ArticleNPJ digital medicine2024
Fast and accurate prediction of drug induced proarrhythmic risk with sex specific cardiac emulators.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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
7 citing papers in PubMed.
- Artificial Intelligence for Precision Antiarrhythmic Drug Therapy in Atrial Fibrillation: From Recurrence Prediction to Comparative Treatment Selection.Medicina (Kaunas, Lithuania) · 2026Review
- Insights from electromechanical simulations to assess omecamtiv mecarbil efficacy in heart failure.The Journal of physiology · 2026Article
- 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
- AI-Enabled Reduction of Animal Use in Cardiovascular Translational Medicine: Regulatory and Technological Perspectives.Life (Basel, Switzerland) · 2025Review
- 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
- Digital twins and Big AI: the future of truly individualised healthcare.NPJ digital medicine · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In silico trials for drug safety assessment require many high-fidelity 3D cardiac simulations to predict drug-induced QT interval prolongation, which is often computationally prohibitive. To streamline this process, we developed sex-specific emulators for a fast prediction of QT interval, trained on a dataset of 900 simulations. Our results show significant differences between 3D and 0D single-cell models as risk levels increase, underscoring the ability of 3D modeling to capture more complex cardiac responses. The emulators demonstrated an average error of 4% compared to simulations, allowing for efficient global sensitivity analysis and fast replication of in silico clinical trials. This approach enables rapid, multi-dose drug testing on standard hardware, addressing critical industry challenges around trial design, assay variability, and cost-effective safety evaluations. By integrating these emulators into drug development, we can improve preclinical reliability and advance the practical application of digital twins in biomedicine.
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.