ArticleBritish journal of pharmacology2013
Computational assessment of drug-induced effects on the electrocardiogram: from ion channel to body surface potentials.
Article in British journal of pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- In silico modelling of multi-electrode arrays for enhancing cardiac drug testing on hiPSC-CM heterogeneous tissues.The Journal of physiology · 2026Article
- Can in silico models predict drug-induced cardiac risk in vulnerable populations?Toxicology reports · 2026Article
- Fast and accurate prediction of drug induced proarrhythmic risk with sex specific cardiac emulators.NPJ digital medicine · 2024Article
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
- Myocardial ischemia simulation based on a multi-scale heart electrophysiology model.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- Proarrhythmic risk assessment of drugs by dVCPT: pharmacometrics & systems pharmacology · 2022Article
- A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes.PLoS computational biology · 2021Article
- ECG Localization Method Based on Volume Conductor Model and Kalman Filtering.Sensors (Basel, Switzerland) · 2021Article
- Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes.PLoS computational biology · 2021Article
- Deriving the Bidomain Model of Cardiac Electrophysiology From a Cell-Based Model; Properties and Comparisons.Frontiers in physiology · 2021Article
- The 'Digital Twin' to enable the vision of precision cardiology.European heart journal · 2020Article
- A greedy classifier optimization strategy to assess ion channel blocking activity and pro-arrhythmia in hiPSC-cardiomyocytes.PLoS computational biology · 2020Article
- Review
- Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers.Computer methods in applied mechanics and engineering · 2020Article
- Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning.Biophysical journal · 2020Article
- Identification of Drug-Induced Multichannel Block and Proarrhythmic Risk in Humans Using Continuous T Vector Velocity Effect Profiles Derived From Surface Electrocardiograms.Frontiers in physiology · 2020Article
- Machine learning in drug development: Characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification.Computer methods in applied mechanics and engineering · 2019Article
- MRI-Based Computational Torso/Biventricular Multiscale Models to Investigate the Impact of Anatomical Variability on the ECG QRS Complex.Frontiers in physiology · 2019Article
- Improved Computational Identification of Drug Response Using Optical Measurements of Human Stem Cell Derived Cardiomyocytes in Microphysiological Systems.Frontiers in pharmacology · 2019Article
- Three-Dimensional Heart Model-Based Screening of Proarrhythmic Potential byFrontiers in physiology · 2019Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
background and purposeUnderstanding drug effects on the heart is key to safety pharmacology assessment and anti-arrhythmic therapy development. Here our goal is to demonstrate the ability of computational models to simulate the effect of drug action on the electrical activity of the heart, at the level of the ion-channel, cell, heart and ECG body surface potential. EXPERIMENTAL APPROACH: We use the state-of-the-art mathematical models governing the electrical activity of the heart. A drug model is introduced using an ion channel conductance block for the hERG and fast sodium channels, depending on the IC(50) value and the drug dose. We simulate the ECG measurements at the body surface and compare biomarkers under different drug actions. KEY
resultsIntroducing a 50% hERG-channel current block results in 8% prolongation of the APD(90) and 6% QT interval prolongation, hERG block does not affect the QRS interval. Introducing 50% fast sodium current block prolongs the QRS and the QT intervals by 12% and 5% respectively, and delays activation times, whereas APD(90) is not affected. CONCLUSIONS AND IMPLICATIONS: Both potassium and sodium blocks prolong the QT interval, but the underlying mechanism is different: for potassium it is due to APD prolongation; while for sodium it is due to a reduction of electrical wave velocity. This study shows the applicability of in silico models for the investigation of drug effects on the heart, from the ion channel to the ECG-based biomarkers.
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