ArticleJournal of chemical information and modeling2024
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank.
Article in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
26 citing papers in PubMed, 39 citations in OpenAlex.
- Beyond Molecular Structures: Investigating Demographic Factors in Drug-Induced Cardiotoxicity Prediction Models.Journal of chemical information and modeling · 2026Article
- Drug Safety Assessment Based on Target Affinity, Drug Exposure and Plasma Protein Binding: Drug-Induced Cardiotoxicity from a Translational Pharmacology Perspective.International journal of molecular sciences · 2026Article
- BioMADE: Predicting Torsades de Pointes from molecular structures through biologically informed representations.bioRxiv : the preprint server for biology · 2026Article
- A diffusion model conditioned on compound bioactivity profiles for generating high-content images.Scientific reports · 2026Article
- Counting cells can accurately predict small-molecule bioactivity benchmarks.Nature communications · 2026Article
- predicTox: an integrated database of clinical risk frequencies and human gene expression signatures for cardiotoxic drugs.Database : the journal of biological databases and curation · 2026Article
- Human Cardiac Organoids: Advances and Prospects from Construction to Preclinical Drug Evaluation.Cells · 2025Review
- Article
- Review
- Transfer learning enables discovery of sub-micromolar antibacterials for ESKAPE pathogens from ultra-large chemical spaces.Chemical science · 2025Article
- PKSmart: an open-source computational model to predict intravenous pharmacokinetics of small molecules.Journal of cheminformatics · 2025Article
- Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World.Chemical research in toxicology · 2025Review
- Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks.Communications biology · 2025Article
- Heart-on-a-Miniscope: A Miniaturized Solution for Electrophysiological Drug Screening in Cardiac Organoids.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Cell Painting: a decade of discovery and innovation in cellular imaging.Nature methods · 2025Review
- Article
- Candesartan preserves aortic structure and function in cisplatin-treated rats by upregulating SIRT1/Nrf2/HO-1 signaling and suppressing oxidative stress, TLR-4/NF-κB signaling, and necroptosis.Frontiers in pharmacology · 2025Article
- Quantitative Structure-Activity Relationship Models to Predict Cardiac Adverse Effects.Chemical research in toxicology · 2024Article
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- Improved Detection of Drug-Induced Liver Injury by Integrating PredictedChemical research in toxicology · 2024Article
Corrections and comments
- Update of
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
Drug-induced cardiotoxicity (DICT) is a major concern in drug development, accounting for 10-14% of postmarket withdrawals. In this study, we explored the capabilities of chemical and biological data to predict cardiotoxicity, using the recently released DICTrank data set from the United States FDA. We found that such data, including protein targets, especially those related to ion channels (e.g., hERG), physicochemical properties (e.g., electrotopological state), and peak concentration in plasma offer strong predictive ability for DICT. Compounds annotated with mechanisms of action such as cyclooxygenase inhibition could distinguish between most-concern and no-concern DICT. Cell Painting features for ER stress discerned most-concern cardiotoxic from nontoxic compounds. Models based on physicochemical properties provided substantial predictive accuracy (AUCPR = 0.93). With the availability of omics data in the future, using biological data promises enhanced predictability and deeper mechanistic insights, paving the way for safer drug development. All models from this study are available at https://broad.io/DICTrank_Predictor.
Indexed as
Identifiers
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.