Comprehensive in vitro Proarrhythmia Assay (C i PA): Pending issues for successful validation and implementation

Multitargeting in cardioprotection: An example of biaromatic compounds

A multitarget drug design approach is actively developing in modern medicinal chemistry and pharmacology, especially with regard to multifactorial diseases such as cardiovascular diseases, cancer, and neurodegenerative diseases. A detailed study of many well-known drugs developed within the single-target approach also often reveals additional mechanisms of their real pharmacological action. One of the multitarget drug design approaches can be the identification of the basic pharmacophore models corresponding to a wide range of the required target ligands. Among such models in the group of cardioprotectors is the linked biaromatic system. This review develops the concept of a "basic pharmacophore" using the biaromatic pharmacophore of cardioprotectors as an example. It presents an analysis of possible biological targets for compounds corresponding to the biaromatic pharmacophore and an analysis of the spectrum of biological targets for the five most known and most studied cardioprotective drugs corresponding to this model, and their involvement in the biological effects of these drugs.

Optical Mapping of Cardiomyocytes in Monolayer Derived from Induced Pluripotent Stem Cells

Optical mapping is a powerful imaging technique widely adopted to measure membrane potential changes and intracellular Ca2+ variations in excitable tissues using voltage-sensitive dyes and Ca2+ indicators, respectively. This powerful tool has rapidly become indispensable in the field of cardiac electrophysiology for studying depolarization wave propagation, estimating the conduction velocity of electrical impulses, and measuring Ca2+ dynamics in cardiac cells and tissues. In addition, mapping these electrophysiological parameters is important for understanding cardiac arrhythmia mechanisms. In this review, we delve into the fundamentals of cardiac optical mapping technology and its applications when applied to hiPSC-derived cardiomyocytes and discuss related advantages and challenges. We also provide a detailed description of the processing and analysis of optical mapping data, which is a crucial step in the study of cardiac diseases and arrhythmia mechanisms for extracting and comparing relevant electrophysiological parameters.

Assessment of the proarrhythmic effects of repurposed antimalarials for COVID-19 treatment using a comprehensive in vitro proarrhythmia assay (CiPA)

Due to the outbreak of the SARS-CoV-2 virus, drug repurposing and Emergency Use Authorization have been proposed to treat the coronavirus disease 2019 (COVID-19) during the pandemic. While the efficiency of the drugs has been discussed, it was identified that certain compounds, such as chloroquine and hydroxychloroquine, cause QT interval prolongation and potential cardiotoxic effects. Drug-induced cardiotoxicity and QT prolongation may lead to life-threatening arrhythmias such as torsades de pointes (TdP), a potentially fatal arrhythmic symptom. Here, we evaluated the risk of repurposed pyronaridine or artesunate-mediated cardiac arrhythmias alone and in combination for COVID-19 treatment through in vitro and in silico investigations using the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. The potential effects of each drug or in combinations on cardiac action potential (AP) and ion channels were explored using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and Chinese hamster ovary (CHO) cells transiently expressing cardiac ion channels (Nav1.5, Cav1.2, and hERG). We also performed in silico computer simulation using the optimized O'Hara-Rudy human ventricular myocyte model (ORd model) to classify TdP risk. Artesunate and dihydroartemisinin (DHA), the active metabolite of artesunate, are classified as a low risk of inducing TdP based on the torsade metric score (TMS). Moreover, artesunate does not significantly affect the cardiac APs of hiPSC-CMs even at concentrations up to 100 times the maximum serum concentration (Cmax). DHA modestly prolonged at APD90 (10.16%) at 100 times the Cmax. When considering Cmax, pyronaridine, and the combination of both drugs (pyronaridine and artesunate) are classified as having an intermediate risk of inducing TdP. However, when considering the unbound concentration (the free fraction not bound to carrier proteins or other tissues inducing pharmacological activity), both drugs are classified as having a low risk of inducing TdP. In summary, pyronaridine, artesunate, and a combination of both drugs have been confirmed to pose a low proarrhythmogenic risk at therapeutic and supratherapeutic (up to 4 times) free Cmax. Additionally, the CiPA initiative may be suitable for regulatory use and provide novel insights for evaluating drug-induced cardiotoxicity.

