Drug-induced Pro-arrhythmic Risk Research Articles

Contractility assessment using aligned human iPSC-derived cardiomyocytes

IntroductionCardiac safety assessment, such as lethal arrhythmias and contractility dysfunction, is critical during drug development. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been shown to be useful in predicting drug-induced proarrhythmic risk through international validation studies. Although cardiac contractility is another key function, fit-for-purpose hiPSC-CMs in evaluating drug-induced contractile dysfunction remain poorly understood. In this study, we investigated whether alignment of hiPSC-CMs on nanopatterned culture plates can assess drug-induced contractile changes more efficiently than non-aligned monolayer culture. MethodsAligned hiPSC-CMs were obtained by culturing on 96-well culture plates with a ridge-groove-ridge nanopattern on the bottom surface, while non-aligned hiPSC-CMs were cultured on regular 96-well plates. Next-generation sequencing and qPCR experiments were performed for gene expression analysis. Contractility of the hiPSC-CMs was assessed using an imaging-based motion analysis system. ResultsWhen cultured on nanopatterned plates, hiPSC-CMs exhibited an aligned morphology and enhanced expression of genes encoding proteins that regulate contractility, including myosin heavy chain, calcium channel, and ryanodine receptor. Compared to cultures on regular plates, the aligned hiPSC-CMs also showed both enhanced contraction and relaxation velocity. In addition, the aligned hiPSC-CMs showed a more physiological response to positive and negative inotropic agents, such as isoproterenol and verapamil. DiscussionTaken together, the aligned hiPSC-CMs exhibited enhanced structural and functional properties, leading to an improved capacity for contractility assessment compared to the non-aligned cells. These findings suggest that the aligned hiPSC-CMs can be used to evaluate drug-induced cardiac contractile changes.

Facilitation of hERG Activation by Its Blocker: A Mechanism to Reduce Drug-Induced Proarrhythmic Risk.

Modulation of the human Ether-à-go-go-Related Gene (hERG) channel, a crucial voltage-gated potassium channel in the repolarization of action potentials in ventricular myocytes of the heart, has significant implications on cardiac electrophysiology and can be either antiarrhythmic or proarrhythmic. For example, hERG channel blockade is a leading cause of long QT syndrome and potentially life-threatening arrhythmias, such as torsades de pointes. Conversely, hERG channel blockade is the mechanism of action of Class III antiarrhythmic agents in terminating ventricular tachycardia and fibrillation. In recent years, it has been recognized that less proarrhythmic hERG blockers with clinical potential or Class III antiarrhythmic agents exhibit, in addition to their hERG-blocking activity, a second action that facilitates the voltage-dependent activation of the hERG channel. This facilitation is believed to reduce the proarrhythmic potential by supporting the final repolarizing of action potentials. This review covers the pharmacological characteristics of hERG blockers/facilitators, the molecular mechanisms underlying facilitation, and their clinical significance, as well as unresolved issues and requirements for research in the fields of ion channel pharmacology and drug-induced arrhythmias.

The impact of uncertainty in hERG binding mechanism on in silico predictions of drug-induced proarrhythmic risk.

Drug-induced reduction of the rapid delayed rectifier potassium current carried by the human Ether-à-go-go-Related Gene (hERG) channel is associated with increased risk of arrhythmias. Recent updates to drug safety regulatory guidelines attempt to capture each drug's hERG binding mechanism by combining in vitro assays with in silico simulations. In this study, we investigate the impact on in silico proarrhythmic risk predictions due to uncertainty in the hERG binding mechanism and physiological hERG current model. Possible pharmacological binding models were designed for the hERG channel to account for known and postulated small molecule binding mechanisms. After selecting a subset of plausible binding models for each compound through calibration to available voltage-clamp electrophysiology data, we assessed their effects, and the effects of different physiological models, on proarrhythmic risk predictions. For some compounds, multiple binding mechanisms can explain the same data produced under the safety testing guidelines, which results in different inferred binding rates. This can result in substantial uncertainty in the predicted torsade risk, which often spans more than one risk category. By comparison, we found that the effect of a different hERG physiological current model on risk classification was subtle. The approach developed in this study assesses the impact of uncertainty in hERG binding mechanisms on predictions of drug-induced proarrhythmic risk. For some compounds, these results imply the need for additional binding data to decrease uncertainty in safety-critical applications.

