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Arrhythmic risk biomarkers for the assessment of drug cardiotoxicity: from experiments to computer simulations.

Corrias A, Jie X, Romero L, Bishop MJ, Bernabeu M, Pueyo E, Rodriguez B - Philos Trans A Math Phys Eng Sci (2010)

Bottom Line: To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels.Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market.We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.

View Article: PubMed Central - PubMed

Affiliation: Oxford University Computing Laboratory, Wolfson Building, Parks Road, Oxford OX1 3QD, UK.

ABSTRACT
In this paper, we illustrate how advanced computational modelling and simulation can be used to investigate drug-induced effects on cardiac electrophysiology and on specific biomarkers of pro-arrhythmic risk. To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels. The review highlights the variety of proposed biomarkers, the complexity of the mechanisms of drug-induced pro-arrhythmia and the existence of significant animal species differences in drug-induced effects on cardiac electrophysiology. Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market. Computational modelling and simulation has significantly contributed to the understanding of cardiac electrophysiology and arrhythmias over the last 40 years. In the second part of this paper, we illustrate how state-of-the-art open source computational modelling and simulation tools can be used to simulate multi-scale effects of drug-induced ion channel block in ventricular electrophysiology at the cellular, tissue and whole ventricular levels for different animal species. We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.

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Related in: MedlinePlus

(a) Action potentials recorded at representative nodes in the mesh under different coupling conditions (β=0.428 μs in the top panel, β= 0.214 μs in the middle panel and β=0.14 μs in the bottom panel; endocardial, blue line; mid-myocardial, green line; and epicardial, red line). The differences between epicardial and endocardial APs are highlighted (red line is a straight line). (b) Effect of coupling on APD triangulation for epicardial, mid-myocardial and endocardial nodes.
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RSTA20100083F7: (a) Action potentials recorded at representative nodes in the mesh under different coupling conditions (β=0.428 μs in the top panel, β= 0.214 μs in the middle panel and β=0.14 μs in the bottom panel; endocardial, blue line; mid-myocardial, green line; and epicardial, red line). The differences between epicardial and endocardial APs are highlighted (red line is a straight line). (b) Effect of coupling on APD triangulation for epicardial, mid-myocardial and endocardial nodes.

Mentions: The role of intercellular coupling in modulating transmural APD heterogeneity and QT interval was evaluated by varying the diffusion coefficient β in the monodomain equation. Simulations were conducted for three cases of intercellular coupling (β=0.428, 0.214 and 0.14 μs). The three values of intercellular coupling gave rise to propagation velocities across the tissue of 39.2, 26.7 and 19.6 cm s−1, respectively. Figure 7a shows APs recorded at representative nodes (the same as in figure 6) under different coupling conditions. As the tissue becomes less coupled the differences between epicardial, mid-myocardial and endocardial APs increase and tend to approach the isolated cell AP. The variation in AP shape due to intercellular coupling is shown in figure 7b, where an estimate of AP triangulation (ratio between APD30 and APD90) is shown for the three different degrees of coupling. While epicardial and endocardial cells slightly increase the value of AP triangulation, as the tissue becomes less coupled, the opposite is seen for mid-myocardial cells. Note that these trends reflect the tendency of an uncoupled tissue to behave in a similar way to isolated cells.


Arrhythmic risk biomarkers for the assessment of drug cardiotoxicity: from experiments to computer simulations.

Corrias A, Jie X, Romero L, Bishop MJ, Bernabeu M, Pueyo E, Rodriguez B - Philos Trans A Math Phys Eng Sci (2010)

(a) Action potentials recorded at representative nodes in the mesh under different coupling conditions (β=0.428 μs in the top panel, β= 0.214 μs in the middle panel and β=0.14 μs in the bottom panel; endocardial, blue line; mid-myocardial, green line; and epicardial, red line). The differences between epicardial and endocardial APs are highlighted (red line is a straight line). (b) Effect of coupling on APD triangulation for epicardial, mid-myocardial and endocardial nodes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2944395&req=5

RSTA20100083F7: (a) Action potentials recorded at representative nodes in the mesh under different coupling conditions (β=0.428 μs in the top panel, β= 0.214 μs in the middle panel and β=0.14 μs in the bottom panel; endocardial, blue line; mid-myocardial, green line; and epicardial, red line). The differences between epicardial and endocardial APs are highlighted (red line is a straight line). (b) Effect of coupling on APD triangulation for epicardial, mid-myocardial and endocardial nodes.
Mentions: The role of intercellular coupling in modulating transmural APD heterogeneity and QT interval was evaluated by varying the diffusion coefficient β in the monodomain equation. Simulations were conducted for three cases of intercellular coupling (β=0.428, 0.214 and 0.14 μs). The three values of intercellular coupling gave rise to propagation velocities across the tissue of 39.2, 26.7 and 19.6 cm s−1, respectively. Figure 7a shows APs recorded at representative nodes (the same as in figure 6) under different coupling conditions. As the tissue becomes less coupled the differences between epicardial, mid-myocardial and endocardial APs increase and tend to approach the isolated cell AP. The variation in AP shape due to intercellular coupling is shown in figure 7b, where an estimate of AP triangulation (ratio between APD30 and APD90) is shown for the three different degrees of coupling. While epicardial and endocardial cells slightly increase the value of AP triangulation, as the tissue becomes less coupled, the opposite is seen for mid-myocardial cells. Note that these trends reflect the tendency of an uncoupled tissue to behave in a similar way to isolated cells.

Bottom Line: To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels.Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market.We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.

View Article: PubMed Central - PubMed

Affiliation: Oxford University Computing Laboratory, Wolfson Building, Parks Road, Oxford OX1 3QD, UK.

ABSTRACT
In this paper, we illustrate how advanced computational modelling and simulation can be used to investigate drug-induced effects on cardiac electrophysiology and on specific biomarkers of pro-arrhythmic risk. To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels. The review highlights the variety of proposed biomarkers, the complexity of the mechanisms of drug-induced pro-arrhythmia and the existence of significant animal species differences in drug-induced effects on cardiac electrophysiology. Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market. Computational modelling and simulation has significantly contributed to the understanding of cardiac electrophysiology and arrhythmias over the last 40 years. In the second part of this paper, we illustrate how state-of-the-art open source computational modelling and simulation tools can be used to simulate multi-scale effects of drug-induced ion channel block in ventricular electrophysiology at the cellular, tissue and whole ventricular levels for different animal species. We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.

Show MeSH
Related in: MedlinePlus