A temperature-dependent in silico model of the human ether-à-go-go-related (hERG) gene channel

Advances in ion channel high throughput screening: where are we in 2023?

INTRODUCTION

Automated Patch Clamp (APC) technology has become an integral element in ion channel research, drug discovery and development pipelines to overcome the use of the highly time-consuming manual patch clamp (MPC) procedures. This automated technology offers increased throughput and promises a new model in obtaining ion channel recordings, which has significant relevance to the development of novel therapies and safety profiling of candidate therapeutic compounds.

AREAS COVERED

This article reviews the recent innovations in APC technology, including platforms, and highlights how they have facilitated usage in both industry and academia. The review also provides an overview of the ion channel research endeavors and how APC platforms have contributed to the understanding of ion channel research, pharmacological tools and therapeutics. Furthermore, the authors provide their opinion on the challenges and goals for APC technology going forward to accelerate academic research and drug discovery across a host of therapeutic areas.

EXPERT OPINION

It is clear that APC technology has progressed drug discovery programs, specifically in the field of neuroscience and cardiovascular research. The challenge for the future is to keep pace with fundamental research and improve translation of the large datasets obtained.

Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment

Reduction of the rapid delayed rectifier potassium current (IKr) via drug binding to the human Ether-à-go-go-Related Gene (hERG) channel is a well recognised mechanism that can contribute to an increased risk of Torsades de Pointes. Mathematical models have been created to replicate the effects of channel blockers, such as reducing the ionic conductance of the channel. Here, we study the impact of including state-dependent drug binding in a mathematical model of hERG when translating hERG inhibition to action potential changes. We show that the difference in action potential predictions when modelling drug binding of hERG using a state-dependent model versus a conductance scaling model depends not only on the properties of the drug and whether the experiment achieves steady state, but also on the experimental protocols. Furthermore, through exploring the model parameter space, we demonstrate that the state-dependent model and the conductance scaling model generally predict different action potential prolongations and are not interchangeable, while at high binding and unbinding rates, the conductance scaling model tends to predict shorter action potential prolongations. Finally, we observe that the difference in simulated action potentials between the models is determined by the binding and unbinding rate, rather than the trapping mechanism. This study demonstrates the importance of modelling drug binding and highlights the need for improved understanding of drug trapping which can have implications for the uses in drug safety assessment.

Translating the measurement of hERG kinetics and drug block for CiPA to a high throughput platform

The Comprehensive in vitro Proarrhythmic Assay (CiPA) has promoted use of in silico models of drug effects on cardiac repolarization to improve proarrhythmic risk prediction. These models contain a pharmacodynamic component describing drug binding to hERG channels that required in vitro data for kinetics of block, in addition to potency, to constrain them. To date, development and validation has been undertaken using data from manual patch-clamp. The application of this approach at scale requires the development of a high-throughput, automated patch-clamp (APC) implementation. Here, we present a comprehensive analysis of the implementation of the Milnes, or CiPA dynamic protocol, on an APC platform, including quality control and data analysis. Kinetics and potency of block were assessed for bepridil, cisapride, terfenadine and verapamil with data retention/QC pass rate of 21.8% overall, or as high as 50.4% when only appropriate sweep lengths were considered for drugs with faster kinetics. The variability in IC₅₀ and kinetics between manual and APC was comparable to that seen between sites/platforms in previous APC studies of potency. Whilst the experimental success is less than observed in screens of potency alone, it is still significantly greater than manual patch. With the modifications to protocol design, including sweep length, number of repetitions, and leak correction recommended in this study, this protocol can be applied on APC to acquire data comparable to manual patch clamp.

