BACKGROUND Drug-induced or acquired long QT syndrome occurs as a result of the unintended disruption of cardiac repolarization due to drugs that block cardiac ion channels. These side effects have been responsible for the withdrawal of a range of drugs from market and are a common reason for termination of the development of new drugs in the preclinical stage. Existing approaches to risk prediction are expensive and overly sensitive meaning that recently there have been renewed efforts, largely driven by the comprehensive proarrhythmic assay initiative, to develop more accurate methods for allocation of proarrhythmic risk. METHODS In this study, we aimed to quantify changes in the morphology of the repolarization phase of the cardiac action potential as an indicator of proarrhythmia, supposing that these shape changes might precede the emergence of ectopic depolarizations that trigger arrhythmia. To do this, we describe a new method of quantifying action potential morphology by measuring the radius of curvature of the repolarization phase both in simulated action potentials, as well as in action potentials measured from induced pluripotent stem cell-derived cardiomyocytes. Features derived from the curvature signal were used as inputs for logistic regressions to predict proarrhythmic risk. RESULTS Optimal risk classifiers based on morphology were able to correctly classify risk to drugs in the comprehensive proarrhythmic assay initiative panels with very high accuracy (0.9375) and outperformed conventional metrics based on action potential duration at 90% repolarization, triangulation, and charge movement (qNet). CONCLUSIONS Analysis of action potential morphology in response to proarrhythmic drugs improves prediction of torsadogenic risk. Furthermore, morphology metrics can be measured directly from the action potential, potentially eliminating the burden of undertaking complex screens of potency and drug-binding kinetics against multiple cardiac ion channels. As such, this method has the potential to improve and streamline regulatory assessment of proarrhythmia in preclinical drug development.

中文翻译：

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动作电位形态学准确预测具有延长心脏复极潜力的药物的致心律失常风险。

背景技术药物诱发的或获得性长QT综合征的发生是由于阻断心脏离子通道的药物导致心脏复极意外破坏的结果。这些副作用是导致一系列药物退出市场的原因，也是终止临床前阶段新药开发的常见原因。现有的风险预测方法价格昂贵且过于敏感，这意味着最近在全面的致心律失常检测倡议的推动下，人们重新努力开发更准确的方法来分配致心律失常风险。方法在本研究中，我们的目的是量化心脏动作电位复极相形态的变化，作为致心律失常的指标，假设这些形状变化可能先于引发心律失常的异位去极化的出现。为此，我们描述了一种通过测量模拟动作电位以及从诱导多能干细胞衍生的心肌细胞测量的动作电位中复极化相的曲率半径来量化动作电位形态的新方法。从曲率信号导出的特征被用作逻辑回归的输入，以预测致心律失常的风险。结果 基于形态学的最佳风险分类器能够以非常高的准确度 (0.9375) 在全面的致心律失常检测计划中正确分类药物风险，并且优于基于 90% 复极、三角测量和电荷运动的动作电位持续时间的传统指标 (qNet ）。结论 对促心律失常药物反应的动作电位形态分析可改善扭转致性风险的预测。此外，形态指标可以直接从动作电位测量，从而可能消除针对多个心脏离子通道进行效力和药物结合动力学的复杂筛选的负担。因此，该方法有可能改善和简化临床前药物开发中致心律失常的监管评估。