On the perspective of an aging population and its potential impact on drug attrition and pre-clinical cardiovascular safety assessment

There is no refuting that America's population is growing older: for the first time in US history, by 2034 older adults (defined as >65 years of age) are projected to outnumber children under the age of 18, representing approximately 70 million people or almost 25% of the population (Lloyd-Jones et al., 2010). Described as the "silver tsunami", this flood of older adults is driven by the baby boomers (people born after World War II, from 1946 to 1964): they are now reaching old age, living longer due to significant advances in healthcare coupled with a record low birth rate, resulting in a skewed elderly population demographic. Unfortunately, older adults are also becoming increasingly unhealthy. Many often suffer from several chronic disorders requiring the use of multiple medications at a level higher than any other age group, resulting in an increased risk of drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Indeed, because of age-related changes in pharmacokinetics (PK) and pharmacodynamics (PD), older adults are also more vulnerable to drug toxicity. Prescribed drugs certainly improve a range of health outcomes, but also often cause considerable ADRs, leading to devastating consequences for patients, clinicians, and manufacturers. Therefore, safe and effective pharmacotherapy remains one of the greatest growing challenges in geriatric medicine. In this review we examine the effects of aging and its impact on the increased risk of experiencing ADRs, resulting in devastating consequences for patients and manufacturers. We assess the current regulatory considerations related to the development of drugs for this population and highlight issues, concerns, and propose alternatives to the standard battery of tests focused on assessing cardiovascular (CV) safety in an attempt to develop safer and efficient new drugs for the growing elderly demographic.

Molecular dynamics simulations suggest possible activation and deactivation pathways in the hERG channel

The elusive activation/deactivation mechanism of hERG is investigated, a voltage-gated potassium channel involved in severe inherited and drug-induced cardiac channelopathies, including the Long QT Syndrome. Firstly, the available structural data are integrated by providing a homology model for the closed state of the channel. Secondly, molecular dynamics combined with a network analysis revealed two distinct pathways coupling the voltage sensor domain with the pore domain. Interestingly, some LQTS-related mutations known to impair the activation/deactivation mechanism are distributed along the identified pathways, which thus suggests a microscopic interpretation of their role. Split channels simulations clarify a surprising feature of this channel, which is still able to gate when a cut is introduced between the voltage sensor domain and the neighboring helix S5. In summary, the presented results suggest possible activation/deactivation mechanisms of non-domain-swapped potassium channels that may aid in biomedical applications.

Costa et al. present the electro-mechanical coupling between the voltage sensor and pore domain of the hERG channel using a combination of molecular dynamics simulations and theoretical network analyses.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Linked biaromatic compounds as cardioprotective agents

Cardiovascular diseases (CVDs) are widespread in the modern world, and their number is constantly growing. For a long time, CVDs have been the leading cause of morbidity and mortality worldwide. Drugs for the treatment of CVD have been developed almost since the beginning of the 20th century, and a large number of effective cardioprotective agents of various classes have been created. Nevertheless, the need for the design and development of new safe drugs for the treatment of CVD remains. Literature data indicate that a huge number of cardioprotective agents of various generations and mechanisms correspond to a single generalized pharmacophore model containing two aromatic nuclei linked by a linear linker. In this regard, we put forward a concept for the design of a new generation of cardioprotective agents with a multitarget mechanism of action within the indicated pharmacophore model. This review is devoted to a generalization of the currently known compounds with cardioprotective properties and corresponding to the pharmacophore model of biaromatic compounds linked by a linear linker. Particular attention is paid to the history of the creation of these drugs, approaches to their design, and analysis of the structure-action relationship within each class.

Reliable identification of cardiac conduction abnormalities in drug discovery using automated patch clamp II: Best practices for Nav1.5 peak current in a high throughput screening environment

INTRODUCTION

For reliable identification of cardiac safety risk, compounds should be screened for activity on cardiac ion channels in addition to hERG, including Na_V1.5 and Ca_V1.2. We identified different parameters that might affect IC₅₀s of compounds on Na_V1.5 peak and late currents recorded using automated patch clamp (APC) and suggest outlines for best practices.

METHODS

APC instruments SyncroPatch 384 and Patchliner were used to record Na_V1.5 peak and late current. Up to 24 CiPA compounds were used to investigate effects of voltage protocol, holding potential (-80 mV or - 95 mV) and temperature (23 ± 1 °C or 36 ± 1 °C) on IC₅₀ values on hNa_V1.5 overexpressed in HEK or CHO cells either as frozen cells or running cultures.

RESULTS

The IC₅₀s of 18 compounds on the Na_V1.5 peak current recorded on the SyncroPatch 384 using the CiPA step-ramp protocol correlated well with the literature. The use of frozen or cultured cells did not affect IC₅₀s but voltage protocol and holding potential did cause differences in IC₅₀ values. Temperature can affect V_half of inactivation and also compound potency. A compound incubation time of 5-6 min was sufficient for most compounds, however slow acting compounds such as terfenadine required longer to reach maximum effect.