Sensitivity Analysis of Ion Channel Conductance on Myocardial Electromechanical Delay: Computational Study

It is well known that cardiac electromechanical delay (EMD) can cause dyssynchronous heart failure (DHF), a prominent cardiovascular disease (CVD). This work computationally assesses the conductance variation of every ion channel on the cardiac cell to give rise to EMD prolongation. The electrical and mechanical models of human ventricular tissue were simulated, using a population approach with four conductance reductions for each ion channel. Then, EMD was calculated by determining the difference between the onset of action potential and the start of cell shortening. Finally, EMD data were put into the optimized conductance dimensional stacking to show which ion channel has the most influence in elongating the EMD. We found that major ion channels, such as L-type calcium (CaL), slow-delayed rectifier potassium (Ks), rapid-delayed rectifier potassium (Kr), and inward rectifier potassium (K1), can significantly extend the action potential duration (APD) up to 580 ms. Additionally, the maximum intracellular calcium (Cai) concentration is greatly affected by the reduction in channel CaL, Ks, background calcium, and Kr. However, among the aforementioned major ion channels, only the CaL channel can play a superior role in prolonging the EMD up to 83 ms. Furthermore, ventricular cells with long EMD have been shown to inherit insignificant mechanical response (in terms of how strong the tension can grow and how far length shortening can go) compared with that in normal cells. In conclusion, despite all variations in every ion channel conductance, only the CaL channel can play a significant role in extending EMD. In addition, cardiac cells with long EMD tend to have inferior mechanical responses due to a lack of Cai compared with normal conditions, which are highly likely to result in a compromised pump function of the heart.

Electrophysiological characterization of the hERG R56Q LQTS variant and targeted rescue by the activator RPR260243

Human Ether-à-go-go (hERG) channels contribute to cardiac repolarization, and inherited variants or drug block are associated with long QT syndrome type 2 (LQTS2) and arrhythmia. Therefore, hERG activator compounds present a therapeutic opportunity for targeted treatment of LQTS. However, a limiting concern is over-activation of hERG resurgent current during the action potential and abbreviated repolarization. Activators that slow deactivation gating (type I), such as RPR260243, may enhance repolarizing hERG current during the refractory period, thus ameliorating arrhythmogenicity with reduced early repolarization risk. Here, we show that, at physiological temperature, RPR260243 enhances hERG channel repolarizing currents conducted in the refractory period in response to premature depolarizations. This occurs with little effect on the resurgent hERG current during the action potential. The effects of RPR260243 were particularly evident in LQTS2-associated R56Q mutant channels, whereby RPR260243 restored WT-like repolarizing drive in the early refractory period and diastolic interval, combating attenuated protective currents. In silico kinetic modeling of channel gating predicted little effect of the R56Q mutation on hERG current conducted during the action potential and a reduced repolarizing protection against afterdepolarizations in the refractory period and diastolic interval, particularly at higher pacing rates. These simulations predicted partial rescue from the arrhythmic effects of R56Q by RPR260243 without risk of early repolarization. Our findings demonstrate that the pathogenicity of some hERG variants may result from reduced repolarizing protection during the refractory period and diastolic interval with limited effect on action potential duration, and that the hERG channel activator RPR260243 may provide targeted antiarrhythmic potential in these cases.

Using cardiac ionic cell models to interpret clinical data

For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi-scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi-scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology.

Calibration of ionic and cellular cardiac electrophysiology models

Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.

In silico models for evaluating proarrhythmic risk of drugs

Safety evaluation of drugs requires examination of the risk of generating Torsade de Pointes (TdP) because it can lead to sudden cardiac death. Until recently, the QT interval in the electrocardiogram (ECG) has been used in the evaluation of TdP risk because the QT interval is known to be associated with the development of TdP. Although TdP risk evaluation based on QT interval has been successful in removing drugs with TdP risk from the market, some safe drugs may have also been affected due to the low specificity of QT interval-based evaluation. For more accurate evaluation of drug safety, the comprehensive in vitro proarrhythmia assay (CiPA) has been proposed by regulatory agencies, industry, and academia. Although the CiPA initiative includes in silico evaluation of cellular action potential as a component, attempts to utilize in silico simulation in drug safety evaluation are expanding, even to simulating human ECG using biophysical three-dimensional models of the heart and torso under the effects of drugs. Here, we review recent developments in the use of in silico models for the evaluation of the proarrhythmic risk of drugs. We review the single cell, one-dimensional, two-dimensional, and three-dimensional models and their applications reported in the literature and discuss the possibility of utilizing ECG simulation in drug safety evaluation.

When Does the IC50 Accurately Assess the Blocking Potency of a Drug?

