Impact of study design on proarrhythmia prediction in the SCREENIT rabbit isolated heart model

Dynamic features of cardiac vector as alternative markers of drug-induced spatial dispersion

INTRODUCTION

The abnormal amplification of ventricular repolarization dispersion (VRD) has long been linked to proarrhythmia risk. Recently, the measure of VRD through electrocardiogram intervals has been strongly questioned. The search for an efficient and non-invasive surrogate marker of drug-induced dispersion effects constitute an urgent research challenge.

METHODS

Herein, drug-induced ventricular dispersion is generated by d-Sotalol supply in an In-vitro rabbit heart model. A cilindrical chamber simulates the thorax and a multi-electrode net is used to obtain spatial electrocardiographic signals. Cardiac vector dynamics is captured by novel velocity cardiomarkers obtained by quaternion methods. Through statistical analysis and machine learning technics, we compute potential dispersion markers that could define proarrhythmic risk.

RESULTS

The cardiomarkers with the greatest statistical significance, both obtained from the electrical cardiac vector, were: the QT_ω, which is the difference between first and last maxima of angular velocity and λ21_v^T, the roundness of linear velocity. When comparing with the performance of the current standards (89%), this pair was able to correctly separate 21 out of 22 experiments achieving a performance of 95%. Moreover, the QT_ω computes in a much more robust basis the QT interval, the current index for drug regulation.

DISCUSSION

These velocity markers circumvent the problems of accuratelly finding the fiducial points such as the always tricky T-wave end. Given the high performance they achieved, it is provided a promising outcome for future applications to the detection of anomalous changes of heterogeneity that may be useful for the purposes of torsadogenic toxicity studies.

Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning

All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here, we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their proarrhythmic potential. We capitalize on recent developments in machine learning and integrate information across 10 orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the proarrhythmic potential of new drugs. Our study paves the way toward establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.

Assessment of drug-induced proarrhythmia: The importance of study design in the rabbit left ventricular wedge model

In the present study, we investigated an impact of the stimulation rate on the detection of the proarrhythmic potential of 10 reference compounds with effects on different cardiac ion channels in the isolated arterially-perfused rabbit left ventricular wedge preparation. The compounds were tested in the wedge model using two distinct protocols; including baseline stimulation at 1-Hz followed by a brief period at 0.5-Hz, either without an additional brief period of 2-Hz stimulation (i.e. Protocol 1) or with 2-Hz stimulation (i.e. Protocol 2). As expected, QT-prolonging drugs (ibutilide and quinidine) prolonged the QT interval, similarly increased the Torsades de Pointes (TdP) score, and elicited early afterdepolarizations (EADs) in both protocols. HMR1556 and JNJ-303 (IKs blockers) also prolonged the QT interval up to 1μM similarly in both protocols. Nifedipine (Ca(2+) antagonist) shortened the QT interval, and reduced force of contraction similarly in both protocols. However, Na(+) channel blockers (Ia, Ib, Ic) widened the QRS duration more in Protocol 2 than in Protocol 1. Furthermore, it was only possible to detect non-TdP-like ventricular tachycardia/fibrillation (VT/VF) induced by Na(+) blockers and by QT-shortening drugs (levcromakalim and mallotoxin) using the 2-Hz stimulation (Protocol 2). Our data suggest that the inclusion of a brief period of fast stimulation at 2Hz is critical for detecting drug-induced slowing of conduction (QRS widening), QT shortening and associated (non-TdP-like) VT/VF, which are distinct from the QT prolongation/TdP proarrhythmia in isolated, arterially-perfused rabbit left ventricular wedges.

Simulation of early after-depolarisation in non-failing human ventricular myocytes: can this help cardiac safety pharmacology?

BACKGROUND

Identified as being the primary mechanism involved in the induction of torsades de pointes (TdP), early after-depolarisation (EAD) formation is an important parameter in cardiac safety pharmacology. Easily observed experimentally at the cellular or tissue level, EAD can also be simulated by computer algorithms using animal or human models. During the last decade, confidence in these algorithms has greatly increased. We investigated the putative usefulness of EAD simulation for cardiac safety pharmacology.

METHODS

EAD simulations were performed in non-failing human ventricular myocytes using the O'Hara-Rudy dynamic model. The role of each cardiac current was investigated by modifying the amplitude of its activity in the model. Prediction of EAD induction by drugs was based on the ratio of their 50% inhibitory concentration values for various cardiac ionic currents to their maximal effective free therapeutic plasma concentration (EFTPCmax).

RESULTS

In the ventricular endocardial myocytes, EAD was only induced by at least 85% inhibition of the rapid delayed rectifier K(+) current (IKr). The other currents can either induce or prevent EAD under sub- (80% IKr inhibition) or up-threshold conditions (87% IKr inhibition) of EAD. The study of the ability of drugs to induce EAD resulted in a classification which was in agreement with the Tdp risk classification.

