Abstract
Torsades de Pointes (TdP) is a type of ventricular arrhythmia which could be observed as an unwanted drug-induced cardiac side effect, and it is associated with repolarization abnormalities in single cells. The pharmacological evaluations of TdP risk in previous years mainly focused on the hERG channel due to its vital role in the repolarization of cardiomyocytes. However, only considering drug effects on hERG led to false positive predictions since the drug action on other ion channels can also have crucial regulatory effects on repolarization. To address the limitation of only evaluating hERG, the Comprehensive in Vitro Proarrhythmia Assay initiative has proposed to systematically integrate drug effects on multiple ion channels into in silico drug trial to improve TdP risk assessment. It is not clear how many ion channels are sufficient for reliable TdP risk predictions, and whether differences in IC50 and Hill coefficient values from independent sources can lead to divergent in silico prediction outcomes. The rationale of this work is to investigate the above two questions using a computationally efficient population of human ventricular cells optimized to favor repolarization abnormality. Our blinded results based on two independent data sources confirm that simulations with the optimized population of human ventricular cell models enable efficient in silico drug screening, and also provide direct observation and mechanistic analysis of repolarization abnormality. Our results show that 1) the minimum set of ion channels required for reliable TdP risk predictions are Nav1.5 (peak), Cav1.2, and hERG; 2) for drugs with multiple ion channel blockage effects, moderate IC50 variations combined with variable Hill coefficients can affect the accuracy of in silico predictions.
Highlights
Cardiotoxicity is a major cause of drug withdrawal from the pharmaceutical market, and its earlier detection and assessment could largely speed up the evaluation of target compounds in the drug development process
In Dataset I, unblinding the compounds revealed a sensitivity of 85% and a specificity of 80% (Table 1), and the overall accuracy was 83%, with 3 false negative (FN) predictions and 2 false positive (FP) predictions
For Dataset II, bold scores indicate the true accuracy of the model predictions after fixing the misclassifications of the automated repolarization abnormality (RA) detection algorithm
Summary
Cardiotoxicity is a major cause of drug withdrawal from the pharmaceutical market, and its earlier detection and assessment could largely speed up the evaluation of target compounds in the drug development process. Drug-induced Torsades de Pointes (TdP) is a type of ventricular arrhythmia linked to sudden cardiac death. Drugs that block the hERG current (IKr) can inhibit the repolarization process, leading to AP duration (APD) prolongation, and facilitating EAD generation (Jurkiewicz and Sanguinetti, 1993; Guo et al, 2011; Pueyo et al, 2011; Dutta et al, 2016). IKr inhibition and QTc prolongation are sensitive but not very specific for predicting ventricular pro-arrhythmia risk. Inhibition of other cardiac ion channels, especially sodium and calcium channels, may mitigate the effects of hERG blockage and reduce pro-arrhythmic risk and EAD generation (Bril et al, 1996; Martin et al, 2004; Sager et al, 2014; Britton et al, 2017)
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