Quantitative assessment of the usability of electromechanical human-based modelling and simulation to replace Langendorff isolated rabbit heart experiments in the preclinical setting

Journal article

Introduction: Effective proarrhythmic and inotropic risk assessment is essential for pharmaceutical development, but current preclinical methods for assessment of cardiac inotropy are flawed and costly, particularly when combined with QTc prolongation studies. Ex vivo rabbit Langendorff isolated heart experiments provide valuable insights into cardiovascular effects and safety, but their high cost, experimental difficulty, and limited applicability to human physiology pose challenges. Human mechanistic in silico modelling and simulation has proven successful in risk assessments of both electrophysiological and cardiac inotropy assessment. Methods: This study evaluates the feasibility of replacing ex vivo Langendorff experiments for contractility with human-based ventricular electromechanical modelling and simulations, based on 37 compounds. Results: Results show 1) 86% of compounds show qualitative agreement using four channel data (IKr, ICaL, INa, Ito), with 73% showing quantitative agreement correlating with higher quality data, 2) sensitivity analysis identified hNCX1 and late hNaV1.5 currents as additional targets, which, when considered alongside the four channel data as input, improved agreement from 86% to 95% (at least qualitatively), 3) incomplete dose-response input data was the key reason for discrepancies between experiment and simulation, while noting only two compounds showed a complete disagreement. Incorporating patient variability through a population of N = 166 human ventricular cell models add further confidence, and highlights increasing inter-subject diversity with increasing concentrations. Conclusion: This study supports the adoption of in silico new approach methodologies for accurate prediction of drug cardiotoxicity, and to refine, reduce and replace the use of ex vivo rabbit experiments.

Authors: Holmes, M; Martinez-Navarro, H; Mohr, M; Chambard, J; Ballet, V

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Frontiers Media
• Journal: Frontiers in Pharmacology
• Volume: 16
• Article number: 1671199
• Publication date: 2025-10-24
• Acceptance date: 2025-09-30
• DOI: 10.3389/fphar.2025.1671199
• EISSN: 1663-9812
• ISSN: 1663-9812
• Language: English
• Keywords: digital twin; cardiac risk assessment; cardiotoxicity; cardiac electromechanics contractility; modelling and simulation; drug modelling; new approach methodologies