We have recorded two videos to show how our DIDB editorial team manually and carefully curate data from citations and FDA drug approval packages and present them in DIDB.
The aim of those videos is to provide you with a better understanding of DIDB’s scientific and editorial processes.
The videos are available in DIDB Resource Center. Please note that you must be signed in to access.
In July, we added 137 citations in DIDB, including 33 in vitro and 144 in vivo articles (55 articles published in July 2021), as well as 2 recently approved NDAs. You can check the citations that are recently published and entered in DIDB and all the NDAs/BLAs in DIDB.
As always, feel free to contact us if you have any questions or comments.
Our publication Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients is now available online on the publisher website (free full text).
The Excipient Knowledgebase is provided as an Excel file and can be downloaded from the Supporting Information section.
The lists of sensitive substrates, inhibitors, and inducers, including the file combining all lists, have been updated and are available in the DIDB Resource Center.
As always, feel free to contact us if you have any questions or comments.
The June Newsletter is now available. You can see this and past newsletters (published in 2020 and 2021) in the DIDB Resource Center. This is our last issue as you can now access a list of the latest citations published which have been entered into DIDB (please note that you must be signed in to access).
Do not hesitate to contact us with comments or suggestions.
Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is likely that these effects on co-administered drugs can reach to clinical significance leading to potential adverse effects or loss of efficacy. These risks can be evaluated through use of in silico methods of mechanistic modeling, including approaches, such as population pharmacokinetic (PK) and physiologically-based PK modeling, which require a comprehensive understanding of the compounds to ensure accurate predictions. We established a knowledgebase of the available compound (or substance) and interaction-specific parameters with the goal of providing a single source of physiochemical, in vitro, and clinical PK and interaction data of commonly used excipients. To illustrate the utility of this knowledgebase, a model for cremophor EL was developed and used to hypothesize the potential for CYP3A- and P-gp-based interactions as a proof of concept.
We have initiated a [How to]… Series of 2-min videos, to show how to search, explore, use, some specific content in DIDB. So far, we have recorded videos on combination drugs, racemate and enantiomers, QT interval prolongation, and drug monographs.
If you have in mind any information you find difficult to retrieve in DIDB, feel free to let us know at didbase@uw.edu. We will get back to you and can decide to explain it in a short video.
The videos are available in DIDB Resource Center. Please note that you must be signed in to access.
Senior team members, Dr Jingjing Yu and Dr Cathy Yeung, are instructing a CE course on Principles & Mechanisms of Pharmacokinetic Drug-Drug Interactions for Recently Approved Drugs which provides pharmaceutical scientists and clinical pharmacists with an in-depth understanding of the mechanisms of drug interactions.
This 5-session course was prepared in collaboration with University of Wisconsin-Madison.
To learn more and register, visit here.
Evaluating the potential of new drugs and their metabolites to cause drug‐drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite‐to‐parent area‐under‐the‐curve ratios (AUCM/AUCP), inhibitory potency of parent and metabolites, and clinical drug‐drug interactions (DDI) were collected. 64% of the metabolites quantified in vivo had AUCM/AUCP≥25% and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. While 50% of the metabolites with AUCM/AUCP<25% were also tested in vitro, none of them showed meaningful CYP inhibition potential. The metabolite % plasma total radioactivity cutoff of ≥10% did not appear to add value to metabolite testing strategies. No relationship between metabolite versus parent drug polarity and inhibition potency was observed. Comparison of metabolite and parent maximum concentration (Cmax) divided by inhibition constant Ki values suggested that metabolites can contribute to in vivo DDIs and hence, quantitative prediction of clinical DDI magnitude may require both parent and metabolite data. This systematic analysis of metabolite data for newly approved drugs supports an AUCM/AUCP cutoff of ≥25% to warrant metabolite in vitro CYP screening to adequately characterize metabolite inhibitory DDI potential and support quantitative DDI predictions.
Presented virtually at ASCPT Annual Meeting, March 2021
Katie Owens, Sophie Argon, Jingjing Yu, Isabelle Ragueneau-Majlessi, and colleagues at FDA
Food-effect (FE) and gastric pH-mediated drug-drug interactions (DDIs) are absorption-related. Here. we evaluated of the Biopharmaceutical Classification System (BCS) may be correlated with FE or pH-mediated DDI observed.