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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.

SUBMITTER: Margara F

PROVIDER: S-EPMC7848595 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Margara Francesca F Wang Zhinuo J ZJ Levrero-Florencio Francesc F Santiago Alfonso A Vázquez Mariano M Bueno-Orovio Alfonso A Rodriguez Blanca B

Progress in biophysics and molecular biology 20200722

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 huma ...[more]

PMID: 32710902

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Project description:Cardiac safety remains the leading cause of drug development discontinuation. We developed a human cardiomyocyte-based model that has the potential to provide a predictive preclinical approach for simultaneously predicting drug-induced inotropic and pro-arrhythmia risk. Methods: Adult human primary cardiomyocytes from ethically consented organ donors were used to measure contractility transients. We used measures of changes in contractility parameters as markers to infer both drug-induced inotropic effect (sarcomere shortening) and pro-arrhythmia (aftercontraction, AC); contractility escape (CE); time to 90% relaxation (TR90). We addressed the clinical relevance of this approach by evaluating the effects of 23 torsadogenic and 10 non-torsadogenic drugs. Each drug was tested separately at four multiples of the free effective therapeutic plasma concentration (fETPC). Results: Human cardiomyocyte-based model differentiated between torsadogenic and non-torsadogenic drugs. For example, dofetilide, a torsadogenic drug, caused ACs and increased TR90 starting at 10-fold the fETPC, while CE events were observed at the highest multiple of fETPC (100-fold). Verapamil, a non-torsadogenic drug, did not change TR90 and induced no AC or CE up to the highest multiple of fETPCs tested in this study (222-fold). When drug pro-arrhythmic activity was evaluated at 10-fold of the fETPC, AC parameter had excellent assay sensitivity and specificity values of 96 and 100%, respectively. This high predictivity supports the translational safety potential of this preparation and of the selected marker. The data demonstrate that human cardiomyocytes could also identify drugs associated with inotropic effects. hERG channel blockers, like dofetilide, had no effects on sarcomere shortening, while multi-ion channel blockers, like verapamil, inhibited sarcomere shortening. Conclusions: Isolated adult human primary cardiomyocytes can simultaneously predict risks associated with inotropic activity and pro-arrhythmia and may enable the generation of reliable and predictive data for assessing human cardiotoxicity at an early stage in drug discovery.

Project description:To assess drug-induced pro-arrhythmic risk, especially Torsades de Pointe (TdP), new models have been proposed, such as in-silico modeling of ventricular action potential (AP) and stem cell-derived cardiomyocytes (SC-CMs). Previously we evaluated the electrophysiological profile of 15 reference drugs in hESC-CMs and hiPSC-CMs for their effects on intracellular AP and extracellular field potential, respectively. Our findings indicated that SC-CMs exhibited immature phenotype and had the propensity to generate false positives in predicting TdP risk. To expand our knowledge with mature human cardiac tissues for drug-induced pro-arrhythmic risk assessment, human ventricular trabeculae (hVT) from ethically consented organ donors were used to evaluate the effects of the same 15 drugs (8 torsadogenic, 5 non-torsadogenic, and 2 discovery molecules) on AP parameters at 1 and 2 Hz. Each drug was tested blindly with 4 concentrations in duplicate trabeculae from 2 hearts. To identify the pro-arrhythmic risk of each drug, a pro-arrhythmic score was calculated as the weighted sum of percent drug-induced changes compared to baseline in various AP parameters, including AP duration and recognized pro-arrhythmia predictors such as triangulation, beat-to-beat variability and incidence of early-afterdepolarizations, at each concentration. In addition, to understand the translation of this preclinical hVT AP-based model to clinical studies, a ratio that relates each testing concentration to the human therapeutic unbound Cmax (Cmax) was calculated. At a ratio of 10, for the 8 torsadogenic drugs, 7 were correctly identified by the pro-arrhythmic score; 1 was mislabeled. For the 5 non-torsadogenic drugs, 4 were correctly identified as safe; 1 was mislabeled. Calculation of sensitivity, specificity, positive predictive value, and negative predictive value indicated excellent performance. For example, at a ratio of 10, scores for sensitivity, specificity, positive predictive value and negative predictive values were 0.88, 0.8, 0.88 and 0.8, respectively. Thus, the hVT AP-based model combined with the integrated analysis of pro-arrhythmic score can differentiate between torsadogenic and non-torsadogenic drugs, and has a greater predictive performance when compared to human SC-CM models.

Project description:ObjectivesSeveral issues that are inherent in the surgical techniques of surgical ventricular restoration (SVR) need specialized devices or techniques to overcome them, which may not always result in optimal outcomes. We used a non-invasive novel in silico modelling technique to study left ventricular (LV) morphology and function before and after SVR. The cardiac magnetic resonance imaging derived actual pre- and postoperative endocardial morphology and function was compared with the in silico analysis of the same.MethodsCardiac magnetic resonance steady state free precession (SSFP) cine images were employed to segment endocardial surface contours over the cardiac cycle. Using the principle of Hausdorff distance to examine phase-to-phase regional endocardial displacement, dyskinetic/akinetic areas were identified at the instant of peak basal contraction velocity. Using a three-dimensional (3D) surface clipping tool, the maximally scarred, dyskinetic or akinetic LV antero-apical areas were virtually resected and a new apex was created. A virtual rectangular patch was created upon the clipped surface LV model by 3D Delaunay triangulation. Presurgical endocardial mechanical function quantified from cine cardiac magnetic resonance, using a technique of spherical harmonics (SPHARM) surface parameterization, was applied onto the virtually clipped and patched LV surface model. Finally, the in silico model of post-SVR LV shape was analysed for quantification of regional left ventricular volumes (RLVVs) and function. This was tested in 2 patients with post-myocardial infarction antero-apical LV aneuryms. Left ventricular mechanical dysynchrony was evaluated by RLVV analysis of pre-SVR, in silico post-SVR and actual post-SVR LV endocardial surface data.ResultsFollowing exclusion of the scarred areas, the virtual resected LV model demonstrated significantly lesser areas of akinesia. The decreases in regional LV volumes in the in silico modelling were significant and comparable with the actual decreases following SVR. Both the regional end diastolic volume (EDV) and end systolic volume (ESV) at the apex decreased significantly corresponding to greater reductions in apical volumes by the technique of rectangular patch plasty (apical EDV 2.1607 ± 0.20577 to 0.4774 ± 0.1775 ml, P = 0.007; apical ESV 1.9708 ± 0.36451 to 0.442 ± 0.047 ml, P = 0.013).ConclusionsThis pilot study was done using novel in silico techniques for virtual surgical modelling, which helped in accurate estimation and planning of optimal LV restoration by SVR.

Dataset Information

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

Publications

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

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