ArticleJournal of pharmacological and toxicological methods
Evaluation of an in silico cardiac safety assay: using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge.
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 32 papers.
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Who cites it
32 citing papers in PubMed, 73 citations in OpenAlex.
- Quantitative systems toxicology: modelling to mechanistically understand and predict drug safety.Nature reviews. Drug discovery · 2026Review
- Molecular Determinants of Voltage-Dependent Gating in Kv11.1 Channels.Advances in experimental medicine and biology · 2026Review
- Computational modelling for improved translation of cardiac inotropic and lusitropic drug effects from rats to humans.Journal of pharmacological and toxicological methods · 2025Article
- A comprehensive review of 20 years of progress in nonclinical QT evaluation and proarrhythmic assessment.Journal of pharmacokinetics and pharmacodynamics · 2025Review
- Application of Mechanistic Mathematical Modeling to Toxicology: Quantitative Systems Toxicology (QST).Handbook of experimental pharmacology · 2025Review
- Quantitative systems toxicology modeling in pharmaceutical research and development: An industry-wide survey and selected case study examples.CPT: pharmacometrics & systems pharmacology · 2024Review
- HPC Framework for Performing in Silico Trials Using a 3D Virtual Human Cardiac Population as Means to Assess Drug-Induced Arrhythmic Risk.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models.Archives of toxicology · 2023Article
- The Potential Mechanisms behind Loperamide-Induced Cardiac Arrhythmias Associated with Human Abuse and Extreme Overdose.Biomolecules · 2023Article
- A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability.Bulletin of mathematical biology · 2022Article
- Electrophysiological characterization of the hERG R56Q LQTS variant and targeted rescue by the activator RPR260243.The Journal of general physiology · 2021Article
- Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk.Cell reports. Medicine · 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
- In silico study of the effects of anti-arrhythmic drug treatment on sinoatrial node function for patients with atrial fibrillation.Scientific reports · 2020Article
- Predicting critical drug concentrations and torsadogenic risk using a multiscale exposure-response simulator.Progress in biophysics and molecular biology · 2019Article
- 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
- Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment.Frontiers in pharmacology · 2019Article
- Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicator.Toxicology research · 2017Article
- Systems Toxicology: Real World Applications and Opportunities.Chemical research in toxicology · 2017Article
- HumanFrontiers in physiology · 2017Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
introductionDrugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during compound development. In silico assays could alleviate such problems. In this study we evaluated an in silico method of predicting the results of a rabbit left-ventricular wedge assay.
methodsConcentration-effect data were acquired from either: the high-throughput IonWorks/FLIPR; the medium-throughput PatchXpress ion channel assays; or QSAR, a statistical IC50 value prediction model, for hERG, fast sodium, L-type calcium and KCNQ1/minK channels. Drug block of channels was incorporated into a mathematical differential equation model of rabbit ventricular myocyte electrophysiology through modification of the maximal conductance of each channel by a factor dependent on the IC50 value, Hill coefficient and concentration of each compound tested. Simulations were performed and agreement with experimental results, based upon input data from the different assays, was evaluated.
resultsThe assay was found to be 78% accurate, 72% sensitive and 81% specific when predicting QT prolongation (>10%) using PatchXpress assay data (77 compounds). Similar levels of predictivity were demonstrated using IonWorks/FLIPR data (121 compounds) with 78% accuracy, 73% sensitivity and 80% specificity. QT shortening (<-10%) was predicted with 77% accuracy, 33% sensitivity and 90% specificity using PatchXpress data and 71% accuracy, 42% sensitivity and 81% specificity using IonWorks/FLIPR data. Strong quantitative agreement between simulation and experimental results was also evident. DISCUSSION: The in silico action potential assay demonstrates good predictive ability, and is suitable for very high-throughput use in early drug development. Adoption of such an assay into cardiovascular safety assessment, integrating ion channel data from routine screens to infer results of animal-based tests, could provide a cost- and time-effective cardiac safety screen.
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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.