Mechanisms and clinical relevance of pharmacokinetic-based clinical drug-drug interactions for drugs recently approved by the US Food and Drug Administration

Identification and Quantification of Drugs, Metabolites, Drug Metabolizing Enzymes, and Transporters – Concepts, Methods, and Translational Sciences. Second Edition 2020, Chapter 11, 339-358.


New drug application reviews contain critical drug interaction study results with newly approved drugs tested both as victims and as perpetrators of drug-drug interactions (DDIs). Pharmacokinetic-based DDI data for drugs approved by the US Food and Drug Administration in 2013–2017 (N = 137) were analyzed using the University of Washington Drug Interaction Database. For the largest metabolism- and transporter-based drug interactions, defined as a change in exposure ≥ 5-fold in victim drugs, the mechanisms and clinical relevance were characterized. Consistent with the major role of CYP3A in drug disposition, CYP3A inhibition and induction explained a majority of the observed interactions (new drugs as victims or as perpetrators). However, transporter-mediated interactions were also prevalent, with OATP1B1/1B3 playing a significant role. As victims, 17 and 4 new molecular entities (NMEs) were identified to be sensitive substrates of enzymes and transporters, respectively. When considered as perpetrators, three drugs showed strong inhibition of CYP3A, one was a strong CYP3A inducer, and two showed strong inhibition of transporters (OATP1B1/1B3 and/or BCRP). All DDIs with AUC changes ≥ 5-fold had labeling recommendations in their respective drug labels, contraindicating or limiting the coadministration with known substrates or perpetrators of the enzyme/transporter involved. The majority of sensitive substrates or strong inhibitors were oncology and antiviral treatments, suggesting a significant risk of DDIs in these patient populations for whom therapeutic management is already complex due to poly-therapy. Pharmacogenetic studies and physiologically based pharmacokinetic models were commonly used to assess the drug interaction potential in specific populations and clinical scenarios. Finally, absorption-based DDIs were evaluated in approximately 30% of drug applications, and 14 NMEs had label recommendations based on the results.