Evaluation of four in silico biomarkers for drug-induced proarrhythmic risk: COVID-19 off-label therapies case study

Evaluation of four in silico biomarkers for drug-induced proarrhythmic risk: COVID-19 off-label therapies case study

Estimation of uncertainty in multi-level in silico models predicting biomarkers of drug-induced proarrhythmic risk

Estimation of uncertainty in multi-level in silico models predicting biomarkers of drug-induced proarrhythmic risk

Confounders and Pharmacological Characterization When Using the QT, JTp, and Tpe Intervals in Beagle Dogs.

Corrected QT (QTc) interval is an essential proarrhythmic risk biomarker, but recent data have identified limitations to its use. The J to T-peak (JTp) interval is an alternative biomarker for evaluating drug-induced proarrhythmic risk. The aim of this study was to evaluate pharmacological effects using spatial magnitude leads and DII electrocardiogram (ECG) leads and common ECG confounders (ie, stress and body temperature changes) on covariate adjusted QT (QTca), covariate adjusted JTp (JTpca), and covariate adjusted T-peak to T-end (Tpeca) intervals. Beagle dogs were exposed to body hyper- (42 °C) or hypothermic (33 °C) conditions or were administered epinephrine to assess confounding effects on heart rate corrected QTca, JTpca, and Tpeca intervals. Dofetilide (0.1, 0.3, 1.0 mg/kg), ranolazine (100, 140, 200 mg/kg), and verapamil (7, 15, 30, 43, 62.5 mg/kg) were administered to evaluate pharmacological effects. Covariate adjusted QT (slope -12.57 ms/°C) and JTpca (-14.79 ms/°C) were negatively correlated with body temperature but Tpeca was minimally affected. Epinephrine was associated with QTca and JTpca shortening, which could be related to undercorrection in the presence of tachycardia, while minimal effects were observed for Tpeca. There were no significant ECG change following ranolazine administration. Verapamil decreased QTca and JTpca intervals and increased Tpeca, whereas dofetilide increased QTca and JTpca intervals but had inconsistent effects on Tpeca. Results highlight potential confounders on QTc interval, but also on JTpca and Tpeca intervals in nonclinical studies. These potential confounding effects may be relevant to the interpretation of ECG data obtained from nonclinical drug safety studies with Beagle dogs.

In Silico Classifiers for the Assessment of Drug Proarrhythmicity.

Drug-induced torsade de pointes (TdP) is a life-threatening ventricular arrhythmia responsible for the withdrawal of many drugs from the market. Although currently used TdP risk-assessment methods are effective, they are expensive and prone to produce false positives. In recent years, in silico cardiac simulations have proven to be a valuable tool for the prediction of drug effects. The objective of this work is to evaluate different biomarkers of drug-induced proarrhythmic risk and to develop an in silico risk classifier. Cellular simulations were performed using a modified version of the O'Hara et al. ventricular action potential model and existing pharmacological data (IC50 and effective free therapeutic plasma concentration, EFTPC) for 109 drugs of known torsadogenic risk (51 positive). For each compound, four biomarkers were tested: Tx (drug concentration leading to a 10% prolongation of the action potential over the EFTPC), TqNet (net charge carried by ionic currents when exposed to 10 times the EFTPC with respect to the net charge in control), Ttriang (triangulation for a drug concentration of 10 times the EFTPC over triangulation in control), and TEAD (drug concentration originating early afterdepolarizations over EFTPC). Receiver operating characteristic (ROC) curves were built for each biomarker to evaluate their individual predictive quality. At the optimal cutoff point, accuracies for Tx, TqNet, Ttriang, and TEAD were 89.9, 91.7, 90.8, and 78.9% respectively. The resulting accuracy of the hERG IC50 test (current biomarker) was 78.9%. When combining Tx, TqNet and Ttriang into a classifier based on decision trees, the prediction improves, achieving an accuracy of 94.5%. The sensitivity analysis revealed that most of the effects on the action potential are mainly due to changes in IKr, ICaL, INaL and IKs. In fact, considering that drugs affect only these four currents, TdP risk classification can be as accurate as when considering effects on the seven main currents proposed by the CiPA initiative. Finally, we built a ready-to-use tool (based on more than 450 000 simulations), which can be used to quickly assess the proarrhythmic risk of a compound. In conclusion, our in silico tool can be useful for the preclinical assessment of TdP-risk and to reduce costs related with new drug development. The TdP risk-assessment tool and the software used in this work are available at https://riunet.upv.es/handle/10251/136919.

