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Dokuchaev A, Kursanov A, Balakina-Vikulova NA, Katsnelson LB, Solovyova O. The importance of mechanical conditions in the testing of excitation abnormalities in a population of electro-mechanical models of human ventricular cardiomyocytes. Front Physiol 2023; 14:1187956. [PMID: 37362439 PMCID: PMC10285544 DOI: 10.3389/fphys.2023.1187956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/25/2023] [Indexed: 06/28/2023] Open
Abstract
Background: Populations of in silico electrophysiological models of human cardiomyocytes represent natural variability in cell activity and are thoroughly calibrated and validated using experimental data from the human heart. The models have been shown to predict the effects of drugs and their pro-arrhythmic risks. However, excitation and contraction are known to be tightly coupled in the myocardium, with mechanical loads and stretching affecting both mechanics and excitation through mechanisms of mechano-calcium-electrical feedback. However, these couplings are not currently a focus of populations of cell models. Aim: We investigated the role of cardiomyocyte mechanical activity under different mechanical conditions in the generation, calibration, and validation of a population of electro-mechanical models of human cardiomyocytes. Methods: To generate a population, we assumed 11 input parameters of ionic currents and calcium dynamics in our recently developed TP + M model as varying within a wide range. A History matching algorithm was used to generate a non-implausible parameter space by calibrating the action potential and calcium transient biomarkers against experimental data and rejecting models with excitation abnormalities. The population was further calibrated using experimental data on human myocardial force characteristics and mechanical tests involving variations in preload and afterload. Models that passed the mechanical tests were validated with additional experimental data, including the effects of drugs with high or low pro-arrhythmic risk. Results: More than 10% of the models calibrated on electrophysiological data failed mechanical tests and were rejected from the population due to excitation abnormalities at reduced preload or afterload for cell contraction. The final population of accepted models yielded action potential, calcium transient, and force/shortening outputs consistent with experimental data. In agreement with experimental and clinical data, the models demonstrated a high frequency of excitation abnormalities in simulations of Dofetilide action on the ionic currents, in contrast to Verapamil. However, Verapamil showed a high frequency of failed contractions at high concentrations. Conclusion: Our results highlight the importance of considering mechanoelectric coupling in silico cardiomyocyte models. Mechanical tests allow a more thorough assessment of the effects of interventions on cardiac function, including drug testing.
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Affiliation(s)
- Arsenii Dokuchaev
- Laboratory of Mathematical Physiology, Institute of Immunology and Physiology, Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia
| | - Alexander Kursanov
- Laboratory of Mathematical Physiology, Institute of Immunology and Physiology, Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia
- Laboratory of Mathematical Modeling in Physiology and Medicine Based on Supercomputers, Ural Federal University, Ekaterinburg, Russia
| | - Nathalie A. Balakina-Vikulova
- Laboratory of Mathematical Physiology, Institute of Immunology and Physiology, Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia
- Laboratory of Mathematical Modeling in Physiology and Medicine Based on Supercomputers, Ural Federal University, Ekaterinburg, Russia
| | - Leonid B. Katsnelson
- Laboratory of Mathematical Physiology, Institute of Immunology and Physiology, Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia
- Laboratory of Mathematical Modeling in Physiology and Medicine Based on Supercomputers, Ural Federal University, Ekaterinburg, Russia
| | - Olga Solovyova
- Laboratory of Mathematical Physiology, Institute of Immunology and Physiology, Ural Branch of Russian Academy of Sciences, Ekaterinburg, Russia
- Laboratory of Mathematical Modeling in Physiology and Medicine Based on Supercomputers, Ural Federal University, Ekaterinburg, Russia
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Occurrence of early afterdepolarization under healthy or hypertrophic cardiomyopathy conditions in the human ventricular endocardial myocyte: In silico study using 109 torsadogenic or non-torsadogenic compounds. Toxicol Appl Pharmacol 2022; 438:115914. [DOI: 10.1016/j.taap.2022.115914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 01/19/2022] [Accepted: 02/05/2022] [Indexed: 11/18/2022]
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Kojima A, Fukushima Y, Itoh H, Imoto K, Matsuura H. A computational analysis of the effect of sevoflurane in a human ventricular cell model of long QT syndrome: Importance of repolarization reserve in the QT-prolonging effect of sevoflurane. Eur J Pharmacol 2020; 883:173378. [DOI: 10.1016/j.ejphar.2020.173378] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 06/26/2020] [Accepted: 07/13/2020] [Indexed: 10/23/2022]
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Li Z, Mirams GR, Yoshinaga T, Ridder BJ, Han X, Chen JE, Stockbridge NL, Wisialowski TA, Damiano B, Severi S, Morissette P, Kowey PR, Holbrook M, Smith G, Rasmusson RL, Liu M, Song Z, Qu Z, Leishman DJ, Steidl‐Nichols J, Rodriguez B, Bueno‐Orovio A, Zhou X, Passini E, Edwards AG, Morotti S, Ni H, Grandi E, Clancy CE, Vandenberg J, Hill A, Nakamura M, Singer T, Polonchuk L, Greiter‐Wilke A, Wang K, Nave S, Fullerton A, Sobie EA, Paci M, Musuamba Tshinanu F, Strauss DG. General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy. Clin Pharmacol Ther 2020; 107:102-111. [PMID: 31709525 PMCID: PMC6977398 DOI: 10.1002/cpt.1647] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 09/06/2019] [Indexed: 12/27/2022]
Abstract
This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration-sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model-based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm.
