In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment

Abstract

Human-based computational modelling and simulation are powerful tools to accelerate the mechanistic understanding of cardiac patho-physiology, and to develop and evaluate therapeutic interventions. The aim of this study is to calibrate and evaluate human ventricular electro-mechanical models for investigations on the effect of the electro-mechanical coupling and pharmacological action on human ventricular electrophysiology, calcium dynamics, and active contraction. The most recent models of human ventricular electrophysiology, excitation-contraction coupling, and active contraction were integrated, and the coupled models were calibrated using human experimental data. Simulations were then conducted using the coupled models to quantify the effects of electro-mechanical coupling and drug exposure on electrophysiology and force generation in virtual human ventricular cardiomyocytes and tissue. The resulting calibrated human electro-mechanical models yielded active tension, action potential, and calcium transient metrics that are in agreement with experiments for endocardial, epicardial, and mid-myocardial human samples. Simulation results correctly predicted the inotropic response of different multichannel action reference compounds and demonstrated that the electro-mechanical coupling improves the robustness of repolarisation under drug exposure compared to electrophysiology-only models. They also generated additional evidence to explain the partial mismatch between in-silico and in-vitro experiments on drug-induced electrophysiology changes. The human calibrated and evaluated modelling and simulation framework constructed in this study opens new avenues for future investigations into the complex interplay between the electrical and mechanical cardiac substrates, its modulation by pharmacological action, and its translation to tissue and organ models of cardiac patho-physiology.

Keywords: Computational modelling; Computer simulation; Drug safety; Human cardiac contraction; Human ventricular action potential; In-silico drug trials.

Fig. 1

Human-based biophysical models and biomarkers of electro-mechanical function. A: Schematic representation of ionic currents, calcium dynamics and contractile properties considered. Here the electrophysiology model diagram represents the ToR-ORd model (adapted from Tomek et al., 2019 as allowed by the CC-BY license). B: Biomarkers computed. B1: Typical AP waveform and relative biomarkers (tp: time to AP peak; APD50/APD90: AP duration at 50/90% repolarisation). Inset: AP repolarisation abnormalities (early afterdepolarisations, EADs). B2: Typical CaT waveform and relative biomarkers (tp: time to CaT peak; rt50/rt90: time to 50/90% decay from CaT peak). B3: Typical active tension waveform and relative biomarkers (tp: time to active tension peak; rt50/rt95: time to 50/95% decay from active tension peak). Inset: Active tension abnormalities (aftercontractions, ACs).

Fig. 2

Human electro-mechanical model calibration and comparison with experimental data. Comparisons between the AP (A), CaT (B), and active tension (C) of the calibrated models and human experimental data (A: Britton et al., 2017b; B: Coppini et al., 2013; C: Mulieri et al., 1992; Pieske et al., 1996; Rossman et al., 2004). ToR-ORd+Land model in blue and ORd+Land model in green. Calibrated models have AP, CaT, and active tension biomarkers that are within experimental ranges. Panel B also shows the CaT used to drive contraction in the original Land model (yellow). Calibration does not affect the AP or CaT (A-B). Panel C shows how the simulated active tensions better replicate experimental data after calibration.

Fig. 3

Electrophysiological consequences of dynamic calcium binding to troponin C. A/C: Electro-mechanical coupling does not affect AP waveforms. B/D: The dynamic calcium binding to troponin C formulation changes the time course of CaTs and predicts less calcium binding to troponin C compared with the previous steady-state approximation (insets). E: Quantification of changes in CaT biomarkers induced by the dynamic calcium binding to troponin C. Black box plots represent experimental data.

Fig. 4

Transmural heterogeneity effects in electro-mechanical function. Single cell simulation results under heterogeneous electrophysiological transmural properties. A-B: Comparison between ToR-ORd+Land (A) and ORd+Land (B) models in AP, CaT, and active tension for endocardial, epicardial, and mid-myocardial cells. C: Active tension development in epicardial cells can be additionally modulated by myofilament calcium sensitivity (Ca50 value). Sensitivity analysis results predict that epicardial calcium sensitivity in the range between 1.75x and 2x the baseline Ca50 value (i.e. reduced sensitivity) achieves a similar active tension for epicardial compared to endocardial cells, as experimentally reported by Haynes et al. (2014). Inset: changes in CaT induced by calcium sensitivity.

Fig. 5

Dofetilide. A: Experimental evidence of Dofetilide-induced abnormalities recorded in human trabeculae at 1 Hz pacing (A1: EADs, figure reproduced with permission from Page et al. (2016)) and human myocytes paced at 0.25 Hz (A2: EADs, figure reproduced from O’Hara et al. (2011) as allowed by the CC-BY licence) and 1 Hz (A3: aftercontractions, figure reproduced from Nguyen et al. (2017) as allowed by the CC-BY licence). B: Single cell and tissue simulations of Dofetilide exposure. B1-B2: Single cell comparison between ToR-ORd+Land (B1) and ORd+Land (B2) model predictions. Dofetilide-induced AP prolongation favours a persistent ICaL current, which mediates positive inotropic effects at low doses and EADs formation for the highest ones. B3-B5: 3D tissue simulations at 1.25 Hz pacing. 0.1 μM of Dofetilide induces EADs (B3) that trigger aftercontractions (B4). Contractility escapes indicated by horizontal arrows. AP and z displacements recorded at the free surface opposite stimulation. B5: AP time course in a line connecting two opposite corners. Arrows highlight APs propagation failure. The inset reports the AP time course at the stimulus site. Results in B3-B5 obtained with the ORd+Land model.

Fig. 6

Electro-mechanical coupling and repolarisation. Electro-mechanical coupling (EM) mitigates the APD prolongation induced by Dofetilide, and delays EADs onset (A-B). This is mediated by a faster CaT decay under EM coupling (C), which recovers almost entirely during AP repolarisation. Results obtained with the ToR-ORd+Land model. CL: cycle length.

Fig. 7

Verapamil. A: Experimental evidence of Verapamil-induced effects on cell shortening (figures reproduced from Nguyen et al. (2017) as allowed by the CC-BY licence). B: Single cell and tissue simulation of Verapamil effects. B1: Dose-response curves of peak active tension for Verapamil, using the ToR-ORd+Land and ORd+Land models. B2: Longitudinal displacement of the free face computed in tissue slabs exposed to different drug concentrations. Inset: superimposed tissue slabs at maximal shortenings (undeformed tissue configuration in grey). C: In-vitro (C1) and in-silico (C2-C3) experiments of Verapamil-induced effects on electrophysiology. C1: Human trabeculae (figure reproduced with permission from Page et al., 2016). C2: Verapamil-induced effects on AP and CaT for ToR-ORd+Land and ORd+Land models. C3: APD90 prolongation under Verapamil exposure with respect to control APD90 for both models.

Fig. 8

Quinidine. A: Experimental evidence on Quinidine-induced effects on human AP (A1, figure reproduced with permission from Page et al., 2016) and cell shortening (A2, figure reproduced from Nguyen et al. (2017) as allowed by the CC-BY licence). B: Single cell simulations of Quinidine effects. B1: Comparison between the ToR-ORd+Land and ORd+Land models in response to Quinidine action in terms of AP and CaT. B2: Quinidine dose-response curves for active tension reduction for both the ToR-ORd+Land and ORd+Land models.