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.
J Clin Pharmacol. 2020 Aug; 60(8); 1087-1098.
Published online 2020 Mar 20
Organic anion-transporting polypeptides (OATPs) 1B1 and 1B3 are the primary hepatic transporters responsible for uptake of drugs into the liver and, as such, an area of growing research focus. Currently, evaluation of these transporters as potential mediators of drug-drug interactions (DDIs) is recommended by regulatory agencies worldwide during the drug development process. Despite the growing focus on OATP1B1/1B3 as mediators of DDIs, only 2 drugs are recommended as index inhibitors for use in clinical studies, single-dose rifampin and cyclosporine, each with limitations for the utility of the resulting data. In this study a thorough analysis of the available in vitro and clinical data was conducted to identify drugs that are clinically relevant inhibitors of OATP1B1/1B3 and, from those, to select any novel index inhibitors. A total of 13 drugs and 16 combination products were identified as clinical inhibitors of OATP1B1/1B3, showing significant changes in exposure for sensitive substrates of the transporters, with strong supporting in vitro evidence. Although none of the identified inhibitors qualified as index inhibitors, this study confirmed the utility of cyclosporine and single-dose rifampin as index inhibitors to evaluate the effect of broad, multiple-pathway inhibition and more selective OATP1B1/1B3 inhibition, respectively.
Clin Transl Sci.
Published online 2020 Jan 25
A systematic analysis of the inhibition transporter data available in New Drug Applications of drugs approved by the US Food and Drug Administration (FDA) in 2018 (N = 42) was performed. In vitro‐to‐in vivo predictions using basic models were available for the nine transporters currently recommended for evaluation. Overall, 29 parents and 16 metabolites showed in vitro inhibition of at least one transporter, with the largest number of drugs found to be inhibitors of P‐gp followed by BCRP. The most represented therapeutic areas were oncology drugs and anti‐infective agents, each comprising 31%. Among drugs with prediction values greater than the FDA recommended cutoffs and further evaluated in vivo, 56% showed positive clinical interactions (area under the concentration‐time curve ratio (AUCRs) ≥ 1.25). Although all the observed or simulated inhibitions were weak (AUCRs < 2), seven of the nine interactions (involving five drugs) resulted in labeling recommendations. Interestingly, more than half of the drugs with predictions greater than the cutoffs had no further evaluations, highlighting that current basic models represent a useful, simple first step to evaluate the clinical relevance of in vitro findings, but that multiple other factors are considered when deciding the need for clinical studies. Four drugs had prediction values less than the cutoffs but had clinical evaluations or physiologically‐based pharmacokinetic simulations available. Consistent with the predictions, all of them were confirmed not to inhibit these transporters in vivo (AUCRs of 0.94–1.09). Overall, based on the clinical evaluations available, drugs approved in 2018 were found to have a relatively limited impact on drug transporters, with all victim AUCRs < 2.
Clin Transl Sci. 2020 Jan; 13(1): 47–52.
Published online 2019 Aug 29
As the research into the organic anion transporting polypeptides (OATPs) continues to grow, it is important to ensure that the data generated are accurate and reproducible. In the in vitro evaluation of OATP1B1/1B3 inhibition, there are many variables that can contribute to variability in the resulting inhibition constants, which can then, in turn, contribute to variable results when clinical predictions (R-values) are performed. Currently, the only experimental condition recommended by the US Food and Drug Administration (FDA) is the inclusion of a pre-incubation period.1 To identify other potential sources of variability, a descriptive analysis of available in vitro inhibition data was completed. For each of the 21 substrate/inhibitor pairs evaluated, cell type and pre-incubation were found to have the greatest effect on half-maximal inhibitory concentration (IC50 ) variability. Indeed, when only HEK293 cells and co-incubation conditions were included, the observed variability for the entire data set (highest IC50 /lowest) was reduced from 12.4 to 5.2. The choice of probe substrate used in the study also had a significant effect on inhibitor constant variability. Interestingly, despite the broad range of inhibitory constants identified, these two factors showed little effect on the calculated R-values relative to the FDA evaluation cutoff of 1.1 triggering a clinical evaluation for the inhibitors evaluated. However, because of the small data set available, further research is needed to confirm these preliminary results and define best practice for the study of OATPs.