News

 |  News

DDI Marker Studies Knowledgebase updated

The DDI Marker Studies Knowledgebase (replacing the previous combined and individual lists of CYP/P-gp substrates and perpetrators) has been updated and is available in the DIDB Resource Center.

Note, that we have initiated the gradual expansion of the Knowledgebase with more transporter data beyond P-gp. Thus, in this version, you will find data for BCRP and OATP1B1/1B3. More transporter data will be added throughout the year.

In addition to substrates, inhibitors and inducers of CYPs and transporters, the Knowledgebase provides useful information on the compounds therapeutic class, clinical recommended dosage, pharmacokinetics (e.g. dose proportionality accumulation ratio, time to steady-state), QT prolongation, and NTI characteristics

As always, feel free to contact us if you have any questions or comments.

 |  New features

New features! AUC and Cmax (90% CI) data, PGx-FDA label, and more

DIDB has been updated with the following new features:

  • AUC and Cmax GMRs (90% CI) are now systematically presented in the study results view (when available) and are used to calculate changes in exposure data
  • Links to PGx external resources have been added to pharmacogenetics queries to provide users with additional contextual information
  • New drug characteristic “PGx (FDA label)” highlights drugs with PGx-related recommendations in FDA label
  • Continuous expansion of compound PK parameters

Feel free to contact us if you experience any issues or if you have any questions or suggestions. Your feedback is always greatly valued!

 |  New features

New Name and Additional Data! for the CYP/P-gp Substrates and Perpetrators Lists

Our new “DDI Marker Studies Knowledgebase” (in Excel) is now available in the Resource Center and replaces the previous combined and individual lists of CYP/P-gp substrates and perpetrators.

The Knowledgebase represents a comprehensive list of compounds that are sensitive or moderate sensitive substrates (NEW), inhibitors, or inducers of CYP enzymes (weak-to-strong potency assigned) and the P-gp transporter.

You can generate an individual list of a specific CYP isoform or transporter as shown in the video (at the bottom of the page).

Additionally, the Knowledgebase provides useful information on the compounds therapeutic class, clinical recommended dosage, pharmacokinetics (e.g., dose proportionality, accumulation ratio, time to steady-state), QT prolongation, and NTI characteristics.

The Knowledgebase will be updated quarterly.

Feel free to contact us if you experience any issues or if you have any questions or suggestions. Your feedback is always greatly valued!

 |  News

UW Pharmacy’s Drug Interaction Database, built to promote medication safety, wins national innovation award

2022 marks 20 years of DIDB licensing and the selection by the ASCPT of Dr. René Levy and Dr. Isabelle Ragueneau-Majlessi to receive the 2022 Gary Neil Prize for Innovation in Drug Development.

Read the story here: https://www.washington.edu/news/2022/01/13/uw-pharmacys-drug-interaction-database-built-to-promote-medication-safety-wins-national-innovation-award/

 |  Publications
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Exploring the Relationship of Drug BCS Classification, Food Effect, and Gastric pH-Dependent Drug Interactions

AAPS J. 2021 Dec 27;24(1):16

Abstract

Food effect (FE) and gastric pH-dependent drug-drug interactions (DDIs) are both absorption-related. Here, we evaluated if Biopharmaceutics Classification System (BCS) classes may be correlated with FE or pH-dependent DDIs. Trends in FE data were investigated for 170 drugs with clinical FE studies from the literature and new drugs approved from 2013 to 2019 by US Food and Drug Administration. A subset of 38 drugs was also evaluated to determine whether FE results can inform the need for a gastric pH-dependent DDI study. The results of FE studies were defined as no effect (AUC ratio 0.80-1.25), increased exposure (AUC ratio ≥1.25), or decreased exposure (AUC ratio ≤0.8). Drugs with significantly increased exposure FE (AUC ratio ≥2.0; N=14) were BCS Class 2 or 4, while drugs with significantly decreased exposure FE (AUC ratio ≤0.5; N=2) were BCS Class 1/3 or 3. The lack of FE was aligned with the lack of a pH-dependent DDI for all 7 BCS Class 1 or 3 drugs as expected. For the 13 BCS Class 2 or 4 weak base drugs with an increased exposure FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). Among the 16 BCS Class 2 or 4 weak base drugs with no FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). FE appears to have limited correlation with BCS classes except for BCS Class 1 drugs, confirming that multiple physiological mechanisms can impact FE. Lack of FE does not indicate absence of pH-dependent DDI for BCS Class 2 or 4 drugs.