Preclinical assessment of drug-induced proarrhythmicity is typically evaluated by the potency of the drug to block the potassium human ether-à-go-go-related gene (hERG) channels, which is currently quantified by the IC₅₀. However, channel block depends on the experimental conditions. Our aim is to improve the evaluation of the blocking potency of drugs by designing experimental stimulation protocols to measure the IC₅₀ that will help to decide whether the IC₅₀ is representative enough. We used the state-of-the-art mathematical models of the cardiac electrophysiological activity to design three stimulation protocols that enhance the differences in the probabilities to occupy a certain conformational state of the channel and, therefore, the potential differences in the blocking effects of a compound. We simulated an extensive set of 144 in silico I_Kr blockers with different kinetics and affinities to conformational states of the channel and we also experimentally validated our key predictions. Our results show that the IC₅₀ protocol dependency relied on the tested compounds. Some of them showed no differences or small differences on the IC₅₀ value, which suggests that the IC₅₀ could be a good indicator of the blocking potency in these cases. However, others provided highly protocol dependent IC₅₀ values, which could differ by even 2 orders of magnitude. Moreover, the protocols yielding the maximum IC₅₀ and minimum IC₅₀ depended on the drug, which complicates the definition of a "standard" protocol to minimize the influence of the stimulation protocol on the IC₅₀ measurement in safety pharmacology. As a conclusion, we propose the adoption of our three-protocol IC₅₀ assay to estimate the potency to block hERG in vitro. If the IC₅₀ values obtained for a compound are similar, then the IC₅₀ could be used as an indicator of its blocking potency, otherwise kinetics and state-dependent binding properties should be accounted.

General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy

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.

Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence

Ion channel behavior can depend strongly on temperature, with faster kinetics at physiological temperatures leading to considerable changes in currents relative to room temperature. These temperature-dependent changes in voltage-dependent ion channel kinetics (rates of opening, closing, inactivating, and recovery) are commonly represented with Q₁₀ coefficients or an Eyring relationship. In this article, we assess the validity of these representations by characterizing channel kinetics at multiple temperatures. We focus on the human Ether-à-go-go-Related Gene (hERG) channel, which is important in drug safety assessment and commonly screened at room temperature so that results require extrapolation to physiological temperature. In Part I of this study, we established a reliable method for high-throughput characterization of hERG1a (Kv11.1) kinetics, using a 15-second information-rich optimized protocol. In this Part II, we use this protocol to study the temperature dependence of hERG kinetics using Chinese hamster ovary cells overexpressing hERG1a on the Nanion SyncroPatch 384PE, a 384-well automated patch-clamp platform, with temperature control. We characterize the temperature dependence of hERG gating by fitting the parameters of a mathematical model of hERG kinetics to data obtained at five distinct temperatures between 25 and 37°C and validate the models using different protocols. Our models reveal that activation is far more temperature sensitive than inactivation, and we observe that the temperature dependency of the kinetic parameters is not represented well by Q₁₀ coefficients; it broadly follows a generalized, but not the standardly-used, Eyring relationship. We also demonstrate that experimental estimations of Q₁₀ coefficients are protocol dependent. Our results show that a direct fit using our 15-s protocol best represents hERG kinetics at any given temperature and suggests that using the Generalized Eyring theory is preferable if no experimental data are available to derive model parameters at a given temperature.

Recording of multiple ion current components and action potentials in human induced pluripotent stem cell-derived cardiomyocytes via automated patch-clamp

INTRODUCTION

The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative proposes a three-step approach to evaluate proarrhythmogenic liability of drug candidates: effects on individual ion channels in heterologous expression systems, integrating these data into in-silico models of the electrical activity of human cardiomyocytes, and comparison with experiments on human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). Here we introduce patch-clamp electrophysiology techniques on hiPSC-CM to combine two of the CiPA steps in one assay.