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Parikh J, Di Achille P, Kozloski J, Gurev V. Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment. Front Pharmacol 2019; 10:1054. [PMID: 31680938 PMCID: PMC6797832 DOI: 10.3389/fphar.2019.01054] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 08/20/2019] [Indexed: 01/08/2023] Open
Abstract
Multiscale computational models of the heart are being extensively investigated for improved assessment of drug-induced torsades de pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics such as action potential duration and net charge carried by ionic currents (qNet) have been proposed as potential candidates for TdP risk stratification after being tested on small datasets. Unlike purely statistical approaches, model-derived metrics are thought to provide mechanism-based classification. In particular, qNet has been recently proposed as a surrogate metric for early afterdepolarizations (EADs), which are known to be cellular triggers of TdP. Analysis of critical model components and of the ion channels that have major impact on model-derived metrics can lead to improvements in the confidence of the prediction. In this paper, we analyze large populations of virtual drugs to systematically examine the influence of different ion channels on model-derived metrics that have been proposed for proarrhythmic risk assessment. We demonstrate via global sensitivity analysis (GSA) that model-derived metrics are most sensitive to different sets of input parameters. Similarly, important differences in sensitivity to specific channel blocks are highlighted when classifying drugs into different risk categories by either qNet or a metric directly based on simulated EADs. In particular, the higher sensitivity of qNet to the block of the late sodium channel might explain why its classification accuracy is better than that of the EAD-based metric, as shown for a small set of known drugs. Our results highlight the need for a better mechanistic interpretation of promising metrics like qNet based on a formal analysis of models. GSA should, therefore, constitute an essential component of the in silico workflow for proarrhythmic risk assessment, as an improved understanding of the structure of model-derived metrics could increase confidence in model-predicted risk.
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Christophe B, Crumb WJ. Impact of disease state on arrhythmic event detection by action potential modelling in cardiac safety pharmacology. J Pharmacol Toxicol Methods 2018; 96:15-26. [PMID: 30580044 DOI: 10.1016/j.vascn.2018.12.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 12/11/2018] [Accepted: 12/17/2018] [Indexed: 11/15/2022]
Abstract
INTRODUCTION The use of in silico cardiac action potential simulations is one of the pillars of the CiPA initiative (Comprehensive in vitro Proarrhythmia Assay) currently under evaluation designed to detect more accurately proarrhythmic liabilities of new drug candidate. In order to take into account the variability of clinical situations, we propose to improve this method by studying the impact of various disease states on arrhythmic events induced by 30 torsadogenic or non-torsadogenic compounds. METHOD In silico modelling was done on the human myocytes using the Dutta revised O'Hara-Rudy algorithm. Results were analysed using a new metric based on the compound IC50s against the seven cardiac ionic currents considered to be the most important by the CiPA initiative (IKr, IKs, INa, INaL, IK1, Ito, ICaL) and the minimal rate of action potential voltage decrease calculated at the early-afterdepolarization (EAD) take-off membrane voltage (Vmin). RESULTS The specific threshold at which each torsadogenic compounds induced EAD, was exacerbated by the presence of cardiac risk factors ranked as follows: congestive heart failure > hypertrophic cardiomyopathy > cardiac pause > no risk factor. Non-torsadogenic compounds induced no EAD even in the presence of cardiac risk factors. DISCUSSION The present study highlighted the impact of pre-existing cardiovascular disease on arrhythmic event detection suggesting that disease state modelling may need to be incorporated in order to fully realize the goal of the CiPA paradigm in a more accurate predictability of proarrhythmic liabilities of new drug candidate.
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Affiliation(s)
| | - William J Crumb
- Nova Research Laboratories LLC, 1441 Canal Street, New Orleans, LA 70112, USA.
