Limits...
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.

Show MeSH

Related in: MedlinePlus

Impact of ionic current variability on cellular electrophysiological biomarkers of arrhythmic risk. Electrophysiological properties are shown in the first column and ionic current properties appear in the first row. Relative sensitivities are depicted in grey code, with white being the colour that indicates the maximum sensitivity of an electrophysiological property. ICaL, L-type calcium current; IKr, the rapid component of the delayed rectifier current; IKs, the slow component of the delayed rectifier current; IK1, inward rectifier potassium current; INaK, sodium–potassium pump current; INaCa, sodium–calcium exchanger current; GCaL, maximal conductance of ICaL; τf, slow voltage-dependent inactivation gate time constants of ICaL; GKr, maximal conductance of IKr; GKs, maximal conductance of IKs; τXs, activation time constant of IKs; GK1, maximal conductance of IK1; GNaK, maximal activity of the sodium–potassium pump; GNaCa, maximal activity of the sodium–calcium exchanger.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2944395&req=5

RSTA20100083F2: Impact of ionic current variability on cellular electrophysiological biomarkers of arrhythmic risk. Electrophysiological properties are shown in the first column and ionic current properties appear in the first row. Relative sensitivities are depicted in grey code, with white being the colour that indicates the maximum sensitivity of an electrophysiological property. ICaL, L-type calcium current; IKr, the rapid component of the delayed rectifier current; IKs, the slow component of the delayed rectifier current; IK1, inward rectifier potassium current; INaK, sodium–potassium pump current; INaCa, sodium–calcium exchanger current; GCaL, maximal conductance of ICaL; τf, slow voltage-dependent inactivation gate time constants of ICaL; GKr, maximal conductance of IKr; GKs, maximal conductance of IKs; τXs, activation time constant of IKs; GK1, maximal conductance of IK1; GNaK, maximal activity of the sodium–potassium pump; GNaCa, maximal activity of the sodium–calcium exchanger.

Mentions: The relative sensitivities of each cellular biomarker to changes in each current property found in that study are represented in figure 2 in grey scale, except for activation and fast voltage-dependent inactivation gate time constants of ICaL and activation and inactivation gate time constants of the rapid component of the delayed rectifier current as their effects were negligible. In figure 2, the highest sensitivity of a biomarker is represented in white and its absolute value is also shown in each white box. The figure shows that changes in any repolarization current conductance and in ICaL inactivation kinetics as well as the slow component of the delayed rectifier current (τXs) can effectively modify the APD. By contrast, AP triangulation is basically determined by inward rectifier potassium current (IK1) and IKs. In addition, adaptation of AP duration to rate changes, restitution properties and intracellular calcium and sodium concentrations depend on ICaL properties and the sodium–potassium pump. As each column represents the effect of a certain ionic current modification, potential side effects of a new component could be anticipated by using this sensitivity analysis.


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)

Impact of ionic current variability on cellular electrophysiological biomarkers of arrhythmic risk. Electrophysiological properties are shown in the first column and ionic current properties appear in the first row. Relative sensitivities are depicted in grey code, with white being the colour that indicates the maximum sensitivity of an electrophysiological property. ICaL, L-type calcium current; IKr, the rapid component of the delayed rectifier current; IKs, the slow component of the delayed rectifier current; IK1, inward rectifier potassium current; INaK, sodium–potassium pump current; INaCa, sodium–calcium exchanger current; GCaL, maximal conductance of ICaL; τf, slow voltage-dependent inactivation gate time constants of ICaL; GKr, maximal conductance of IKr; GKs, maximal conductance of IKs; τXs, activation time constant of IKs; GK1, maximal conductance of IK1; GNaK, maximal activity of the sodium–potassium pump; GNaCa, maximal activity of the sodium–calcium exchanger.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

RSTA20100083F2: Impact of ionic current variability on cellular electrophysiological biomarkers of arrhythmic risk. Electrophysiological properties are shown in the first column and ionic current properties appear in the first row. Relative sensitivities are depicted in grey code, with white being the colour that indicates the maximum sensitivity of an electrophysiological property. ICaL, L-type calcium current; IKr, the rapid component of the delayed rectifier current; IKs, the slow component of the delayed rectifier current; IK1, inward rectifier potassium current; INaK, sodium–potassium pump current; INaCa, sodium–calcium exchanger current; GCaL, maximal conductance of ICaL; τf, slow voltage-dependent inactivation gate time constants of ICaL; GKr, maximal conductance of IKr; GKs, maximal conductance of IKs; τXs, activation time constant of IKs; GK1, maximal conductance of IK1; GNaK, maximal activity of the sodium–potassium pump; GNaCa, maximal activity of the sodium–calcium exchanger.
Mentions: The relative sensitivities of each cellular biomarker to changes in each current property found in that study are represented in figure 2 in grey scale, except for activation and fast voltage-dependent inactivation gate time constants of ICaL and activation and inactivation gate time constants of the rapid component of the delayed rectifier current as their effects were negligible. In figure 2, the highest sensitivity of a biomarker is represented in white and its absolute value is also shown in each white box. The figure shows that changes in any repolarization current conductance and in ICaL inactivation kinetics as well as the slow component of the delayed rectifier current (τXs) can effectively modify the APD. By contrast, AP triangulation is basically determined by inward rectifier potassium current (IK1) and IKs. In addition, adaptation of AP duration to rate changes, restitution properties and intracellular calcium and sodium concentrations depend on ICaL properties and the sodium–potassium pump. As each column represents the effect of a certain ionic current modification, potential side effects of a new component could be anticipated by using this sensitivity analysis.

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