DISCUSSION

We conclude that holding potential, voltage protocol and temperature can affect IC₅₀ values and recommend the use of the CiPA step-ramp protocol at physiological temperature to record Na_V1.5 peak and late currents for cardiac safety. Further recommendations include: a minimum compound incubation time of 5 min, a replicate number of 4 and the use of positive and negative controls for reliable IC₅₀s.

Investigation of cardiac glycosides from oleander in a human induced pluripotent stem cells derived cardiomyocyte model

The ingestion of Nerium oleander and Thevetia peruviana are common causes for poisoning in Southeast Asia. All parts of the oleander shrub contain cardiac glycosides of the cardenolide type. These glycosides act via inhibition of a Na⁺/K⁺-ATPase which might cause severe arrhythmia and subsequent death in oleander-poisoned patients. The current study uses human induced pluripotent stem cells derived cardiomyocytes (hiPSC-CM) in a microelectrode array (MEA) system to assess the cardiac effects of neriifolin, oleandrin, digitoxigenin, peruvoside and thevetin A from the oleander plant. Digoxin was used as established reference compound. All tested compounds showed a corrected field potential duration (FPDc) shortening and was the lowest for 600 nM digitoxigenin with -36.9 ± 1.2 %. Next to the dose-dependent pro-arrhythmic potential, a complete beat arrest of the spontaneously beating hiPSC-CM was observed at a concentration of 300 nM for neriifolin, 600 nM for oleandrin and 1000 nM for digitoxigenin and peruvoside. Thevetin A did not cause arrhythmia up to a final concentration of 1000 nM. Thus, it was possible to establish a cardiac effect rank order of the tested substances: neriifolin > oleandrin > digitoxigenin = peruvoside > digoxin > thevetin A.

Investigating inherited arrhythmias using hiPSC-derived cardiomyocytes

Fundamental to the functional behavior of cardiac muscle is that the cardiomyocytes are integrated as a functional syncytium. Disrupted electrical activity in the cardiac tissue can lead to serious complications including cardiac arrhythmias. Therefore, it is important to study electrophysiological properties of the cardiac tissue. With advancements in stem cell research, protocols for the production of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been established, providing great potential in modelling cardiac arrhythmias and drug testing. The hiPSC-CM model can be used in conjunction with electrophysiology-based platforms to examine the electrical activity of the cardiac tissue. Techniques for determining the myocardial electrical activity include multielectrode arrays (MEAs), optical mapping (OM), and patch clamping. These techniques provide critical approaches to investigate cardiac electrical abnormalities that underlie arrhythmias.

hiPSC-Derived Cardiac Tissue for Disease Modeling and Drug Discovery

Relevant, predictive normal, or disease model systems are of vital importance for drug development. The difference between nonhuman models and humans could contribute to clinical trial failures despite ideal nonhuman results. As a potential substitute for animal models, human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs) provide a powerful tool for drug toxicity screening, modeling cardiovascular diseases, and drug discovery. Here, we review recent hiPSC-CM disease models and discuss the features of hiPSC-CMs, including subtype and maturation and the tissue engineering technologies for drug assessment. Updates from the international multisite collaborators/administrations for development of novel drug discovery paradigms are also summarized.

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: T_x (drug concentration leading to a 10% prolongation of the action potential over the EFTPC), T_qNet (net charge carried by ionic currents when exposed to 10 times the EFTPC with respect to the net charge in control), T_triang (triangulation for a drug concentration of 10 times the EFTPC over triangulation in control), and T_EAD (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 T_x, T_qNet, T_triang, and T_EAD 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 T_x, T_qNet and T_triang 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 I_Kr, I_CaL, I_NaL and I_Ks. 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.

Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges

The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross-disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP-based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders.