METHODS

We performed automated patch-clamp experiments on hiPSC-CM (Cor.4U^®, Ncardia) using the CytoPatch™2 platform in ruptured whole-cell and β-escin-perforated-patch configurations. A combination of three voltage-clamp protocols allowed recording of five distinct ion current components (voltage-gated Na⁺ current, L-type Ca²⁺ current, transient outward K⁺ current, delayed rectifier K⁺ current, and "funny" hyperpolarization-activated current) from the same cell. We proved their molecular identity by either Na⁺ replacement with choline or by applying specific blockers: nifedipine, cisapride, chromanol 293B, phrixotoxin-1, ZD7288. We developed a C++ script for automated analysis of voltage-clamp recordings and computation of ion current/conductance surface density for these five cardiac ion currents.

RESULTS

The distributions from n = 54 hiPSC-CM in "ruptured" patch-clamp vs. n = 35 hiPSC-CM in β-escin-perforated patch-clamp were similar for membrane capacitance, access resistance, and ion current/conductance surface densities. The β-escin-perforated configuration resulted in improved stability of action potential (AP) shape and duration over a 10-min interval, with APD90 decay rate 0.7 ± 1.6%/min (mean ± SD, n = 4) vs. 4.6 ± 1.1%/min. (n = 3) for "ruptured" approach (p = 0.0286, one-tailed Mann-Whitney test).

DISCUSSION

The improved stability obtained here will allow development of CiPA-compliant automated patch-clamp assays on hiPSC-CM. Future applications include the study of multi ion-channel blocking properties of drugs using dynamic-clamp protocols, adding a valuable new tool to the arsenal of safety-pharmacology.

Quantitative Systems Pharmacology Models for a New International Cardiac Safety Regulatory Paradigm: An Overview of the Comprehensive In Vitro Proarrhythmia Assay In Silico Modeling Approach

As a relatively new discipline, quantitative systems pharmacology has seen a significant increase in the application and utility of drug development. One area that could greatly benefit from such an approach is in the proarrhythmia assessment of new drugs. The Comprehensive In Vitro Proarrhythmia Assay (CiPA) Initiative is a global public-private partnership project that has developed an integrated approach using mechanistic in silico models for proarrhythmia risk prediction. Progress to date has led to the formation of the International Council on Harmonisation Implementation Working Group to revise regulatory guidelines via the Questions-and-Answers process to address the best practices for proarrhythmia models and how they can impact clinical drug development. This article reviews the CiPA in silico model-development process, focusing on its unique development and validation strategy, and summarizes the lessons learned as consideration points for the ongoing implementation of CiPA-like in silico models in drug development.

The influence of hERG1a and hERG1b isoforms on drug safety screening in iPSC-CMs

The human Ether-à-go-go Related Gene (hERG) encodes the pore forming subunit of the channel that conducts the rapid delayed rectifier potassium current I_Kr. I_Kr drives repolarization in the heart and when I_Kr is dysfunctional, cardiac repolarization delays, the QT interval on the electrocardiogram (ECG) prolongs and the risk of developing lethal arrhythmias such as Torsade de Pointes (TdP) increases. TdP risk is incorporated in drug safety screening for cardiotoxicity where hERG is the main target since the I_Kr channels appear highly sensitive to blockage. hERG block is also included as an important read-out in the Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative which aims to combine in vitro and in silico experiments on induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to screen for cardiotoxicity. However, the hERG channel has some unique features to consider for drug safety screening, which we will discuss in this study. The hERG channel consists of different isoforms, hERG1a and hERG1b, which individually influence the kinetics of the channel and the drug response in the human heart and in iPSC-CMs. hERG1b is often underappreciated in iPSC-CM studies, drug screening assays and in silico models, and the fact that its contribution might substantially differ between iPSC-CM and healthy but also diseased human heart, adds to this problem. In this study we show that the activation kinetics in iPSC-CMs resemble hERG1b kinetics using Cs⁺ as a charge carrier. Not including hERG1b in drug safety testing might underestimate the actual role of hERG1b in repolarization and drug response, and might lead to inappropriate conclusions. We stress to focus more on including hERG1b in drug safety testing concerning I_Kr.

