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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) The whole ventricular mesh. A portion of it is shifted to allow visualization of the three layers in which the wall has been subdivided: endocardial (blue), mid-myocardial (green) and epicardial (red). (b) Action potentials of isolated cells included in the three layers.
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RSTA20100083F5: (a) The whole ventricular mesh. A portion of it is shifted to allow visualization of the three layers in which the wall has been subdivided: endocardial (blue), mid-myocardial (green) and epicardial (red). (b) Action potentials of isolated cells included in the three layers.

Mentions: In this section, a rabbit ventricular model was used to simulate the impact of ion channel block on the ECG, under several conditions of tissue coupling. The propagation of the AP across the cardiac muscle was simulated by solving the monodomain equation using the Chaste simulator (Pitt-Francis et al. 2009). Potse et al. (2006) have shown that, in most cases when the extracellular potential is not of specific interest, the distribution of Vm calculated with the monodomain and bidomain equations are very similar. Having to solve one equation instead of two, the monodomain model has the advantage of reduced computational cost. Hence, although the Chaste software fully supports the solution of the bidomain equations for the whole heart, here the monodomain model was used. Assuming a constant conductivity tensor, the monodomain equation is3.1where Vm is the transmembrane potential, Cm is the membrane capacitance per unit of tissue area, Iion is given by the equations in the Mahajan–Shiferaw model of a rabbit ventricular cell (Mahajan et al. 2008), Istim is an intracellular stimulus current and β is a diffusion coefficient (see below). The geometry of the rabbit ventricles was reconstructed from MRI images as described in Bishop et al. (2010) and discretized by 3 172 910 tetrahedral elements (average distance between nodes was 250.741 μM). Transmural cellular heterogeneities were modelled by dividing the cardiac wall in epicardial, mid-myocardial and endocardial layers as shown in figure 5a in relative proportions of 2:3:3, respectively (Saucerman et al. 2004). In each of these layers, parameters for IKs and Ito were scaled in order to match the experimental observations on AP duration in single-cell experiments by McIntosh et al. (2000) in a similar way to that proposed by Saucerman et al. (2004; figure 5b).


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) The whole ventricular mesh. A portion of it is shifted to allow visualization of the three layers in which the wall has been subdivided: endocardial (blue), mid-myocardial (green) and epicardial (red). (b) Action potentials of isolated cells included in the three layers.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

RSTA20100083F5: (a) The whole ventricular mesh. A portion of it is shifted to allow visualization of the three layers in which the wall has been subdivided: endocardial (blue), mid-myocardial (green) and epicardial (red). (b) Action potentials of isolated cells included in the three layers.
Mentions: In this section, a rabbit ventricular model was used to simulate the impact of ion channel block on the ECG, under several conditions of tissue coupling. The propagation of the AP across the cardiac muscle was simulated by solving the monodomain equation using the Chaste simulator (Pitt-Francis et al. 2009). Potse et al. (2006) have shown that, in most cases when the extracellular potential is not of specific interest, the distribution of Vm calculated with the monodomain and bidomain equations are very similar. Having to solve one equation instead of two, the monodomain model has the advantage of reduced computational cost. Hence, although the Chaste software fully supports the solution of the bidomain equations for the whole heart, here the monodomain model was used. Assuming a constant conductivity tensor, the monodomain equation is3.1where Vm is the transmembrane potential, Cm is the membrane capacitance per unit of tissue area, Iion is given by the equations in the Mahajan–Shiferaw model of a rabbit ventricular cell (Mahajan et al. 2008), Istim is an intracellular stimulus current and β is a diffusion coefficient (see below). The geometry of the rabbit ventricles was reconstructed from MRI images as described in Bishop et al. (2010) and discretized by 3 172 910 tetrahedral elements (average distance between nodes was 250.741 μM). Transmural cellular heterogeneities were modelled by dividing the cardiac wall in epicardial, mid-myocardial and endocardial layers as shown in figure 5a in relative proportions of 2:3:3, respectively (Saucerman et al. 2004). In each of these layers, parameters for IKs and Ito were scaled in order to match the experimental observations on AP duration in single-cell experiments by McIntosh et al. (2000) in a similar way to that proposed by Saucerman et al. (2004; figure 5b).

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