ArticleScientific reports2019
Database of adverse events associated with drugs and drug combinations.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 31 citations in OpenAlex.
- Comprehensive Analysis of Gastrointestinal Injury Induced by Nonsteroidal Anti-Inflammatory Drugs Using Data from FDA Adverse Event Reporting System Database.Pharmaceuticals (Basel, Switzerland) · 2025Article
- HDN-DDI: a novel framework for predicting drug-drug interactions using hierarchical molecular graphs and enhanced dual-view representation learning.BMC bioinformatics · 2025Article
- Network-based estimation of therapeutic efficacy and adverse reaction potential for prioritisation of anti-cancer drug combinations.Computational and structural biotechnology journal · 2025Article
- Characterization of Antineoplastic Agents Inducing Taste and Smell Disorders Using the FAERS Database.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Repurposing proteasome inhibitors for improved treatment of triple-negative breast cancer.Cell death discovery · 2024Article
- Safety comparisons among monoamine oxidase inhibitors against Parkinson's disease using FDA adverse event reporting system.Scientific reports · 2023Article
- Comprehensive Study of Drug-Induced Pruritus Based on Adverse Drug Reaction Report Database.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Identifying Differences in the Performance of Machine Learning Models for Off-Targets Trained on Publicly Available and Proprietary Data Sets.Chemical research in toxicology · 2023Article
- A Standardized Dataset of a Spontaneous Adverse Event Reporting System.Healthcare (Basel, Switzerland) · 2022Article
- Synthetic Lethality through the Lens of Medicinal Chemistry.Journal of medicinal chemistry · 2020Review
- Prevention of Early Alzheimer's Disease by Erinacine A-EnrichedFrontiers in aging neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Due to the aging world population and increasing trend in clinical practice to treat patients with multiple drugs, adverse events (AEs) are becoming a major challenge in drug discovery and public health. In particular, identifying AEs caused by drug combinations remains a challenging task. Clinical trials typically focus on individual drugs rather than drug combinations and animal models are unreliable. An added difficulty is the combinatorial explosion in the number of possible combinations that can be made using the increasingly large set of FDA approved chemicals. We present a statistical and computational technique for identifying AEs caused by two-drug combinations. Taking advantage of the large and increasing data deposited in FDA's postmarketing reports, we demonstrate that the task of predicting AEs for 2-drug combinations is amenable to the Likelihood Ratio Test (LRT). Our pAERS database constructed with LRT contains almost 77 thousand associations between pairs of drugs and corresponding AEs caused solely by drug-drug interactions (DDIs). The DDIs stored in pAERS complement the existing data sets. Due to our stringent statistical test, we expect many of the associations in pAERS to be unrecorded or poorly documented in the literature.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.