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使用多尺度暴露-反应模拟器预测关键药物浓度和致扭风险。

Predicting critical drug concentrations and torsadogenic risk using a multiscale exposure-response simulator.

机构信息

Department of Mechanical Engineering, Stanford University, Stanford, CA, 94305, United States.

Dassault Systèmes Simulia Corporation, Johnston, RI, 02919, United States.

出版信息

Prog Biophys Mol Biol. 2019 Jul;144:61-76. doi: 10.1016/j.pbiomolbio.2018.10.003. Epub 2018 Oct 26.

Abstract

Torsades de pointes is a serious side effect of many drugs that can trigger sudden cardiac death, even in patients with structurally normal hearts. Torsadogenic risk has traditionally been correlated with the blockage of a specific potassium channel and a prolonged recovery period in the electrocardiogram. However, the precise mechanisms by which single channel block translates into heart rhythm disorders remain incompletely understood. Here we establish a multiscale exposure-response simulator that converts block-concentration characteristics from single cell recordings into three-dimensional excitation profiles and electrocardiograms to rapidly assess torsadogenic risk. For the drug dofetilide, we characterize the QT interval and heart rate at different drug concentrations and identify the critical concentration at the onset of torsades de pointes: For dofetilide concentrations of 2x, 3x, and 4x, as multiples of the free plasma concentration C = 2.1 nM, the QT interval increased by +62.0%, +71.2%, and +82.3% compared to baseline, and the heart rate changed by -21.7%, -23.3%, and +88.3%. The last number indicates that, at the critical concentration of 4x, the heart spontaneously developed an episode of a torsades-like arrhythmia. Strikingly, this critical drug concentration is higher than the concentration estimated from early afterdepolarizations in single cells and lower than in one-dimensional cable models. Our results highlight the importance of whole heart modeling and explain, at least in part, why current regulatory paradigms often fail to accurately quantify the pro-arrhythmic potential of a drug. Our exposure-response simulator could provide a more mechanistic assessment of pro-arrhythmic risk and help establish science-based guidelines to reduce rhythm disorders, design safer drugs, and accelerate drug development.

摘要

尖端扭转型室性心动过速是许多药物的严重副作用,即使在结构正常的心脏患者中,也可能引发心脏性猝死。致扭转型风险传统上与特定钾通道的阻断和心电图中恢复时间的延长有关。然而,单通道阻断如何转化为心律失常的精确机制仍不完全清楚。在这里,我们建立了一个多尺度的暴露-反应模拟器,可将阻滞-浓度特征从单细胞记录转换为三维激发图和心电图,以快速评估致扭转型风险。对于药物多非利特,我们在不同药物浓度下描述了 QT 间期和心率,并确定了尖端扭转型室性心动过速发作的临界浓度:对于多非利特浓度为 2x、3x 和 4x,即游离血浆浓度 C 的 2 倍、3 倍和 4 倍,与基线相比,QT 间期分别增加了+62.0%、+71.2%和+82.3%,心率分别变化了-21.7%、-23.3%和+88.3%。最后一个数字表示,在临界浓度 4x 下,心脏自发地发生了一阵尖端扭转型样的心律失常。引人注目的是,这个临界药物浓度高于从单细胞早期后除极估计的浓度,低于一维电缆模型中的浓度。我们的结果强调了整体心脏建模的重要性,并至少部分解释了为什么当前的监管模式经常无法准确量化药物的致心律失常潜力。我们的暴露-反应模拟器可以更深入地评估致心律失常风险,并有助于建立基于科学的指导方针,以减少节律紊乱、设计更安全的药物并加速药物开发。

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