CONCLUSION

Based on EAD computer simulation within the human situation, the present study identified the role of various cardiac currents in the EAD formation and suggested that prediction of EAD formation can be useful for early cardiac safety pharmacology.

Keeping the rhythm: hERG and beyond in cardiovascular safety pharmacology

Following its involvement in life-threatening cardiac arrhythmias, the catchword 'hERG' has become infamous in the drug discovery community. The blockade of the ion channel coded by the human ether-á-go-go-related gene (hERG) has been correlated to a prolongation of the QT interval in the ECG, which again is correlated to a potential risk of a life-threatening polymorphic ventricular tachycardia - torsades de pointes (TdP). Therefore, in vitro investigations for blockade of this ion channel have become a standard, starting early in most drug discovery projects and often accompanying the whole project; at some stage, scientists in many medicinal chemistry programs have to deal with hERG channel liabilities. Data for the compound effects on hERG channel activity are generally part of the safety pharmacology risk assessment in regulatory submissions and, at this stage, are ideally conducted in compliance with good laboratory practice. With the withdrawal of clobutinol from the market, owing to its perceived risk of introducing TdP, the importance of the hERG channel has very recently been reconfirmed. Despite being of such importance for drug discovery, the relevance and impact of hERG data are sometimes misinterpreted, as there are drugs that block the hERG-coded ion channel but do not cause TdP, and drugs that cause TdP but do not block the hERG channel. This review aims to provide an overview of TdP, including the cardiac action potential and the ion channels involved in it, as well as on the relevance and interpretation of in vitro hERG channel data and their impact for drug discovery projects. Finally, novel cardiac safety test systems beyond in vitro hERG channel screening are discussed.

The isolated rabbit heart and Purkinje fibers as models for identifying proarrhythmic liability

INTRODUCTION

Delayed ventricular repolarization is associated with rare, but often fatal, polymorphic tachyarrhythmias named Torsades de Pointes. ICH S7B guideline recommends an integrated approach for cardiovascular preclinical evaluation of new drug candidates, including action potential assays (as a Purkinje fiber test) but also proarrhythmia models. The aim of this preliminary study was to compare the respective value of two preclinical in vitro rabbit cardiac preparations-the Purkinje fiber and the isolated perfused heart (Langendorff method)-based on effects of dofetilide, a selective IKr inhibitor.

METHODS

Transmembrane action potentials from rabbit Purkinje fibers were recorded using a conventional intracellular glass microelectrode. Electrocardiograms from rabbit isolated hearts were evaluated for QRS, QT and T wave durations (Tpeak-Tend). The pacing protocol was the same for both preparations (basal rate of 80 bpm and pacing of 40, 60 and 140 bpm). Dofetilide was tested in both systems at concentrations of 1, 3 and 10 nmol/L.

RESULTS

In Purkinje fibers dofetilide induced a concentration- and reverse use-dependent increase in action potential durations measured at 50 and 90% of repolarization. At 10 nmol/L, only 3/10 fibers showed early after depolarizations. In the isolated heart model, dofetilide also induced a similar concentration- and reverse use-dependent increase in QT-interval. From 3 nmol/L, major changes in T wave morphology, R-on-T extrasystoles and TdP were observed, mainly at low rate. Prior to arrhythmias, T wave shape and duration were markedly altered suggesting an increase in the heterogeneity of cardiac ventricular repolarization.

CONCLUSIONS

The effects of dofetilide were comparable in the two models for delayed repolarization but the isolated heart appears to be a better predictor for arrhythmias and a unique in vitro model to assess arrhythmogenic potential of QT prolonging compounds at least when associated with IKr/hERG inhibition.

hERG-related drug toxicity and models for predicting hERG liability and QT prolongation

BACKGROUND

hERG K(+) channels have been recognized as a primary antitarget in safety pharmacology. Their blockade, caused by several drugs with different therapeutic indications, may lead to QT prolongation and, eventually, to potentially fatal arrhythmia, namely torsade de pointes. Therefore, a number of preclinical models have been developed to predict hERG liability early in the drug development process.

OBJECTIVE

The aim of this review is to outline the present state of the art on drug-induced hERG blockade, providing insights on the predictive value of in vitro and in silico models for hERG liability.

METHODS

On the basis of latest reports, high-throughput preclinical models have been discussed outlining advantages and limitations.

CONCLUSION

Although no single model has an absolute value, an integrated risk assessment is recommended to predict the pro-arrhythmic risk of a given drug. This prediction requires expertise from different areas and should encompass emerging issues such as interference with hERG trafficking and QT shortening.

