ArticleScientific reports2015
A novel algorithm for analyzing drug-drug interactions from MEDLINE literature.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.Journal of medical Internet research · 2025Article
- Patents on PARP-1 Inhibitors for the Management of Cancer from 2017-2023.Recent patents on anti-cancer drug discovery · 2025Review
- The association between warfarin usage and international normalized ratio increase: systematic analysis of FDA Adverse Event Reporting System (FAERS).The journal of cardiovascular aging · 2023Article
- TP-DDI: A Two-Pathway Deep Neural Network for Drug-Drug Interaction Prediction.Interdisciplinary sciences, computational life sciences · 2022Article
- Drug Combinations: Mathematical Modeling and Networking Methods.Pharmaceutics · 2019Review
- Leveraging genetic interactions for adverse drug-drug interaction prediction.PLoS computational biology · 2019Article
- CuDDI: A CUDA-Based Application for Extracting Drug-Drug Interaction Related Substance Terms from PubMed Literature.Molecules (Basel, Switzerland) · 2019Article
- Are patients with a nasally placed feeding tube at risk of potential drug-drug interactions? A multicentre cross-sectional study.PloS one · 2019Article
- Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning.PloS one · 2018Article
- Impact of Drug Treatment at Neonatal Ages on Variability of Drug Metabolism and Drug-drug Interactions in Adult Life.Current pharmacology reports · 2017Article
- Characterization of the mechanism of drug-drug interactions from PubMed using MeSH terms.PloS one · 2017Article
- Drug combination therapy increases successful drug repositioning.Drug discovery today · 2016Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Drug-drug interaction (DDI) is becoming a serious clinical safety issue as the use of multiple medications becomes more common. Searching the MEDLINE database for journal articles related to DDI produces over 330,000 results. It is impossible to read and summarize these references manually. As the volume of biomedical reference in the MEDLINE database continues to expand at a rapid pace, automatic identification of DDIs from literature is becoming increasingly important. In this article, we present a random-sampling-based statistical algorithm to identify possible DDIs and the underlying mechanism from the substances field of MEDLINE records. The substances terms are essentially carriers of compound (including protein) information in a MEDLINE record. Four case studies on warfarin, ibuprofen, furosemide and sertraline implied that our method was able to rank possible DDIs with high accuracy (90.0% for warfarin, 83.3% for ibuprofen, 70.0% for furosemide and 100% for sertraline in the top 10% of a list of compounds ranked by p-value). A social network analysis of substance terms was also performed to construct networks between proteins and drug pairs to elucidate how the two drugs could interact.
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Registered trials
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