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Parikh J, Gurev V, Rice JJ. Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features. Front Pharmacol 2017; 8:816. [PMID: 29184497 PMCID: PMC5694470 DOI: 10.3389/fphar.2017.00816] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 10/27/2017] [Indexed: 12/16/2022] Open
Abstract
While pre-clinical Torsades de Pointes (TdP) risk classifiers had initially been based on drug-induced block of hERG potassium channels, it is now well established that improved risk prediction can be achieved by considering block of non-hERG ion channels. The current multi-channel TdP classifiers can be categorized into two classes. First, the classifiers that take as input the values of drug-induced block of ion channels (direct features). Second, the classifiers that are built on features extracted from output of the drug-induced multi-channel blockage simulations in the in-silico models (derived features). The classifiers built on derived features have thus far not consistently provided increased prediction accuracies, and hence casts doubt on the value of such approaches given the cost of including biophysical detail. Here, we propose a new two-step method for TdP risk classification, referred to as Multi-Channel Blockage at Early After Depolarization (MCB@EAD). In the first step, we classified the compound that produced insufficient hERG block as non-torsadogenic. In the second step, the role of non-hERG channels to modulate TdP risk are considered by constructing classifiers based on direct or derived features at critical hERG block concentrations that generates EADs in the computational cardiac cell models. MCB@EAD provides comparable or superior TdP risk classification of the drugs from the direct features in tests against published methods. TdP risk for the drugs highly correlated to the propensity to generate EADs in the model. However, the derived features of the biophysical models did not improve the predictive capability for TdP risk assessment.
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Affiliation(s)
| | | | - John J. Rice
- IBM T. J. Watson Research Center, Yorktown Heights, NY, United States
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McMillan B, Gavaghan DJ, Mirams GR. Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicator. Toxicol Res (Camb) 2017; 6:912-921. [PMID: 29456831 PMCID: PMC5779076 DOI: 10.1039/c7tx00141j] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 09/12/2017] [Indexed: 12/19/2022] Open
Abstract
Drug-induced Torsades de Pointes (TdP) arrhythmia is of major interest in predictive toxicology. Drugs which cause TdP block the hERG cardiac potassium channel. However, not all drugs that block hERG cause TdP. As such, further understanding of the mechanistic route to TdP is needed. Early afterdepolarisations (EADs) are a cell-level phenomenon in which the membrane of a cardiac cell depolarises a second time before repolarisation, and EADs are seen in hearts during TdP. Therefore, we propose a method of predicting TdP using induced EADs combined with multiple ion channel block in simulations using biophysically-based mathematical models of human ventricular cell electrophysiology. EADs were induced in cardiac action potential models using interventions based on diseases that are known to cause EADs, including: increasing the conduction of the L-type calcium channel, decreasing the conduction of the hERG channel, and shifting the inactivation curve of the fast sodium channel. The threshold of intervention that was required to cause an EAD was used to classify drugs into clinical risk categories. The metric that used L-type calcium induced EADs was the most accurate of the EAD metrics at classifying drugs into the correct risk categories, and increased in accuracy when combined with action potential duration measurements. The EAD metrics were all more accurate than hERG block alone, but not as predictive as simpler measures such as simulated action potential duration. This may be because different routes to EADs represent risk well for different patient subgroups, something that is difficult to assess at present.
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Affiliation(s)
- Beth McMillan
- Computational Biology , Dept. of Computer Science , University of Oxford , Oxford , OX1 3QD , UK . ; ; Tel: +44 (0)1865 273838
| | - David J Gavaghan
- Computational Biology , Dept. of Computer Science , University of Oxford , Oxford , OX1 3QD , UK . ; ; Tel: +44 (0)1865 273838
| | - Gary R Mirams
- Centre for Mathematical Biology , School of Mathematical Sciences , University of Nottingham , Nottingham , NG7 2RD , UK
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Identification of Na+/K+-ATPase inhibition-independent proarrhythmic ionic mechanisms of cardiac glycosides. Sci Rep 2017; 7:2465. [PMID: 28550304 PMCID: PMC5446409 DOI: 10.1038/s41598-017-02496-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 04/13/2017] [Indexed: 12/17/2022] Open
Abstract
The current study explored the Na+/K+-ATPase (NKA) inhibition-independent proarrhythmic mechanisms of cardiac glycosides (CGs) which are well-known NKA inhibitors. With the cytosolic Ca2+ chelated by EGTA and BAPTA or extracellular Ca2+ replaced by Ba2+, effects of bufadienolides (bufalin (BF) and cinobufagin (CBG)) and cardenolides (ouabain (Oua) and pecilocerin A (PEA)) on the L-type calcium current (ICa,L) were recorded in heterologous expression Cav1.2-CHO cells and human embryonic stem cell-derived cardiomyocytes (hESC-CMs). BF and CBG demonstrated a concentration-dependent (0.1 to 100 µM) ICa,L inhibition (maximal ≥50%) without and with the NKA activity blocked by 10 µM Oua. BF significantly shortened the action potential duration at 1.0 µM and shortened the extracellular field potential duration at 0.01~1.0 µM. On the other hand, BF and CBG at 100 µM demonstrated a strong inhibition (≥40%) of the rapidly activating component of the delayed rectifier K+ current (IKr) in heterologous expression HEK293 cells and prolonged the APD of the heart of day-3 Zebrafish larva with disrupted rhythmic contractions. Moreover, hESC-CMs treated with BF (10 nM) for 24 hours showed moderate yet significant prolongation in APD90. In conclusion, our data indicate that CGs particularly bufadienolides possess cytosolic [Ca2+]i- and NKA inhibition- independent proarrhythmic potential through ICa,L and IKr inhibitions.
