Evaluation of an in silico cardiac safety assay: using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge.
Evaluation of an in silico cardiac safety assay: using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge.
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DOI：
10.1016/j.vascn.2013.04.004
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发表时间：
2013-07
影响因子：
1.9
通讯作者：
Mirams GR
中科院分区：
文献类型：
--
作者：
Beattie KA;Luscombe C;Williams G;Munoz-Muriedas J;Gavaghan DJ;Cui Y;Mirams GR
延长心电图QT间期的药物是制药公司和监管机构关注的主要安全问题。尽管进行了一系列的试验来评估复合效应对QT间期的影响，QT间期延长仍然是复合发展过程中消耗的主要原因。计算机分析可以缓解这些问题。在这项研究中，我们评估了一种预测兔左心室楔形测定结果的计算机方法。浓度效应数据通过以下方法获得：高通量IonWorks/FLIPR；中通量PatchXpress离子通道检测；QSAR是一种统计IC50值预测模型，用于hERG、fast钠、l型钙和KCNQ1/minK通道。通过以IC50值、Hill系数和所测化合物浓度为影响因子，改变各通道的最大电导，将药物通道阻滞纳入兔心室肌细胞电生理数学微分方程模型。根据来自不同分析的输入数据，进行了模拟，并评估了与实验结果的一致性。使用PatchXpress检测数据（77种化合物）预测QT间期延长时，发现该方法准确率为78%，灵敏度为72%，特异性为81%。使用IonWorks/FLIPR数据（121种化合物）显示了相似的预测水平，准确率为78%，灵敏度为73%，特异性为80%。使用PatchXpress数据预测QT缩短（< - 10%）的准确度为77%，灵敏度为33%，特异性为90%；使用IonWorks/FLIPR数据预测QT缩短（< - 10%）的准确度为71%，灵敏度为42%，特异性为81%。模拟和实验结果之间的定量一致性也很明显。该方法具有良好的预测能力，适用于高通量的早期药物开发。将这种检测方法应用于心血管安全评估，整合常规筛查的离子通道数据来推断基于动物的试验结果，可以提供一种成本高、时间有效的心脏安全筛查方法。
Drugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during compound development. In silico assays could alleviate such problems. In this study we evaluated an in silico method of predicting the results of a rabbit left-ventricular wedge assay. Concentration–effect data were acquired from either: the high-throughput IonWorks/FLIPR; the medium-throughput PatchXpress ion channel assays; or QSAR, a statistical IC50 value prediction model, for hERG, fast sodium, L-type calcium and KCNQ1/minK channels. Drug block of channels was incorporated into a mathematical differential equation model of rabbit ventricular myocyte electrophysiology through modification of the maximal conductance of each channel by a factor dependent on the IC50 value, Hill coefficient and concentration of each compound tested. Simulations were performed and agreement with experimental results, based upon input data from the different assays, was evaluated. The assay was found to be 78% accurate, 72% sensitive and 81% specific when predicting QT prolongation (>10%) using PatchXpress assay data (77 compounds). Similar levels of predictivity were demonstrated using IonWorks/FLIPR data (121 compounds) with 78% accuracy, 73% sensitivity and 80% specificity. QT shortening (<−10%) was predicted with 77% accuracy, 33% sensitivity and 90% specificity using PatchXpress data and 71% accuracy, 42% sensitivity and 81% specificity using IonWorks/FLIPR data. Strong quantitative agreement between simulation and experimental results was also evident. The in silico action potential assay demonstrates good predictive ability, and is suitable for very high-throughput use in early drug development. Adoption of such an assay into cardiovascular safety assessment, integrating ion channel data from routine screens to infer results of animal-based tests, could provide a cost- and time-effective cardiac safety screen.
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