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. 2018 Sep;175(17):3435-3452.
doi: 10.1111/bph.14357. Epub 2018 Jul 22.

Arrhythmic hazard map for a 3D whole-ventricle model under multiple ion channel block

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Arrhythmic hazard map for a 3D whole-ventricle model under multiple ion channel block

Jun-Ichi Okada et al. Br J Pharmacol. 2018 Sep.

Abstract

Background and purpose: To date, proposed in silico models for preclinical cardiac safety testing are limited in their predictability and usability. We previously reported a multi-scale heart simulation that accurately predicts arrhythmogenic risk for benchmark drugs.

Experimental approach: We created a comprehensive hazard map of drug-induced arrhythmia based on the electrocardiogram (ECG) waveforms simulated under wide range of drug effects using the multi-scale heart simulator described here, implemented with cell models of human cardiac electrophysiology.

Key results: A total of 9075 electrocardiograms constitute the five-dimensional hazard map, with coordinates representing the extent of the block of each of the five ionic currents (rapid delayed rectifier potassium current (IKr ), fast (INa ) and late (INa,L ) components of the sodium current, L-type calcium current (ICa,L ) and slow delayed rectifier current (IKs )), involved in arrhythmogenesis. Results of the evaluation of arrhythmogenic risk based on this hazard map agreed well with the risk assessments reported in the literature. ECG databases also suggested that the interval between the J-point and the T-wave peak is a superior index of arrhythmogenicity when compared to the QT interval due to its ability to characterize the multi-channel effects compared with QT interval.

Conclusion and implications: Because concentration-dependent effects on electrocardiograms of any drug can be traced on this map based on in vitro current assay data, its arrhythmogenic risk can be evaluated without performing costly and potentially risky human electrophysiological assays. Hence, the map serves as a novel tool for use in pharmaceutical research and development.

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Figures

Figure 1
Figure 1
Method. Multiple ionic current‐blocking effects of drugs at each concentration (upper left) was mapped in a five‐dimensional space (lower left). For each point, multi‐scale heart simulation was performed (upper right) to produce a 12‐lead ECG, from which ECG indices or the occurrence of arrhythmia were determined (lower right).
Figure 2
Figure 2
Organ‐level validation of the model. Electrophysiological response of the model was validated against the ECG data of normal human subjects. For five of the test drugs, concentration‐dependent changes in QT intervals (ΔQT) calculated using the model were compared with those from published reports (Darpo et al., 2015). The IC50 and Hill coefficient values for each drug are listed in Supporting Information Table S2.1).
Figure 3
Figure 3
Five‐dimensional hazard map of drug‐induced arrhythmias. Top: Five‐dimensional data are visualized as a cluster of three‐dimensional subspace distributed in a plane with axes of I Ks block and I Na,L block. The coordinate system of subspace consists of the extent of block of I Kr, I Na and I Ca,L. Bottom: In each subspace (in this case, I Ks block = 0% and I Na,L block = 0%), the dose‐dependent effect of the drug (bepridil) can be traced as a trajectory. The trajectories were generated by functions, and the numbers on them represent the drug concentrations expressed as multiples of ETPCunbound. The region of arrhythmia is indicated as brown blocks. The inset shows the concentration–block relations of five ion currents. It demonstrates that virtually no inhibitory effects were observed for I Ks or I Na,L in the concentration ranges studied (shaded area). ECG changes at various concentrations are shown to the right with the corresponding activation sequence in the heart.
Figure 4
Figure 4
Visualization of drug effects in a hazard map. In each panel, orthogonal projections are shown with a 3D hazard map. (A) Concentration–block relationships of terfenadine, quinidine and amiodarone are shown as trajectories in a subspace at I Na,L block = 0% and I Ks block = 0%. (B) Concentration–block relationships of terfenadine, quinidine and amiodarone are shown as trajectories in a subspace at I Na,L block = 0% and I Ks block = 50%.
Figure 5
Figure 5
Visualizations of drug effects in hazard map. In each panel, orthogonal projections are shown with a 3D hazard map. (A) Concentration–block relationships of quinidine in a subspace at I Na,L block = 0% and I Ks block = 0% are shown. From the original trajectory (thick line), the effect of I Ca,L block was added gradually to shift the trajectory (blue arrow). (B) The effect of I Na,L block was visualized for quinidine and ranolazine in a subspace with I Ca,L, I Kr and I Na,L coordinates (I Na block = 0% and I Ks block = 0%).
Figure 6
Figure 6
Effects of multiple ionic current blocks on arrhythmogenicity and ECG indices. (A) In the five rows at the top, the extent of block of I Kr, I Ks, I Ca,L, I Na and I Na,L is shown in colour. For each combination of ionic current block, the occurrence of arrhythmia is indicated in black (6th row). Prolongations of the QT interval (ΔQT, 7th row), J‐Tpeak (ΔJ‐Tpeak, 8th row) and Tpeak‐Tend (ΔTpeak‐Tend, 9th row) are shown in colour. Colour codes are summarized in the bottom legend. (B) Coefficients of linear regression applied to changes in QT interval, Tpeak‐Tend and J‐Tpeak. (C) Coefficients of logistic regression applied to the relationship between the occurrence of arrhythmia and ionic current block.

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