Pharmacology -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1002/cpt.2666
• Languages: English
• ISSNs: 0009-9236

Abstract

Abstract : Transporters contribute to renal elimination of drugs; therefore drug disposition can be impacted if transporters are inhibited by comedicant drugs. Regulatory agencies have provided guidelines to assess potential drug–drug interaction (DDI) risk for renal organic cation transporter 2 (OCT2) and multidrug and toxin extrusion 1 and 2‐K (MATE1/2‐K) transporters. Despite this, there are challenges with translating in vitro data using currently available tools to obtain a quantitative assessment of DDI risk in the clinic. Given the high number of drugs and new molecular entities showing in vitro inhibition toward OCT2 and/or MATE1/2‐K and the lack of translation to clinically significant effects, it is reasonable to question whether the current in vitro assay design and modeling practice has led to unnecessary clinical evaluation. The aim of this review is to assess and discuss available in vitro and clinical data along with prediction models intended to provide clinical context of risk, including static models proposed by regulatory agencies and physiologically‐based pharmacokinetic models, in order to identify best practices and areas of future opportunity. This analysis highlights that different in vitro assay designs, including substrate and cell systems used, strongly influence the derived concentration of drug producing 50% inhibition values and contribute to high variability observed across laboratories. Furthermore, the lack of sensitive index substrates coupled with specific inhibitors for individual transporters necessitates the use of complex models to evaluate clinical DDI risk.