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Evaluation of an in silico cardiac safety assay: Using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge

机译:进行计算机心脏安全性测定的评估:使用离子通道筛查数据预测兔心室楔块的QT间隔变化

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Introduction: 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. Methods: 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. Results: 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. Discussion: 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.
机译:简介:延长心电图QT间隔的药物是制药公司和监管机构的主要安全隐患。尽管进行了一系列评估化合物对QT间隔影响的分析方法,但QT延长仍然是化合物开发过程中磨损的主要原因。计算机分析可以减轻此类问题。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。方法:浓度-效应数据可从以下两种获得:高通量IonWorks / FLIPR;中通量PatchXpress离子通道测定;或QSAR,一种统计性IC50值预测模型,用于hERG,快速钠,L型钙和KCNQ1 / minK通道。通过将每个通道的最大电导率修改为取决于IC50值,Hill系数和每种测试化合物的浓度的因子,将通道的药物阻滞结合到兔心室肌细胞电生理的数学微分方程模型中。进行模拟并基于来自不同测定的输入数据评估与实验结果的一致性。结果:使用PatchXpress分析数据(77种化合物)预测QT延长(> .10%)时,发现该方法的准确度为78%,灵敏度为72%,特异性为81%。使用IonWorks / FLIPR数据(121种化合物)以78%的准确度,73%的灵敏度和80%的特异性证明了相似的预测水平。使用PatchXpress数据预测QT缩短(<。-。10%)具有77%的准确度,33%的灵敏度和90%的特异性,使用IonWorks / FLIPR数据具有71%的准确度,42%灵敏度和81%的特异性。模拟与实验结果之间的强烈定量一致性也很明显。讨论:电子计算机内动作电位测定法显示出良好的预测能力,适用于早期药物开发中的高通量使用。在心血管安全性评估中采用这种检测方法,整合常规筛查中的离子通道数据以推断基于动物的检测结果,可以提供一种节省成本和时间的心脏安全性筛查方法。

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