ArticleJournal of pharmacological and toxicological methods
Prediction of Thorough QT study results using action potential simulations based on ion channel screens.
Article in Journal of pharmacological and toxicological methods. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
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- A model for the human fetal ventricular myocyte electrophysiology.PLoS computational biology · 2026Article
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- Comparison of in silico predictions of action potential duration in response to inhibition of IKr and ICaL with new human ex vivo recordings.PLoS computational biology · 2025Article
- Computational modelling for improved translation of cardiac inotropic and lusitropic drug effects from rats to humans.Journal of pharmacological and toxicological methods · 2025Article
- Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.Nature cardiovascular research · 2025Article
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- Neural network emulation of the human ventricular cardiomyocyte action potential: a tool for more efficient computation in pharmacological studies.bioRxiv : the preprint server for biology · 2023Article
- Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models.Archives of toxicology · 2023Article
- Multitargeting nature of muscarinic orthosteric agonists and antagonists.Frontiers in physiology · 2022Review
- Molecular determinants of pro-arrhythmia proclivity of d- and l-sotalol via a multi-scale modeling pipeline.Journal of molecular and cellular cardiology · 2021Article
- How circadian variability of the heart rate and plasma electrolytes concentration influence the cardiac electrophysiology - model-based case study.Journal of pharmacokinetics and pharmacodynamics · 2021Article
- Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.Circulation research · 2021Article
- Mechanisms of Premature Ventricular Complexes Caused by QT Prolongation.Biophysical journal · 2021Article
- Drug Development and the Use of Induced Pluripotent Stem Cell-Derived Cardiomyocytes for Disease Modeling and Drug Toxicity Screening.International journal of molecular sciences · 2020Review
- Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk.Cell reports. Medicine · 2020Article
- Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- When Does the ICJournal of chemical information and modeling · 2020Article
- Combining an in silico proarrhythmic risk assay with a tPKPD model to predict QTc interval prolongation in the anesthetized guinea pig assay.Toxicology and applied pharmacology · 2020Article
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7 authors.
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Abstract
introductionDetection of drug-induced pro-arrhythmic risk is a primary concern for pharmaceutical companies and regulators. Increased risk is linked to prolongation of the QT interval on the body surface ECG. Recent studies have shown that multiple ion channel interactions can be required to predict changes in ventricular repolarisation and therefore QT intervals. In this study we attempt to predict the result of the human clinical Thorough QT (TQT) study, using multiple ion channel screening which is available early in drug development.
methodsIon current reduction was measured, in the presence of marketed drugs which have had a TQT study, for channels encoded by hERG, CaV1.2, NaV1.5, KCNQ1/MinK, and Kv4.3/KChIP2.2. The screen was performed on two platforms - IonWorks Quattro (all 5 channels, 34 compounds), and IonWorks Barracuda (hERG & CaV1.2, 26 compounds). Concentration-effect curves were fitted to the resulting data, and used to calculate a percentage reduction in each current at a given concentration. Action potential simulations were then performed using the ten Tusscher and Panfilov (2006), Grandi et al. (2010) and O'Hara et al. (2011) human ventricular action potential models, pacing at 1Hz and running to steady state, for a range of concentrations.
resultsWe compared simulated action potential duration predictions with the QT prolongation observed in the TQT studies. At the estimated concentrations, simulations tended to underestimate any observed QT prolongation. When considering a wider range of concentrations, and conventional patch clamp rather than screening data for hERG, prolongation of ≥5ms was predicted with up to 79% sensitivity and 100% specificity. DISCUSSION: This study provides a proof-of-principle for the prediction of human TQT study results using data available early in drug development. We highlight a number of areas that need refinement to improve the method's predictive power, but the results suggest that such approaches will provide a useful tool in cardiac safety assessment.
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