Trovato Cristian, Longobardi Stefano, Passini Elisa, Beattie Kylie A, Holmes Maxx, Chaudhary Khuram W, Rossman Eric I, Rodriguez Blanca
Department of Computer Science, University of Oxford, Oxford, United Kingdom.
Systems Medicine, Clinical Pharmacology and Safety Science, R&D, AstraZeneca, Cambridge, United Kingdom.
Front Pharmacol. 2025 Mar 17;16:1500668. doi: 10.3389/fphar.2025.1500668. eCollection 2025.
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 assays limited to stem cell-derived or adult human primary cardiomyocytes. Human mechanistic 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 experimentally calibrated control population of 323 human ventricular cells. Simulated biomarkers indicating drug-induced inotropic effects were compared with preclinical data from the literature. Computer simulations predicted drug-induced inotropic changes observed 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 predictive potential. This study describes the validation and application of an 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.
药物引起的心脏收缩力(变力性)变化可导致心脏毒性,这是药物研发中导致药物停用的主要原因。评估心脏变力性的临床前方法并不完善,检测仅限于干细胞衍生的或成人原代心肌细胞。人体机制建模和模拟已成功应用于预测心律失常,有助于早期药物研发中的心脏安全性评估策略。在本研究中,我们调查了它们预测药物对心脏变力性影响的能力。我们考虑了一组由28种中性/负性变力性和13种正性变力性参考化合物组成的验证集,并分别通过离子通道抑制和九个生物力学建模参数的扰动来模拟它们对细胞收缩性的影响。对于每种化合物,在一个经过实验校准的由323个人类心室细胞组成的对照群体中模拟了广泛的药物浓度。将模拟的指示药物诱导变力性效应的生物标志物与文献中的临床前数据进行了比较。计算机模拟预测了25种中性/负性变力性药物和10种正性变力性药物所观察到的药物诱导的变力性变化。对于86%的受试药物,负性变力性变化的预测在数量上是一致的。活性张力峰值被确定为具有最高预测潜力的生物标志物。本研究描述了一种用于药物安全性评估的心脏机电模型的验证和应用,该模型结合了离子通道抑制数据和潜在变力性机制的信息来预测变力性变化。此外,还概述了将其作为临床前药物安全性评估策略一部分进行整合的途径。