 |  Publications
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Evaluating the feasibility of performing pharmacogenetic guided-medication therapy management in a retirement community: A prospective, single arm study

J Am Coll Clin Pharm. 2021;1-11
  • doi: 10.1002/jac5.1570
  • Semantic Scholar

    • Abstract

    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.

     |  New features

    New features! and improvement of existing queries

    DIDB has been updated with the following new features:

    • “Citations recently published” and “NDA/BLAs recently enters” can retrieve citations and NDA/BLAs containing PGx data only
    • The above result pages show if the citation or NDA/BLA contains in vitro, in vivo, or PGx content
    • All the “In Vitro Parameter Queries” take multiple compounds
    • All query results now 
      • use the therapeutic class format of presenting two levels, e.g., “Antiemetics ⟶ Neurokinin-1 Receptor Antagonist”
      • both levels of the therapeutic class are links directed to the therapeutic class DDI risk assessment
      • drug names are now links if there is any DDI summary/QT summary/PK profile in their monographs

    Feel free to contact us if you experience any issues or if you have any questions or suggestions. Your feedback is always greatly valued!

     |  News

    Lists of Sensitive Substrates, Inhibitors and Inducers updated

    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.

    A total of 18 drug interactions, involving 13 drugs, were added to the October version or were updated. Nine of these drugs were cancer treatments, including 7 kinase inhibitors, being identified as sensitive substrates or perpetrators of CYP enzymes or the P-gp transporter.

    As always, feel free to contact us if you have any questions or comments.

     |  Publications
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    Pharmacokinetic Drug-Drug Interactions With Drugs Approved by the U.S. Food and Drug Administration in 2020: Mechanistic Understanding and Clinical Recommendations

    Drug Metab Dispos. 2021 Oct7; 47(2); 135-144

    Abstract

    Pharmacokinetic-based drug-drug interaction (DDI) data for drugs approved by the U.S. Food and Drug Administration in 2017 (N = 34) were analyzed using the University of Washington Drug Interaction Database. The mechaniDrug-drug interaction (DDI) data for small molecular drugs approved by the U.S. Food and Drug Administration in 2020 (N = 40) were analyzed using the University of Washington Drug Interaction Database. The mechanism(s) and clinical relevance of these interactions were characterized based on information available in the new drug application reviews. About 180 positive clinical studies, defined as mean area under the curve ratios (AUCRs) {greater than or equal to} 1.25 for inhibition DDIs or pharmacogenetic studies and {less than or equal to} 0.8 for induction DDIs, were then fully analyzed. Oncology was the most represented therapeutic area, including 30% of 2020 approvals. As victim drugs, inhibition and induction of CYP3A explained most of all observed clinical interactions. Three sensitive substrates were identified: avapritinib (CYP3A), lonafarnib (CYP3A), and relugolix (P-gp), with AUCRs of 7.00, 5.07, and 6.25 when co-administered with itraconazole, ketoconazole, and erythromycin, respectively. As precipitants, three drugs were considered strong inhibitors of enzymes (AUCR {greater than or equal to} 5): cedazuridine for cytidine deaminase, and lonafarnib and tucatinib for CYP3A. No drug showed strong inhibition of transporters. No strong inducer of enzymes or transporters was identified. As expected, all DDIs with AUCRs {greater than or equal to} 5 or {less than or equal to} 0.2 and almost all those with AUCRs of 2-5 and 0.2-0.5 triggered dosing recommendations in the drug label. Overall, all 2020 drugs found to be either sensitive substrates or strong inhibitors of enzymes or transporters were oncology treatments, underscoring the need for effective DDI management strategies in cancer patients often receiving poly-therapy. Significance Statement This minireview provides a thorough and specific overview of the most significant pharmacokinetic-based DDI data observed (or expected) with small molecular drugs approved by the U.S. Food and Drug Administration in 2020. It will help to better understand mitigation strategies to manage the DDI risks in the clinic.

     |  Publications
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    Analysis of Drug-Drug Interaction Labeling Language and Clinical Recommendations for Newly approved Drugs Evaluated With Digoxin, Midazolam, and S-Warfarin

    Clin Ther. 2021 Nov;43(11):2032-2039

    Abstract

    To best promote drug tolerability and efficacy in the clinic, data from drug-drug interaction (DDI) evaluations and subsequent translation of the results to DDI prevention and/or management strategies must be incorporated into the US Food and Drug Administration (FDA) product labeling in a consistent manner because differences in language might result in varied interpretations. This analysis aimed to assess the consistency in DDI labeling language in New Drug Applications (NDAs).