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

Abstract

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.

Quantitative Systems Pharmacology Models for a New International Cardiac Safety Regulatory Paradigm: An Overview of the Comprehensive In Vitro Proarrhythmia Assay In Silico Modeling Approach

“…After the training was completed and before the validation began, the model, metric, validation data set and methodology, plus performance measures and acceptable performance levels were all “frozen” in a time‐stamped validation strategy document (Supplementary Text 1 in ref. ). Subsequently, the model was taken to predict validation drugs, and the validation report document (Supplementary Text 2 in ref.…”

“…This procedure was approved by the Ci PA Steering Committee and time stamped in the validation strategy document (Supplementary Text 1 of ref. ) before the actual validation took place. The figure was adapted from ref.…”

“…The ISWG replaced the hERG /IKr component of the base O'Hara Rudy model with such a Markov submodel ( Figure a ), which can distinguish drugs with different binding kinetics captured by a dynamic voltage protocol ( Figure b ). Together with other model adjustments based on training data, this resulted in a prototype model CiPAORdv1.0 to be evaluated by the validation data set later …”

“…The ISWG developed such a method to estimate the joint distributions of pharmacodynamic parameters (binding kinetics, IC50s, etc.) based on training data and then applied it to validation . In contrast, most of the other published models for TdP risk prediction did not consider variability and uncertainty .…”

“…Subsequently, the model was taken to predict validation drugs, and the validation report document (Supplementary Text 2 in ref. ) indicated that the preregistered model CiPAORdv1.0 and metric qNet were able to meet all prespecified performance measures and outperform other alternative models/metrics tested. Such a rigorous design provides high confidence that the prototype model developed by ISWG has acceptable prediction accuracy for TdP risk assessment under the new CiPA paradigm.…”