The draft guidance newly released by FDA on “Drug-Drug Interaction Assessment of Therapeutics Proteins” is now available in DIDB Resource Center. Please note that you must be signed in to access.
For your information, in addition to small molecules, DIDB also contains drug-drug interaction data for therapeutic proteins extracted from literature and FDA biological license applications (BLAs).
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.
In our new support page, you will find FAQs, brochures, and videos which will take you inside the DIDB to view its content, features and functionality.
For first-time DIDB users and refresher training, you are encouraged to review our updated detailed tutorials on how to use the different in vitro and in vivo queries.
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.
Data entry for drug therapies approved by FDA in 2019 is now complete. Among the 48 drugs (38 NDAs and 10 BLAs) approved last year, 39 (33 NDAs and 6 BLAs) have relevant in vitro and clinical findings related to DDI, PGx, food effect, and/or organ impairment. Drug monographs are also available, summarizing key DDI results, QT, and PK information.
The full list of NDA/BLAs entered in DIDB can be found at https://didb.druginteractionsolutions.org/resources/all-ndas/
Do not hesitate to contact us with comments or suggestions.
DIDB has been updated with the following new features:
Feel free to contact us at didbase@uw.edu if you experience any issues or if you have any questions or suggestions. Your feedback is always greatly valued!
New finalized In Vitro & Clinical Drug Interaction Studies FDA guidances (January 2020) are now available in the DIDB Resource Center. Please note that you must be signed in to access.
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.
The lists of sensitive substrates, inhibitors, and inducers have been updated and are available in the Resource Center.
Note that we are working on improving the consistency of the presentation so you may notice small changes in some of the drug names or therapeutic classes. Also, for the same reason, we are now presenting all changes in exposure as AUC ratios.
Finally, you will find a new Excel file, combining all the information, so that you can search easily using any of the headings (drug name, therapeutic class, CYP…). Any feedback on this new combined file is welcome!
As always, feel free to contact us if you have any questions or comments.
We have changed our domain to match our new name of UW Drug Interaction Solutions. We feel this name change better reflects our expanding activities and offerings.
All old bookmarks and links will still work, they will be redirected to the same page on our new domain.
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