In silico predictions of drug-induced changes in human cardiac contractility agree with experimental recordings

Cristian Trovato ^1,2* Stefano Longobardi ³ Elisa Passini ¹ Kylie A. Beattie ^3* Maxx Holmes ^1* Khuram Chaudhary ⁴ Eric Rossman ⁴ Blanca Rodriguez ^1*

• ¹ University of Oxford, Oxford, United Kingdom
• ² AstraZeneca (United Kingdom), London, England, United Kingdom
• ³ GlaxoSmithKline (United Kingdom), Brentford, England, United Kingdom
• ⁴ GlaxoSmithKline (United States), Philadelphia, Pennsylvania, United States

Drug-induced changes in cardiac contractility (inotropy) can lead to cardiotoxicity, a major cause of discontinuation in drug development. Preclinical approaches to assess cardiac inotropy are imperfect, with in vitro assays limited to stem cell derived or adult human primary cardiomyocytes. Human mechanistic in silico modelling and simulations are already successfully applied for proarrhythmia prediction, contributing to cardiac safety assessment strategies in early drug development. In this study, we investigated their ability to predict drug-induced effects on cardiac inotropy.We considered a validation set of 28 neutral/negative inotropic and 13 positive inotropic reference compounds and simulated their effects on cell contractility via ion channel inhibition and perturbation of nine biomechanical modelling parameters, respectively. For each compound, a wide range of drug concentrations was simulated in an experimentallycalibrated control population of 323 human ventricular in silico cells. Simulated biomarkers informing on drug-induced inotropy effects were compared to in vitro preclinical data from the literature.Computer simulations predicted drug-induced inotropic changes observed in vitro for 25 neutral/negative inotropes and 10 positive inotropes. Predictions of negative inotropic changes were quantitatively in agreement for 86% of tested drugs. Active tension peak was identified as the biomarker with highest predictivity potential.This study describes the validation and application of an in silico cardiac electromechanical model for drug safety evaluation, combining ion channel inhibition data and information on potential inotropic mechanisms to predict inotropic changes. Furthermore, a route for its integration as part of a preclinical drug safety assessment strategy is outlined.