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Updated: Sep 22, 2025

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Translational drug-interaction corpus
Shijun Zhang1, Hengyi Wu2, Lei Wang1
1Department of Biomedical Informatics, College of Medicine, The Ohio State University, 1585 Neil Ave, Columbus, OH 43210, USA.
Researchers developed a new drug-drug interaction (DDI) corpus for text mining, improving annotation accuracy to 96%. This resource aids in discovering DDIs with translational impact across pharmacokinetic and clinical studies.
Area of Science:
- Pharmacology and Toxicology
- Natural Language Processing
- Bioinformatics
Background:
- Accurate identification of drug-drug interactions (DDIs) with translational impact from in vitro pharmacokinetics (PK), in vivo PK, and clinical outcomes is crucial.
- Existing text mining approaches rely heavily on the quality of annotated corpora, highlighting a need for improved resources.
- Translational research in drug interactions requires robust data for accurate DDI discovery.
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