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Paci M, Hyttinen J, Rodriguez B, Severi S. Human induced pluripotent stem cell-derived versus adult cardiomyocytes: an in silico electrophysiological study on effects of ionic current block. Br J Pharmacol 2015; 172:5147-60. [PMID: 26276951 PMCID: PMC4629192 DOI: 10.1111/bph.13282] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Revised: 07/29/2015] [Accepted: 08/03/2015] [Indexed: 12/28/2022] Open
Abstract
Background and Purpose Two new technologies are likely to revolutionize cardiac safety and drug development: in vitro experiments on human‐induced pluripotent stem cell‐derived cardiomyocytes (hiPSC‐CMs) and in silico human adult ventricular cardiomyocyte (hAdultV‐CM) models. Their combination was recently proposed as a potential replacement for the present hERG‐based QT study for pharmacological safety assessments. Here, we systematically compared in silico the effects of selective ionic current block on hiPSC‐CM and hAdultV‐CM action potentials (APs), to identify similarities/differences and to illustrate the potential of computational models as supportive tools for evaluating new in vitro technologies. Experimental Approach In silico AP models of ventricular‐like and atrial‐like hiPSC‐CMs and hAdultV‐CM were used to simulate the main effects of four degrees of block of the main cardiac transmembrane currents. Key Results Qualitatively, hiPSC‐CM and hAdultV‐CM APs showed similar responses to current block, consistent with results from experiments. However, quantitatively, hiPSC‐CMs were more sensitive to block of (i) L‐type Ca2+ currents due to the overexpression of the Na+/Ca2+ exchanger (leading to shorter APs) and (ii) the inward rectifier K+ current due to reduced repolarization reserve (inducing diastolic potential depolarization and repolarization failure). Conclusions and Implications In silico hiPSC‐CMs and hAdultV‐CMs exhibit a similar response to selective current blocks. However, overall hiPSC‐CMs show greater sensitivity to block, which may facilitate in vitro identification of drug‐induced effects. Extrapolation of drug effects from hiPSC‐CM to hAdultV‐CM and pro‐arrhythmic risk assessment can be facilitated by in silico predictions using biophysically‐based computational models.
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Affiliation(s)
- M Paci
- Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland
| | - J Hyttinen
- Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland
| | - B Rodriguez
- Department of Computer Science, University of Oxford, Oxford, UK
| | - S Severi
- Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Cesena (FC), Italy
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Cavero I, Holzgrefe H. CiPA: Ongoing testing, future qualification procedures, and pending issues. J Pharmacol Toxicol Methods 2015; 76:27-37. [PMID: 26159293 DOI: 10.1016/j.vascn.2015.06.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2015] [Revised: 06/04/2015] [Accepted: 06/25/2015] [Indexed: 01/04/2023]
Abstract
INTRODUCTION The comprehensive in vitro proarrhythmia assay (CiPA) is a nonclinical, mechanism-based paradigm for assessing drug proarrhythmic liability. TOPICS COVERED The first CiPA assay determines effects on cloned human cardiac ion channels. The second investigates whether the latter study-generated metrics engender proarrhythmic markers on a computationally reconstructed human ventricular action potential. The third evaluates conclusions from, and searches possibly missed effects by in silico analysis, in human stem cell-derived cardiomyocytes (hSC-CMs). CiPA ad hoc Expert-Working Groups have proposed patch clamp protocols for seven cardiac ion channels, a modified O'Hara-Rudy model for in silico analysis, detailed procedures for field (MEA) and action potential (VSD) measurements in hSC-CMs, and 29 reference drugs for CiPA assay testing and validation. DISCUSSION CiPA adoption as drug development tool for identifying electrophysiological mechanisms conferring proarrhythmic liability to candidate drugs is a complex, multi-functional task requiring significant time, reflection, and efforts to be fully achieved.
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