In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk.

Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( IKs and IKr, respectively) and the L-type calcium current ( ICaL) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC50 based test.

Action Potential Recording and Pro-arrhythmia Risk Analysis in Human Ventricular Trabeculae.

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.

In Silico Simulation Tool for Evaluation of Drug-Induced Proarrhythmic Risk based on Biophysical Mathematical Model of Human Ventricular Cardiomyocytes

In Silico Simulation Tool for Evaluation of Drug-Induced Proarrhythmic Risk based on Biophysical Mathematical Model of Human Ventricular Cardiomyocytes

Simulation of L-Type Calcium Currents using Different Experimental Data Sources: from Cell Line to iPS-Derived Cardiomyocyte

Drug-induced pro-arrhythmic risk has been one of the main causes for drug candidate failure and has even led to compound withdrawn from the market. A new cardiac safety paradigm that combines in-vitro screening of multiple ion channels and in-silico tools, particularly biophysically-detailed cardiac electrophysiology models, has been encouraged by the FDA, HESI, Cardiac Safety Research Consortium & Safety Pharmacology Society.CaV1.2 channel (conducting the L-type Calcium current (ICaL)) plays an important role in cardiac electrophysiology. Blockade of ICaL can mitigate the pro-arrhythmic risk for multi-channel blockers (e.g. verapamil). For drug development, L-type calcium current data can be obtained from different experimental sources. Cell lines over-expressing the human CaV1.2 channel are normally used for HT compound screening. And recently iPS-derived cardiomyocytes have become an increasingly widespread model in pharmaceutical industry.In this study, the kinetics (steady state activation, inactivation and recovery from inactivation) of CaV1.2 CaL from over-expressed CHO cells and iPS-derived cardiomyocytes were measured using Ca2+ containing or Ba2+ containing solutions (to distinguish between Calcium-dependent and Voltage-dependent inactivations). Several in-silico models were used to emulate the experimental protocols, the simulated ICaL was extracted and compared with experimental data.Comparing simulated traces using data obtained from these two experiment sources, we can learn a lot about the biophysical and biological models and their translational value.

パッチクランプ法を用いた細胞薬理実験と心臓シミュレータを組み合わせた薬物スクリーニング手法

We developed a novel cardiotoxicity testing system combining in vitro channel assays and a three-dimensional heart simulator. The inhibitory effects of drugs were measured for the six ion channels using the automated patch clamp technique. According to the dose-inhibition relations thus obtained, effects of drugs under various plasma concentrations were reproduced by changing parameters values of 22 million cell models implemented in the heart simulator. This system can predict drug-induced proarrhythmic risk more accurately compared with the currently used methods such as the QT interval and the hERG test.

