Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative

Apr 30, 2018 • By Zhihua Li, Bradley J. Ridder, Xiaomei Han, Wendy W. Wu, Jiansong Sheng, Phu N. Tran, Min Wu, Aaron Randolph, Ross H. Johnstone, Gary R. Mirams, Yuri Kuryshev, James Kramer, Caiyun Wu, William J. Crumb Jr. and David G. Strauss

The International Council on Harmonization (ICH) S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are pro-arrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures. This suggests that the current CiPA model/metric may be fit for regulatory use, and standardization of experimental protocols and quality control criteria could increase the model prediction accuracy even further.
In the 1990s to early 2000s, it was recognized that drug-induced Torsade de Pointes (TdP), a rare but potentially fatal arrhythmia, is associated with pharmacological block of a potassium channel encoded by the human ether-à- go- go related gene (hERG) and electrocardiographic QTc prolongation. This finding led to the establishment of two International Council on Harmonization (ICH) regulatory guidelines (S7B and E14) for cardiac safety assessment that focus on assessing the potential of a drug to cause hERG block and QT prolongation. Although sensitive for identifying drugs that can cause TdP, these biomarkers have low specificity. This has caused the unintended effect of deprioritizing or excluding many drugs from development that may not have actual TdP risk. In response, a new paradigm—the Comprehensive In Vitro Proarrhythmia Assay (CiPA)—was proposed that takes into account drug effects on multiple cardiac ion channels in vitro and integrates these effects into a mechanistic in silico cardiomyocyte model to predict TdP risk as the direct end point.

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