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Computational assessment of drug-induced effects on the electrocardiogram: from ion channel to body surface potentials
BACKGROUND AND PURPOSE: Understanding 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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3579290/ https://www.ncbi.nlm.nih.gov/pubmed/22946617 http://dx.doi.org/10.1111/j.1476-5381.2012.02200.x |
Sumario: | BACKGROUND AND PURPOSE: Understanding 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 RESULTS: Introducing 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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