Drug-induced Proarrhythmia and Torsade de Pointes: A Primer for Students and Practitioners of Medicine and Pharmacy

Multiple marketing withdrawals due to proarrhythmic concerns occurred in the United States, Canada, and the United Kingdom in the late 1980s to early 2000s. This primer reviews the clinical implications of a drug's identified proarrhythmic liability, the issues associated with these safety-related withdrawals, and the actions taken by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) and by regulatory agencies in terms of changing drug development practices and introducing new nonclinical and clinical tests to asses proarrhythmic liability. ICH Guidelines S7B and E14 were released in 2005. Since then, they have been adopted by many regional regulatory authorities and have guided nonclinical and clinical proarrhythmic cardiac safety assessments during drug development. While this regulatory paradigm has been successful in preventing drugs with unanticipated potential for inducing the rare but potentially fatal polymorphic ventricular arrhythmia torsade de pointes from entering the market, it has led to the termination of drug development programs for other potentially useful medicines because of isolated results from studies with limited predictive value. Research efforts are now exploring alternative approaches to better predict potential proarrhythmic liabilities. For example, in the domain of human electrocardiographic assessments, concentration-response modeling conducted during phase 1 clinical development has recently become an accepted alternate primary methodology to the ICH E14 "thorough QT/QTc" study for defining a drug's corrected QT interval prolongation liability under certain conditions. When a drug's therapeutic benefit is considered important at a public health level but there is also an identified proarrhythmic liability that may result from administration of the single drug in certain individuals and/or drug-drug interactions, marketing approval will be accompanied by appropriate directions in the drug's prescribing information. Health-care professionals in the fields of medicine and pharmacy need to consider the prescribing information in conjunction with individual patients' clinical characteristics and concomitant medications when prescribing and dispensing such drugs.

Composite Biomarkers Derived from Micro-Electrode Array Measurements and Computer Simulations Improve the Classification of Drug-Induced Channel Block

The Micro-Electrode Array (MEA) device enables high-throughput electrophysiology measurements that are less labor-intensive than patch-clamp based techniques. Combined with human-induced pluripotent stem cells cardiomyocytes (hiPSC-CM), it represents a new and promising paradigm for automated and accurate in vitro drug safety evaluation. In this article, the following question is addressed: which features of the MEA signals should be measured to better classify the effects of drugs? A framework for the classification of drugs using MEA measurements is proposed. The classification is based on the ion channels blockades induced by the drugs. It relies on an in silico electrophysiology model of the MEA, a feature selection algorithm and automatic classification tools. An in silico model of the MEA is developed and is used to generate synthetic measurements. An algorithm that extracts MEA measurements features designed to perform well in a classification context is described. These features are called composite biomarkers. A state-of-the-art machine learning program is used to carry out the classification of drugs using experimental MEA measurements. The experiments are carried out using five different drugs: mexiletine, flecainide, diltiazem, moxifloxacin, and dofetilide. We show that the composite biomarkers outperform the classical ones in different classification scenarios. We show that using both synthetic and experimental MEA measurements improves the robustness of the composite biomarkers and that the classification scores are increased.

Real Patient and its Virtual Twin: Application of Quantitative Systems Toxicology Modelling in the Cardiac Safety Assessment of Citalopram

A quantitative systems toxicology (QST) model for citalopram was established to simulate, in silico, a 'virtual twin' of a real patient to predict the occurrence of cardiotoxic events previously reported in patients under various clinical conditions. The QST model considers the effects of citalopram and its most notable electrophysiologically active primary (desmethylcitalopram) and secondary (didesmethylcitalopram) metabolites, on cardiac electrophysiology. The in vitro cardiac ion channel current inhibition data was coupled with the biophysically detailed model of human cardiac electrophysiology to investigate the impact of (i) the inhibition of multiple ion currents (I_Kr, I_Ks, I_CaL); (ii) the inclusion of metabolites in the QST model; and (iii) unbound or total plasma as the operating drug concentration, in predicting clinically observed QT prolongation. The inclusion of multiple ion channel current inhibition and metabolites in the simulation with unbound plasma citalopram concentration provided the lowest prediction error. The predictive performance of the model was verified with three additional therapeutic and supra-therapeutic drug exposure clinical cases. The results indicate that considering only the hERG ion channel inhibition of only the parent drug is potentially misleading, and the inclusion of active metabolite data and the influence of other ion channel currents should be considered to improve the prediction of potential cardiac toxicity. Mechanistic modelling can help bridge the gaps existing in the quantitative translation from preclinical cardiac safety assessment to clinical toxicology. Moreover, this study shows that the QST models, in combination with appropriate drug and systems parameters, can pave the way towards personalised safety assessment.

Have the Findings from Clinical Risk Prediction and Trials Any Key Messages for Safety Pharmacology?

