Human-based in silico models are emerging as important tools to study the effects of integrating inward and outward ion channel currents to predict clinical proarrhythmic risk. The aims of this study were 2-fold: 1) Evaluate the capacity of an in silico model to predict QTc interval prolongation in the in vivo anesthetized cardiovascular guinea pig (CVGP) assay for new chemical entities (NCEs) and; 2) Determine if a translational pharmacokinetic/pharmacodynamic (tPKPD) model can improve the predictive capacity. In silico simulations for NCEs were performed using a population of human ventricular action potential (AP) models. PatchXpress® (PX) or high throughput screening (HTS) ion channel data from respectively n = 73 and n = 51 NCEs were used as inputs for the in silico population. These NCEs were also tested in the CVGP (n = 73). An M5 pruned decision tree-based regression tPKPD model was used to evaluate the concentration at which an NCE is liable to prolong the QTc interval in the CVGP. In silico results successfully predicted the QTc interval prolongation outcome observed in the CVGP with an accuracy/specificity of 85%/73% and 75%/77%, when using PX and HTS ion channel data, respectively. Considering the tPKPD predicted concentration resulting in QTc prolongation (EC5%) increased accuracy/specificity to 97%/95% using PX and 88%/97% when using HTS. Our results support that human-based in silico simulations in combination with tPKPD modeling can provide correlative results with a commonly used early in vivo safety assay, suggesting a path toward more rapid NCE assessment with reduced resources, cycle time, and animal use.

中文翻译：

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将计算机促心律失常风险测定与 tPKPD 模型相结合，以预测麻醉豚鼠测定中的 QTc 间期延长。

基于人的计算机模型正在成为研究整合向内和向外离子通道电流以预测临床前心律失常风险的重要工具。本研究的目的有两个：1) 评估计算机模型预测新化学实体 (NCE) 体内麻醉心血管豚鼠 (CVGP) 试验中 QTc 间期延长的能力；以及；2) 确定转化药代动力学/药效学 (tPKPD) 模型是否可以提高预测能力。使用一组人类心室动作电位 (AP) 模型对 NCE 进行计算机模拟。分别来自 n = 73 和 n = 51 NCE 的 PatchXpress® (PX) 或高通量筛选 (HTS) 离子通道数据用作计算机群体的输入。这些 NCE 也在 CVGP (n = 73) 中进行了测试。使用基于 M5 修剪决策树的回归 tPKPD 模型来评估 NCE 可能延长 CVGP 中 QTc 间期的浓度。当使用 PX 和 HTS 离子通道数据时，计算机结果成功预测了 CVGP 中观察到的 QTc 间期延长结果，准确度/特异性分别为 85%/73% 和 75%/77%。考虑到导致 QTc 延长 (EC5%) 的 tPKPD 预测浓度，使用 PX 将准确度/特异性提高到 97%/95%，使用 HTS 时提高到 88%/97%。我们的结果支持基于人的计算机模拟与 tPKPD 建模相结合可以提供与常用的早期体内安全性测定相关的结果，这表明通过减少资源、周期时间和动物使用来实现更快速的 NCE 评估的途径。