DIDB has been specifically designed to support pharmaceutical scientists in their assessment of human PK-based drug interactions and drug safety.
Powered by the the expertise of the team at UW Drug Interaction Solutions, DIDB’s preclinical (human in vitro) and clinical (in vivo) datasets have been used for over 20 years by pharmaceutical researchers and regulatory scientists around the world.
Trusted by scientists
Internationally recognized and trusted
DIDB is internationally recognized as an authoritative, unbiased, transparent research tool by over 120 organizations from over 40 countries working in:
- Pharmaceutical companies of all sizes
- Regulatory agencies
- Contract Research Organizations
- Academics institutions
- Non-profit organizations
- Publishers of drug information
- Providers of clinical decision support system
Metabolism and transport drug-drug interactions (DDIs) data were introduced in 1999. DIDB was later expanded with the addition of pharmacogenetics (PGx) data, as well as food-effects studies, organ impairment data, and additional mechanism of PK-based drug interactions.
More data every day
The most curated information available anywhere
DIDB has the largest manually curated collection of qualitative and quantitative preclinical (human in vitro) and clinical (in vivo) information related to various extrinsic and intrinsic factors. These include interacting co-medications, excipients, food products, herbals, tobacco, organ impairment, and genetics, that can affect drug exposure in humans. Its easy-to-use interface allows users to efficiently retrieve the most relevant and up-to-date information from the large body of publications and regulatory documentation.
Drug disposition datasets available in DIDB:
Knowledge and rigor
Important features of DIDB
- All curation activities and editorial tasks are performed in-house.
- Content is updated daily by a team of research scientists with extensive expertise in DDIs and PGx.
- Data and case reports are extracted from peer-reviewed publications as well as recent NDA/BLA reviews and drug labels.
- Inclusion of both clinical and research information allowing in vitro to in vivo extrapolations (IVIVE).
- Inclusion of negative data, critical to identify possible therapeutic options.
- Mechanistic approach: all interactions are characterized based on their mechanism(s) and studies are organized accordingly, allowing a quick retrieval and identification of a drug DDI profile. The understanding of the DDI mechanisms can then be used to make predictions beyond the observed interactions.
- Quantitative approach: DIDB uses standard metrics (changes in drug exposure or oral clearance) across all citations to evaluate the impact of the interaction in the clinic. Citations related to a drug or a group of drugs can then be retrieved based on these changes, allowing differentiation among drugs based on their sensitivity to inhibition/induction, and identification of the best therapeutic options.
- Continuous incorporation of new scientific findings and improvement of the platform functionalities based on user feedback.