Anti-arrhythmic drugs are a mainstay in the management of symptoms related to arrhythmias, and are adjuncts in prevention and treatment of life-threatening ventricular arrhythmias. However, they also have the potential for pro-arrhythmia and thus the prediction of arrhythmia predisposition and drug response are critical issues. Clinical trials are the latter stages in the safety testing and efficacy process prior to market release, and as such serve as a critical safeguard. In this review, we look at some of the lessons to be learned from approaches to arrhythmia prediction in patients, clinical trials of drugs used in the treatment of arrhythmias, and the implications for the design of pre-clinical safety pharmacology testing.

Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come?

Cardiotoxicity is a severe side effect of drugs that induce structural or electrophysiological changes in heart muscle cells. As a result, the heart undergoes failure and potentially lethal arrhythmias. It is still a major reason for drug failure in preclinical and clinical phases of drug discovery. Current methods for predicting cardiotoxicity are based on guidelines that combine electrophysiological analysis of cell lines expressing ion channels ectopically in vitro with animal models and clinical trials. Although no new cases of drugs linked to lethal arrhythmias have been reported since the introduction of these guidelines in 2005, their limited predictive power likely means that potentially valuable drugs may not reach clinical practice. Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are now emerging as potentially more predictive alternatives, particularly for the early phases of preclinical research. However, these cells are phenotypically immature and culture and assay methods not standardized, which could be a hurdle to the development of predictive computational models and their implementation into the drug discovery pipeline, in contrast to the ambitions of the comprehensive pro-arrhythmia in vitro assay (CiPA) initiative. Here, we review present and future preclinical cardiotoxicity screening and suggest possible hPSC-CM-based strategies that may help to move the field forward. Coordinated efforts by basic scientists, companies and hPSC banks to standardize experimental conditions for generating reliable and reproducible safety indices will be helpful not only for cardiotoxicity prediction but also for precision medicine.

LINKED ARTICLES

This article is part of a themed section on New Insights into Cardiotoxicity Caused by Chemotherapeutic Agents. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.21/issuetoc.

In silico assessment of the effects of various compounds in MEA/hiPSC-CM assays: Modeling and numerical simulations

We propose a mathematical approach for the analysis of drugs effects on the electrical activity of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) based on multi-electrode array (MEA) experiments. Our goal is to produce an in silico tool able to simulate drugs action in MEA/hiPSC-CM assays. The mathematical model takes into account the geometry of the MEA and the electrodes' properties. The electrical activity of the stem cells at the ion-channel level is governed by a system of ordinary differential equations (ODEs). The ODEs are coupled to the bidomain equations, describing the propagation of the electrical wave in the stem cells preparation. The field potential (FP) measured by the MEA is modeled by the extracellular potential of the bidomain equations. First, we propose a strategy allowing us to generate a field potential in good agreement with the experimental data. We show that we are able to reproduce realistic field potentials by introducing different scenarios of heterogeneity in the action potential. This heterogeneity reflects the differentiation atria/ventricles and the age of the cells. Second, we introduce a drug/ion channels interaction based on a pore block model. We conduct different simulations for five drugs (mexiletine, dofetilide, bepridil, ivabradine and BayK). We compare the simulation results with the field potential collected from experimental measurements. Different biomarkers computed on the FP are considered, including depolarization amplitude, repolarization delay, repolarization amplitude and depolarization-repolarization segment. The simulation results show that the model reflect properly the main effects of these drugs on the FP.

Identification of Ion Currents Components Generating Field Potential Recorded in MEA From hiPSC-CM

OBJECTIVE

Multi electrodes arrays (MEAs) combined with cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) can enable high- or medium-throughput drug screening in safety pharmacology. This technology has recently attracted a lot of attention, in particular from an international initiative named CiPA. But it is currently limited by the difficulty to analyze the measured signals. We propose a strategy to analyze the signals acquired by the MEA and to automatically deduce the channels affected by the drug.

METHODS

Our method is based on the bidomain equations, a model for the MEA electrodes, and an inverse problem strategy.

RESULTS

in silico MEA signals are obtained for two commercial devices and an example of early after depolarization is presented. Then, by processing real signals obtained for four different compounds, our algorithm was able to provide dose-response curves for potassium, sodium, and calcium channels. For ivabradine and moxifloxacin, the IC50 and dose-response curves are in very good agreement with known values.

SIGNIFICANCE

The proposed strategy offers a possible answer to a major question raised by the community of safety pharmacology. By allowing a more automated analysis of the signals, our approach could contribute to promote the technology based on MEA and hiPSC-CMs and, therefore, improve reliability and efficiency of drug screening.

Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes (hPSC-CMs) Using Multi-electrode Arrays (MEAs)

Cardiomyocytes can now be derived with high efficiency from both human embryonic and human induced-Pluripotent Stem Cells (hPSC). hPSC-derived cardiomyocytes (hPSC-CMs) are increasingly recognized as having great value for modeling cardiovascular diseases in humans, especially arrhythmia syndromes. They have also demonstrated relevance as in vitro systems for predicting drug responses, which makes them potentially useful for drug-screening and discovery, safety pharmacology and perhaps eventually for personalized medicine. This would be facilitated by deriving hPSC-CMs from patients or susceptible individuals as hiPSCs. For all applications, however, precise measurement and analysis of hPSC-CM electrical properties are essential for identifying changes due to cardiac ion channel mutations and/or drugs that target ion channels and can cause sudden cardiac death. Compared with manual patch-clamp, multi-electrode array (MEA) devices offer the advantage of allowing medium- to high-throughput recordings. This protocol describes how to dissociate 2D cell cultures of hPSC-CMs to small aggregates and single cells and plate them on MEAs to record their spontaneous electrical activity as field potential. Methods for analyzing the recorded data to extract specific parameters, such as the QT and the RR intervals, are also described here. Changes in these parameters would be expected in hPSC-CMs carrying mutations responsible for cardiac arrhythmias and following addition of specific drugs, allowing detection of those that carry a cardiotoxic risk.

Proarrhythmic risk assessment using conventional and new in vitro assays

Drug-induced QT prolongation is a major safety issue in the drug discovery process. This study was conducted to assess the electrophysiological responses of four substances using established preclinical assays usually used in regulatory studies (hERG channel or Purkinje fiber action potential) and a new assay (human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs)-field potential). After acute exposure, moxifloxacin and dofetilide concentration-dependently decreased I_Kr amplitude (IC₅₀ values: 102 μM and 40 nM, respectively) and lengthened action potential (100 μM moxifloxacin: +23% and 10 nM dofetilide: +18%) and field potential (300 μM moxifloxacin: +76% and 10 nM dofetilide: +38%) durations. Dofetilide starting from 30 nM induced arrhythmia in hiPSC-CMs. Overnight application of pentamidine (10 and 100 μM) and arsenic (1 and 10 μM) decreased I_Kr, whereas they were devoid of effects after acute application. Long-term pentamidine incubation showed a time- and concentration-dependent effect on field potential duration. In conclusion, our data suggest that hiPSC-CMs represent a fully functional cellular electrophysiology model which may significantly improve the predictive validity of in vitro safety studies. Thereafter, lead candidates may be further investigated in patch-clamp assays for mechanistic studies on individual ionic channels or in a multicellular Purkinje fiber preparation for confirmatory studies on cardiac conduction.

Recalibration of nonclinical safety pharmacology assessment to anticipate evolving regulatory expectations

Safety pharmacology (SP) has evolved in terms of architecture and content since the inception of the SP Society (SPS). SP was initially focused on the issue of drug-induced QT prolongation, but has now become a broad spectrum discipline with expanding expectations for evaluation of drug adverse effect liability in all organ systems, not merely the narrow consideration of torsades de pointes (TdP) liability testing. An important part of the evolution of SP has been the elaboration of architecture for interrogation of non-clinical models in terms of model development, model validation and model implementation. While SP has been defined by mandatory cardiovascular, central nervous system (CNS) and respiratory system studies ever since the core battery was elaborated, it also involves evaluation of drug effects on other physiological systems. The current state of SP evolution is the incorporation of emerging new technologies in a wide range of non-clinical drug safety testing models. This will refine the SP process, while potentially expanding the core battery. The continued refinement of automated technologies (e.g., automated patch clamp systems) is enhancing the scope for detection of adverse effect liability (i.e., for more than just IKr blockade), while introducing a potential for speed and accuracy in cardiovascular and CNS SP by providing rapid, high throughput ion channel screening methods for implementation in early drug development. A variety of CNS liability assays, which exploit isolated brain tissue, and in vitro electrophysiological techniques, have provided an additional level of complimentary preclinical safety screens aimed at establishing the seizurogenic potential and risk for memory dysfunction of new chemical entities (NCEs). As with previous editorials that preface the annual themed issue on SP methods published in the Journal of Pharmacological and Toxicological Methods (JPTM), we highlight here the content derived from the most recent (2015) SPS meeting held in Prague, Czech Republic. This issue of JPTM continues the tradition of providing a publication summary of articles primarily presented at the SPS meeting with direct bearing on the discipline of SP. Novel method development and refinement in all areas of the discipline are reflected in the content.