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

Determinants of Isoform-Specific Gating Kinetics of hERG1 Channel: Combined Experimental and Simulation Study

I_Kr is the rapidly activating component of the delayed rectifier potassium current, the ion current largely responsible for the repolarization of the cardiac action potential. Inherited forms of long QT syndrome (LQTS) (Lees-Miller et al., 1997) in humans are linked to functional modifications in the Kv11.1 (hERG) ion channel and potentially life threatening arrhythmias. There is little doubt now that hERG-related component of I_Kr in the heart depends on the tetrameric (homo- or hetero-) channels formed by two alternatively processed isoforms of hERG, termed hERG1a and hERG1b. Isoform composition (hERG1a- vs. the b-isoform) has recently been reported to alter pharmacologic responses to some hERG blockers and was proposed to be an essential factor pre-disposing patients for drug-induced QT prolongation. Very little is known about the gating and pharmacological properties of two isoforms in heart membranes. For example, how gating mechanisms of the hERG1a channels differ from that of hERG1b is still unknown. The mechanisms by which hERG 1a/1b hetero-tetramers contribute to function in the heart, or what role hERG1b might play in disease are all questions to be answered. Structurally, the two isoforms differ only in the N-terminal region located in the cytoplasm: hERG1b is 340 residues shorter than hERG1a and the initial 36 residues of hERG1b are unique to this isoform. In this study, we combined electrophysiological measurements for HEK cells, kinetics and structural modeling to tease out the individual contributions of each isoform to Action Potential formation and then make predictions about the effects of having various mixture ratios of the two isoforms. By coupling electrophysiological data with computational kinetic modeling, two proposed mechanisms of hERG gating in two homo-tetramers were examined. Sets of data from various experimental stimulation protocols (HEK cells) were analyzed simultaneously and fitted to Markov-chain models (M-models). The minimization procedure presented here, allowed assessment of suitability of different Markov model topologies and the corresponding parameters that describe the channel kinetics. The kinetics modeling pointed to key differences in the gating kinetics that were linked to the full channel structure. Interactions between soluble domains and the transmembrane part of the channel appeared to be critical determinants of the gating kinetics. The structures of the full channel in the open and closed states were compared for the first time using the recent Cryo-EM resolved structure for full open hERG channel and an homology model for the closed state, based on the highly homolog EAG1 channel. Key potential interactions which emphasize the importance of electrostatic interactions between N-PAS cap, S4-S5, and C-linker are suggested based on the structural analysis. The derived kinetic parameters were later used in higher order models of cells and tissue to track down the effect of varying the ratios of hERG1a and hERG1b on cardiac action potentials and computed electrocardiograms. Simulations suggest that the recovery from inactivation of hERG1b may contribute to its physiologic role of this isoform in the action potential. Finally, the results presented here contribute to the growing body of evidence that hERG1b significantly affects the generation of the cardiac I_kr and plays an important role in cardiac electrophysiology. We highlight the importance of carefully revisiting the Markov models previously proposed in order to properly account for the relative abundance of the hERG1 a- and b- isoforms.

Translating New Science Into the Drug Review Process: The US FDA's Division of Applied Regulatory Science

In 2011, the US Food and drug Administration (FDA) developed a strategic plan for regulatory science that focuses on developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of FDA-regulated products. In line with this, the Division of Applied Regulatory Science was created to move new science into the Center for Drug Evaluation and Research (CDER) review process and close the gap between scientific innovation and drug review. The Division, located in the Office of Clinical Pharmacology, is unique in that it performs mission-critical applied research and review across the translational research spectrum including in vitro and in vivo laboratory research, in silico computational modeling and informatics, and integrated clinical research covering clinical pharmacology, experimental medicine, and postmarket analyses. The Division collaborates with Offices throughout CDER, across the FDA, other government agencies, academia, and industry. The Division is able to rapidly form interdisciplinary teams of pharmacologists, biologists, chemists, computational scientists, and clinicians to respond to challenging regulatory questions for specific review issues and for longer-range projects requiring the development of predictive models, tools, and biomarkers to speed the development and regulatory evaluation of safe and effective drugs. This article reviews the Division's recent work and future directions, highlighting development and validation of biomarkers; novel humanized animal models; translational predictive safety combining in vitro, in silico, and in vivo clinical biomarkers; chemical and biomedical informatics tools for safety predictions; novel approaches to speed the development of complex generic drugs, biosimilars, and antibiotics; and precision medicine.

