ArticleScientific data2022
A reference set of clinically relevant adverse drug-drug interactions.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Contrastive learning of adverse events to provide effective and interpretable vector representations for machine-assisted pharmacovigilance.Briefings in bioinformatics · 2026Article
- Assessing Associations of Three Types of Higher-Risk Medication Use and Mortality in Older Adults.Journal of the American Geriatrics Society · 2026Article
- MCSG: A Method for Simultaneous Disproportionality Analysis and Background Rate Estimation in Large Pharmacovigilance Databases.Drug safety · 2026Article
- BEACON: predicting side effects and therapeutics outcomes to drugs by Bridging knowlEdge grAph with CONtextual language model.bioRxiv : the preprint server for biology · 2026Article
- Development of a Drug Safety Signal Detection Reference Set Using Japanese Safety Information.Therapeutic innovation & regulatory science · 2025Article
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- Detection Algorithms for Simple Two-Group Comparisons Using Spontaneous Reporting Systems.Drug safety · 2024Review
- Developing RxNorm Extension: A Step Toward Global Drug Data Harmonization in Observational Drug Research.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Article
- Avapritinib Carries the Risk of Drug InteractionCurrent drug metabolism · 2024Article
- Exploring the impact of design criteria for reference sets on performance evaluation of signal detection algorithms: The case of drug-drug interactions.Pharmacoepidemiology and drug safety · 2023Article
- The curse and blessing of abundance-the evolution of drug interaction databases and their impact on drug network analysis.GigaScience · 2022Article
- A reference set of clinically relevant adverse drug-drug interactions.Scientific data · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The accurate and timely detection of adverse drug-drug interactions (DDIs) during the postmarketing phase is an important yet complex task with potentially major clinical implications. The development of data mining methodologies that scan healthcare databases for drug safety signals requires appropriate reference sets for performance evaluation. Methodologies for establishing DDI reference sets are limited in the literature, while there is no publicly available resource simultaneously focusing on clinical relevance of DDIs and individual behaviour of interacting drugs. By automatically extracting and aggregating information from multiple clinical resources, we provide a scalable approach for generating a reference set for DDIs that could support research in postmarketing safety surveillance. CRESCENDDI contains 10,286 positive and 4,544 negative controls, covering 454 drugs and 179 adverse events mapped to RxNorm and MedDRA concepts, respectively. It also includes single drug information for the included drugs (i.e., adverse drug reactions, indications, and negative drug-event associations). We demonstrate usability of the resource by scanning a spontaneous reporting system database for signals of DDIs using traditional signal detection algorithms.
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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.