ArticleScientific reports2015
3D pharmacophoric similarity improves multi adverse drug event identification in pharmacovigilance.
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 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Article
- An Early Adverse Drug Event Detection Approach with False Discovery Rate Control.medRxiv : the preprint server for health sciences · 2023Article
- Considerations and challenges for sex-aware drug repurposing.Biology of sex differences · 2022Review
- A compound attributes-based predictive model for drug induced liver injury in humans.PloS one · 2020Article
- Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports.BMC medical informatics and decision making · 2019Article
- Drug Side-Effect Prediction Via Random Walk on the Signed Heterogeneous Drug Network.Molecules (Basel, Switzerland) · 2019Article
- Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach.Molecules (Basel, Switzerland) · 2018Article
- Use of antihistamines and risk of ventricular tachyarrhythmia: a nested case-control study in five European countries from the ARITMO project.European journal of clinical pharmacology · 2017Article
- Computational Drug Target Screening through Protein Interaction Profiles.Scientific reports · 2016Article
- Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.Journal of cheminformatics · 2016Article
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Authors and funding
3 authors.
Funding
Abstract
Adverse drugs events (ADEs) detection constitutes a considerable concern in patient safety and public health care. For this reason, it is important to develop methods that improve ADE signal detection in pharmacovigilance databases. Our objective is to apply 3D pharmacophoric similarity models to enhance ADE recognition in Offsides, a pharmacovigilance resource with drug-ADE associations extracted from the FDA Adverse Event Reporting System (FAERS). We developed a multi-ADE predictor implementing 3D drug similarity based on a pharmacophoric approach, with an ADE reference standard extracted from the SIDER database. The results showed that the application of our 3D multi-type ADE predictor to the pharmacovigilance data in Offsides improved ADE identification and generated enriched sets of drug-ADE signals. The global ROC curve for the Offsides ADE candidates ranked with the 3D similarity score showed an area of 0.7. The 3D predictor also allows the identification of the most similar drug that causes the ADE under study, which could provide hypotheses about mechanisms of action and ADE etiology. Our method is useful in drug development, screening potential adverse effects in experimental drugs, and in drug safety, applicable to the evaluation of ADE signals selected through pharmacovigilance data mining.
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