Mechanistic Model-Informed Proarrhythmic Risk Assessment of Drugs: Review of the "CiPA" Initiative and Design of a Prospective Clinical Validation Study

The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative is developing and validating a mechanistic-based assessment of the proarrhythmic risk of drugs. CiPA proposes to assess a drug's effect on multiple ion channels and integrate the effects in a computer model of the human cardiomyocyte to predict proarrhythmic risk. Unanticipated or missed effects will be assessed with human stem cell-derived cardiomyocytes and electrocardiogram (ECG) analysis in early phase I clinical trials. This article provides an overview of CiPA and the rationale and design of the CiPA phase I ECG validation clinical trial, which involves assessing an additional ECG biomarker (J-Tpeak) for QT prolonging drugs. If successful, CiPA will 1) create a pathway for drugs with hERG block / QT prolongation to advance without intensive ECG monitoring in phase III trials if they have low proarrhythmic risk; and 2) enable updating drug labels to be more informative about proarrhythmic risk, not just QT prolongation.

Mechanistic Model-Informed Proarrhythmic Risk Assessment of Drugs: Review of the "CiPA" Initiative and Design of a Prospective Clinical Validation Study

The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative is developing and validating a mechanistic-based assessment of the proarrhythmic risk of drugs. CiPA proposes to assess a drug's effect on multiple ion channels and integrate the effects in a computer model of the human cardiomyocyte to predict proarrhythmic risk. Unanticipated or missed effects will be assessed with human stem cell-derived cardiomyocytes and electrocardiogram (ECG) analysis in early phase I clinical trials. This article provides an overview of CiPA and the rationale and design of the CiPA phase I ECG validation clinical trial, which involves assessing an additional ECG biomarker (J-Tpeak) for QT prolonging drugs. If successful, CiPA will 1) create a pathway for drugs with hERG block / QT prolongation to advance without intensive ECG monitoring in phase III trials if they have low proarrhythmic risk; and 2) enable updating drug labels to be more informative about proarrhythmic risk, not just QT prolongation.

Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (C_max). However, when drug effects were extrapolated above 10× C_max, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC₅₀-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC₅₀-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm.

Natural products modulating the hERG channel: heartaches and hope

This review covers natural products modulating the hERG potassium channel. Risk assessment strategies, structural features of blockers, and the duality target/antitarget are discussed.

Covering: 1996–December 2016

The human Ether-à-go-go Related Gene (hERG) channel is a voltage-gated potassium channel playing an essential role in the normal electrical activity in the heart. It is involved in the repolarization and termination of action potentials in excitable cardiac cells. Mutations in the hERG gene and hERG channel blockage by small molecules are associated with increased risk of fatal arrhythmias. Several drugs have been withdrawn from the market due to hERG channel-related cardiotoxicity. Moreover, as a result of its notorious ligand promiscuity, this ion channel has emerged as an important antitarget in early drug discovery and development. Surprisingly, the hERG channel blocking profile of natural compounds present in frequently consumed botanicals (i.e. dietary supplements, spices, and herbal medicinal products) is not routinely assessed. This comprehensive review will address these issues and provide a critical compilation of hERG channel data for isolated natural products and extracts over the past two decades (1996–2016). In addition, the review will provide (i) a solid basis for the molecular understanding of the physiological functions of the hERG channel, (ii) the translational potential of in vitro/in vivo results to cardiotoxicity in humans, (iii) approaches for the identification of hERG channel blockers from natural sources, (iv) future perspectives for cardiac safety guidelines and their applications within phytopharmaceuticals and dietary supplements, and (v) novel applications of hERG channel modulation (e.g. as a drug target).