Prediction of Thorough QT study results using action potential simulations based on ion channel screens

IntroductionDetection of drug-induced pro-arrhythmic risk is a primary concern for pharmaceutical companies and regulators. Increased risk is linked to prolongation of the QT interval on the body surface ECG. Recent studies have shown that multiple ion channel interactions can be required to predict changes in ventricular repolarisation and therefore QT intervals. In this study we attempt to predict the result of the human clinical Thorough QT (TQT) study, using multiple ion channel screening which is available early in drug development. MethodsIon current reduction was measured, in the presence of marketed drugs which have had a TQT study, for channels encoded by hERG, CaV1.2, NaV1.5, KCNQ1/MinK, and Kv4.3/KChIP2.2. The screen was performed on two platforms — IonWorks Quattro (all 5 channels, 34 compounds), and IonWorks Barracuda (hERG & CaV1.2, 26 compounds). Concentration–effect curves were fitted to the resulting data, and used to calculate a percentage reduction in each current at a given concentration.Action potential simulations were then performed using the ten Tusscher and Panfilov (2006), Grandi et al. (2010) and O'Hara et al. (2011) human ventricular action potential models, pacing at 1Hz and running to steady state, for a range of concentrations. ResultsWe compared simulated action potential duration predictions with the QT prolongation observed in the TQT studies. At the estimated concentrations, simulations tended to underestimate any observed QT prolongation. When considering a wider range of concentrations, and conventional patch clamp rather than screening data for hERG, prolongation of ≥5ms was predicted with up to 79% sensitivity and 100% specificity. DiscussionThis study provides a proof-of-principle for the prediction of human TQT study results using data available early in drug development. We highlight a number of areas that need refinement to improve the method's predictive power, but the results suggest that such approaches will provide a useful tool in cardiac safety assessment.

Arrhythmic risk biomarkers for the assessment of drug cardiotoxicity: from experiments to computer simulations

In this paper, we illustrate how advanced computational modelling and simulation can be used to investigate drug-induced effects on cardiac electrophysiology and on specific biomarkers of pro-arrhythmic risk. To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels. The review highlights the variety of proposed biomarkers, the complexity of the mechanisms of drug-induced pro-arrhythmia and the existence of significant animal species differences in drug-induced effects on cardiac electrophysiology. Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market. Computational modelling and simulation has significantly contributed to the understanding of cardiac electrophysiology and arrhythmias over the last 40 years. In the second part of this paper, we illustrate how state-of-the-art open source computational modelling and simulation tools can be used to simulate multi-scale effects of drug-induced ion channel block in ventricular electrophysiology at the cellular, tissue and whole ventricular levels for different animal species. We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.

Temporal variability of QT interval and changes in T wave morphology in dogs as markers of the clinical risk of drug-induced proarrhythmia

Introduction The aim of this experiment was to establish the usefulness of assessing temporal variability of the QT interval and changes in the T wave morphology in dogs as markers of pro-arrhythmic risk in humans. For this purpose, the electrocardiographic effects of astemizole and cisapride, two well known pro-arrhythmic drugs in humans, were assessed in dogs. Methods: Astemizole was administered intravenously at single doses of 1 and 3 mg/kg whilst cisapride was administered orally at doses of 1.5 and 6 mg/kg. Electrocardiograms (ECG) were recorded before and after treatment. From each ECG tracing, QT intervals were recorded over 100 beats for calculation of the mean and standard deviation (SD) of QT and mean corrected QT (QTc). The coefficient of variation of QT (CV = SD/mean) was calculated as an indicator of QT temporal variability. The changes in T wave morphology were assessed in precordial lead CV5RL. Results: Astemizole increased both the QTc interval and the CV of QT. Increases in these parameters also occurred after cisapride, but were less marked than after astemizole. In addition, both compounds produced a notching of the T wave, consisting of the presence of two peaks. Discussion: The effects of astemizole and cisapride on the CV of QT and their propensity to induce of T wave notching are consistent with the blocking of I Kr channels and indicate, respectively, an increase in temporal variability of cardiac repolarization and an increased heterogeneity of the repolarization of cardiac cells across the myocardium. These changes are key triggers of arrhythmic events and are thus consistent with the pro-arrhythmic properties of these drugs. This study therefore indicates that the evaluation of CV of QT and T wave morphology in dogs may help in predicting drug-induced pro-arrhythmic risk in humans.