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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

Action potentials (AP) from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100% IKr blockade (dashed lines) conditions, for the rabbit (a) and the guinea pig (b) models (black line, endocardium; blue line, M cell; green line, epicardium).
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RSTA20100083F3: Action potentials (AP) from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100% IKr blockade (dashed lines) conditions, for the rabbit (a) and the guinea pig (b) models (black line, endocardium; blue line, M cell; green line, epicardium).

Mentions: Figure 3 shows the time course of the AP from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100 per cent IKr blockade (dashed lines) conditions, for the rabbit (figure 3a) and the guinea pig (figure 3b) models. Clearly, in both models, Ir blockade led to prolongation of APD in all three layers and the interval between Q-wave and the peak of the T-wave (QTp). Figure 4 presents changes in transmural dispersion of repolarization (TDR; measured as the maximum difference in transmural APD) and QTp with varying degrees of IKr blockade for the rabbit (crosses) and guinea pig (triangles) models. Specifically, as the degree of IKr blockade increased from 0 to 100 per cent, TDR increased gradually by 17 and 8 per cent, together with a gradual increase in QTp by 20 and 13 per cent for the rabbit and guinea pig model, respectively. Here, we present simulations using two ionic specific models and we evaluate two sets of biomarkers. However, it must be noted that users could use any AP model and investigate any biomarker in addition to those described in the previous section.


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)

Action potentials (AP) from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100% IKr blockade (dashed lines) conditions, for the rabbit (a) and the guinea pig (b) models (black line, endocardium; blue line, M cell; green line, epicardium).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

RSTA20100083F3: Action potentials (AP) from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100% IKr blockade (dashed lines) conditions, for the rabbit (a) and the guinea pig (b) models (black line, endocardium; blue line, M cell; green line, epicardium).
Mentions: Figure 3 shows the time course of the AP from a representative node of each transmural layer and also the pseudo-ECG for the control (solid lines) and 100 per cent IKr blockade (dashed lines) conditions, for the rabbit (figure 3a) and the guinea pig (figure 3b) models. Clearly, in both models, Ir blockade led to prolongation of APD in all three layers and the interval between Q-wave and the peak of the T-wave (QTp). Figure 4 presents changes in transmural dispersion of repolarization (TDR; measured as the maximum difference in transmural APD) and QTp with varying degrees of IKr blockade for the rabbit (crosses) and guinea pig (triangles) models. Specifically, as the degree of IKr blockade increased from 0 to 100 per cent, TDR increased gradually by 17 and 8 per cent, together with a gradual increase in QTp by 20 and 13 per cent for the rabbit and guinea pig model, respectively. Here, we present simulations using two ionic specific models and we evaluate two sets of biomarkers. However, it must be noted that users could use any AP model and investigate any biomarker in addition to those described in the previous section.

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