Model systems for the discovery and development of antiarrhythmic drugs

Cardiovascular diseases are the leading cause of mortality worldwide and about 25% of cardiovascular deaths are due to disturbances in cardiac rhythm or "arrhythmias". Arrhythmias were traditionally treated with antiarrhythmic drugs, but increasing awareness of the risks of presently available antiarrhythmic agents has greatly limited their usefulness. Most common treatment algorithms still involve small molecule drugs, and antiarrhythmic agents with improved efficacy and safety are sorely needed. This paper reviews the model systems that are available for discovery and development of new antiarrhythmic drugs. We begin with a presentation of screening methods used to identify specific channel-interacting agents, with a particular emphasis on high-throughput screens. Traditional manual electrophysiological methods, automated electrophysiology, fluorescent dye methods, flux assays and radioligand binding assays are reviewed. We then discuss a variety of relevant arrhythmia models. Two models are widely used in testing for arrhythmogenic actions related to excess action potential prolongation, an important potential adverse effect of chemical entities affecting cardiac rhythm: the methoxamine-sensitized rabbit and the dog with chronic atrioventricular block. We then go on to review models used to assess potential antiarrhythmic actions. For ventricular arrhythmias, chemical induction methods, cardiac or neural electrical stimulation, ischaemic heart models and models of cardiac channelopathies can be used to identify effective antiarrhythmic agents. For atrial arrhythmias, potentially useful models include vagally-maintained atrial fibrillation, acute asphyxia with atrial burst-pacing, sterile pericarditis, Y-shaped atria surgical incisions, chronic atrial dilation models, atrial electrical remodelling due to sustained atrial tachycardia, heart failure-related atrial remodelling, and acute atrial ischaemia. It is hoped that the new technologies now available and the recently-developed models for arrhythmia-response assessment will permit the introduction of newer and more effective antiarrhythmic therapies in the near future.

Preclinical Torsades-de-Pointes screens: advantages and limitations of surrogate and direct approaches in evaluating proarrhythmic risk

The successful development of novel drugs requires the ability to detect (and avoid) compounds that may provoke Torsades-de-Pointes (TdeP) arrhythmia while endorsing those compounds with minimal torsadogenic risk. As TdeP is a rare arrhythmia not readily observed during clinical or post-marketing studies, numerous preclinical models are employed to assess delayed or altered ventricular repolarization (surrogate markers linked to enhanced proarrhythmic risk). This review evaluates the advantages and limitations of selected preclinical models (ranging from the simplest cellular hERG current assay to the more complex in vitro perfused ventricular wedge and Langendorff heart preparations and in vivo chronic atrio-ventricular (AV)-node block model). Specific attention is paid to the utility of concentration-response relationships and "risk signatures" derived from these studies, with the intention of moving beyond predicting clinical QT prolongation and towards prediction of TdeP risk. While the more complex proarrhythmia models may be suited to addressing questionable or conflicting proarrhythmic signals obtained with simpler preclinical assays, further benchmarking of proarrhythmia models is required for their use in the robust evaluation of safety margins. In the future, these models may be able to reduce unwarranted attrition of evolving compounds while becoming pivotal in the balanced integrated risk assessment of advancing compounds.

Sensitive and reliable proarrhythmia in vivo animal models for predicting drug-induced torsades de pointes in patients with remodelled hearts

As an increasing number of non-cardiac drugs have been reported to cause QT interval prolongation and torsades de pointes (TdP), we extensively studied the utility of atrioventricular (AV) block animals as a model to predict their torsadogenic action in human. The present review highlights such in vivo proarrhythmia models. In the case of the canine model, test substances were administered p.o. at conscious state >4 weeks after the induction of AV block, with subsequent Holter ECG monitoring to evaluate drug effects. Control AV block dogs (no pharmacological treatment) survive for several years without TdP attack. For pharmacologically treated dogs, drugs were identified as high, low or no risk. High-risk drugs induced TdP at 1-3 times the therapeutic dose. Low-risk drugs did not induce TdP at this dose range, but induced it at higher doses. No-risk drugs never induced TdP at any dose tested. Electrophysiological, anatomical histological and biochemical adaptations against persistent bradycardia-induced chronic heart failure were observed in AV block dogs. Recently, we have developed another highly sensitive proarrhythmia model using a chronic AV block cynomolgus monkey, which possesses essentially the same pathophysiological adaptations and drug responses as those demonstrated in the canine model. As a common remodelling process leading to a diminished repolarization reserve may present in patients who experience drug-induced TdP and in the AV block animals, the in vivo proarrhythmia models described in this review may be useful for predicting the risk of pharmacologically induced TdP in humans.