ArticlePloS one2020
A compound attributes-based predictive model for drug induced liver injury in humans.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Computational Evaluation of Potential c-Abl Kinase Inhibitors for Parkinson's Disease: QSAR, Docking, Bioisosteric Replacement, ADMET, and MD Simulations.Applied biochemistry and biotechnology · 2025Article
- Machine Learning Models for Predicting Liver Toxicity.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Detecting Novel Ototoxins and Potentiation of Ototoxicity by Disease Settings.Frontiers in neurology · 2021Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug induced liver injury (DILI) is one of the key safety concerns in drug development. To assess the likelihood of drug candidates with potential adverse reactions of liver, we propose a compound attributes-based approach to predicting hepatobiliary disorders that are routinely reported to US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Specifically, we developed a support vector machine (SVM) model with recursive feature extraction, based on physicochemical and structural properties of compounds as model input. Cross validation demonstrates that the predictive model has a robust performance with averaged 70% of both sensitivity and specificity over 500 trials. An independent validation was performed on public benchmark drugs and the results suggest potential utility of our model for identifying safety alerts. This in silico approach, upon further validation, would ultimately be implemented, together with other in vitro safety assays, for screening compounds early in drug development.
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Registered trials
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