Quantitative systems toxicology

The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of evaluating the adverse effects of drugs in animals to predict human health risks. The U.S. Environmental Protection Agency recognized the need to develop innovative toxicity testing strategies and asked the National Research Council to develop a long-range vision and strategy for toxicity testing in the 21st century. The vision aims to reduce the use of animals and drug development costs through the integration of computational modeling and in vitro experimental methods that evaluates the perturbation of toxicity-related pathways. Towards this vision, collaborative quantitative systems pharmacology and toxicology modeling endeavors (QSP/QST) have been initiated amongst numerous organizations worldwide. In this article, we discuss how quantitative structure-activity relationship (QSAR), network-based, and pharmacokinetic/pharmacodynamic modeling approaches can be integrated into the framework of QST models. Additionally, we review the application of QST models to predict cardiotoxicity and hepatotoxicity of drugs throughout their development. Cell and organ specific QST models are likely to become an essential component of modern toxicity testing, and provides a solid foundation towards determining individualized therapeutic windows to improve patient safety.

Inhibitory effects and mechanism of dihydroberberine on hERG channels expressed in HEK293 cells

The human ether-a-go-go-related gene (hERG) potassium channel conducts rapid delayed rectifier potassium currents (I_Kr) and contributes to phase III cardiac action potential repolarization. Drugs inhibit hERG channels by binding to aromatic residues in hERG helixes. Berberine (BBR) has multiple actions, and its hydrogenated derivative dihydroberberine (DHB) is a potential candidate for developing new drugs. Previous studies have demonstrated that BBR blocks hERG channels and prolongs action potential duration (APD). Our present study aimed to investigate the effects and mechanism of DHB on hERG channels. Protein expression and the hERG current were analyzed using western blotting and patch-clamp, respectively. DHB inhibited the hERG current concentration-dependently after instantaneous perfusion, accelerated channel inactivation by directly binding tyrosine (Tyr652) and phenylalanine (Phe656), and decreased mature (155-kDa) and simultaneously increased immature (135-kDa) hERG expression, respectively. This suggests disruption of forward trafficking of hERG channels. Besides, DHB remarkably reduced heat shock protein 90 (Hsp90) expression and its interaction with hERG, indicating that DHB disrupted hERG trafficking by impairing channel folding. Meanwhie, DHB enhanced the expression of cleaved activating transcription factor-6 (ATF-6), a biomarker of unfolded protein response (UPR). Expression of calnexin and calreticulin, chaperones activated by ATF-6 to facilitate channel folding, were also increased, which indicating UPR activation. Additionally, the degradation rate of mature 155-kDa hERG increased following DHB exposure. In conclusion, we demonstrated that DHB acutely blocked hERG channels by binding the aromatic Tyr652 and Phe656. DHB may decrease hERG plasma membrane expression through two pathways involving disruption of forward trafficking of immature hERG channels and enhanced degradation of mature hERG channels. Furthermore, forward trafficking was disrupted by impaired channel folding associated with altered interactions between hERG proteins and chaperones. Finally, trafficking inhibition activated UPR, and mature hERG channel degradation was increased by DHB.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology

BACKGROUND

The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model.

METHODS AND RESULTS

Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk.

CONCLUSIONS

Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm.

Measuring kinetics and potency of hERG block for CiPA

INTRODUCTION

The Comprehensive in vitro Proarrhythmic Assay (CiPA) aims to update current cardiac safety testing to better evaluate arrhythmic risk. A central theme of CiPA is the use of in silico approaches to risk prediction incorporating models of drug binding to hERG. To parameterize these models, accurate in vitro measurement of potency and kinetics of block is required. The Ion Channel Working Group was tasked with: i) selecting a protocol that could measure kinetics of block and was easily implementable on automated platforms for future rollout in industry and ii) acquiring a reference dataset using the standardized protocol.

METHODS

Data were acquired using a 'step depolarisation' protocol using manual patch-clamp at ambient temperature.

RESULTS

Potency, kinetics and trapping characteristics of hERG block for the CiPA training panel of twelve drugs were measured. Timecourse of block and trapping characteristics could be reliably measured if the time constant for onset of block was between ~500ms and ~15s. Seven drugs, however had time courses of block faster than this cut-off.

DISCUSSION

Here we describe the implementation of the standardized protocol for measurement of kinetics and potency of hERG block for CiPA. The results highlight the challenges in identifying a single protocol to measure hERG block over a range of kinetics. The dataset from this study is being used by the In Silico Working Group to develop models of drug binding for risk prediction and is freely available as a 'gold standard' ambient temperature dataset to evaluate variability across high throughput platforms.

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.