ArticleClinical pharmacology and therapeutics2021
Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning.
Article in Clinical pharmacology and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.
- Sex Matters: A Comprehensive Comparison of Female and Male Hearts.Frontiers in physiology · 2022Pooled it
- Arrhythmia risk predictions from molecular simulations of cardiac ion channel-drug interactions.Biophysical journal · 2026Article
- Perioperative Arrhythmias: Pathophysiology, Risk Stratification, Management, and Emerging Technologies-A Narrative Review Toward Personalised Care.Journal of personalized medicine · 2026Review
- Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.The Journal of physiology · 2026Review
- Sex-specific virtual population for the prediction and assessment of arrhythmia risk.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- Can in silico models predict drug-induced cardiac risk in vulnerable populations?Toxicology reports · 2026Article
- T-World Virtual Human Cardiomyocyte. I. Development, Validation, and Cell Arrhythmogenesis.Circulation research · 2026Article
- Beat-to-beat variability of ventricular repolarization reveals sex-specific instability and proarrhythmic risk.The Journal of physiology · 2026Article
- Population Modeling Approach for Human Cardiac Arrhythmia Risk Prediction.Circulation. Arrhythmia and electrophysiology · 2026Article
- BMAL1 mediates sex-specific circadian regulation of cardiac ion channels and temporal arrhythmia vulnerability.Heart rhythm · 2026Article
- Toward Standardized Methodologies for Drug-Induced Proarrhythmia Classification: An In Silico Proof of Concept.Computational and structural biotechnology journal · 2026Article
- A multiscale computational model of cardiac electrophysiology for drug-induced pro-arrhythmic risk stratification.Biomedical engineering letters · 2026Article
- Mechanistic insights into sex differences in atrial electrophysiology and arrhythmia vulnerability through sex-specific computational models.The Journal of physiology · 2025Article
- Developing cardiac biomechanical models beyond the clinic: modeling stressors of daily life.Biomechanics and modeling in mechanobiology · 2025Review
- Prediction of TdP Arrhythmia Risk Through Molecular Simulations of Conformation-specific Drug Interactions with the hERG KbioRxiv : the preprint server for biology · 2025Article
- Development and Clinical Validation of a Cross-Sex Translator of ECG Drug Responses.JACC. Clinical electrophysiology · 2025Article
- Sex-specific human electromechanical multiscale in-silico models for virtual therapy evaluation.Journal of molecular and cellular cardiology plus · 2025Article
- A scoping review of artificial intelligence applications in clinical trial risk assessment.NPJ digital medicine · 2025Article
- Cardiac digital twins: a tool to investigate the function and treatment of the diabetic heart.Cardiovascular diabetology · 2025Review
- Digital twin for sex-specific identification of class III antiarrhythmic drugs based on in vitro measurements, computer models, and machine learning tools.PLoS computational biology · 2025Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for all new therapeutic compounds. Unfortunately, these have proven to be poor predictors of torsadogenic risk, and are likely to have prevented safe compounds from reaching clinical phases. Although this has stimulated numerous efforts to define new paradigms for cardiac safety, none of the recently developed strategies accounts for patient conditions. In particular, despite being a well-established independent risk factor for TdP, female sex is vastly under-represented in both basic research and clinical studies, and thus current TdP metrics are likely biased toward the male sex. Here, we apply statistical learning to synthetic data, generated by simulating drug effects on cardiac myocyte models capturing male and female electrophysiology, to develop new sex-specific classification frameworks for TdP risk. We show that (i) TdP classifiers require different features in females vs. males; (ii) male-based classifiers perform more poorly when applied to female data; and (iii) female-based classifier performance is largely unaffected by acute effects of hormones (i.e., during various phases of the menstrual cycle). Notably, when predicting TdP risk of intermediate drugs on female simulated data, male-biased predictive models consistently underestimate TdP risk in women. Therefore, we conclude that pipelines for preclinical cardiotoxicity risk assessment should consider sex as a key variable to avoid potentially life-threatening consequences for the female population.
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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.