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

2018; Wiley; Volume: 105; Issue: 2 Linguagem: Inglês

10.1002/cpt.1184

1532-6535

Zhihua Li, Bradley J. Ridder, Xiaomei Han, Wendy Wu, Jiansong Sheng, P. Tran, Min Wu, Aaron Randolph, Ross H. Johnstone, Gary R. Mirams, Yuri A. Kuryshev, James Kramer, Caiyun Wu, William Crumb, David G. Strauss,

Statistical Methods in Clinical Trials

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 (Ci PA ) 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 Ci PA training drugs. In this study, we report the application of the prespecified model and metric to independent Ci PA validation drugs. Over two validation datasets, the Ci PA 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 Ci PA 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.