Integrating excitation-contraction coupling into electrophysiological models increased the number of accepted biomarkers for Torsade de Pointes risk assessment (from 4 to 6 for CiPAORdv1.0).
Does incorporating excitation-contraction coupling improve biomarker robustness for Torsade de Pointes risk assessment in in silico human ventricular electrophysiological models?
Incorporating electromechanical coupling into in silico human ventricular models enhances the robustness and reliability of biomarkers for predicting drug-induced Torsade de Pointes risk.
BACKGROUND AND OBJECTIVE: Predicting drug-induced cardiac toxicity remains a critical challenge in preclinical safety assessment, particularly for evaluating the risk of Torsade de Pointes (TdP). While the Comprehensive in vitro Proarrhythmia Assay (CiPA) framework enables biomarker-based risk stratification, the robustness of these biomarkers under ion-channel uncertainty remains insufficiently characterized. This study aims to systematically evaluate whether incorporating excitation-contraction (EC) coupling can improve biomarker robustness for TdP risk assessment. METHODS: Human ventricular electrophysiological models (CiPAORdv1.0 and ToR-ORd) were integrated with a Land-based electromechanical model. Eleven biomarkers were evaluated using ordinal logistic regression, with 12 drugs used for training and 16 drugs for testing. To account for uncertainty, model performance was assessed using 10,000 independent test-time iterations following the CiPA framework. RESULTS: Integration of EC coupling consistently increased the number of accepted biomarkers (CiPAORdv1.0: 4 to 6; ToR-ORd: 5 to 7). The most pronounced improvements were observed in calcium transient-based biomarkers (CaTD50, CaTD90), which transitioned from rejected to accepted. In addition, voltage-based biomarkers such as APD90 and qNet exhibited reduced variability and improved statistical stability, as reflected by narrower confidence intervals. CONCLUSIONS: These findings demonstrate that incorporating electromechanical coupling enhances biomarker robustness by improving the physiological representation of calcium dynamics under uncertain conditions. This study provides a structured computational evaluation of biomarker reliability and highlights the potential of electromechanical models to strengthen in silico TdP risk prediction within the CiPA framework.
Hanum et al. (Mon,) conducted a other in Drug-induced cardiac toxicity (Torsade de Pointes). Integration of excitation-contraction (EC) coupling vs. Standard electrophysiological models without EC coupling was evaluated on Number of accepted biomarkers and biomarker robustness. Integrating excitation-contraction coupling into electrophysiological models increased the number of accepted biomarkers for Torsade de Pointes risk assessment (from 4 to 6 for CiPAORdv1.0).