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
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paper_title: The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative — Update on progress

paper_content:

The implementation of the ICH S7B and E14 guidelines has been successful in preventing the introduction of potentially torsadogenic drugs to the market, but it has also unduly constrained drug development by focusing on hERG block and QT prolongation as essential determinants of proarrhythmia risk. The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative was established to develop a new paradigm for assessing proarrhythmic risk, building on the emergence of new technologies and an expanded understanding of torsadogenic mechanisms beyond hERG block. An international multi-disciplinary team of regulatory, industry and academic scientists are working together to develop and validate a set of predominantly nonclinical assays and methods that eliminate the need for the thorough-QT study and enable a more precise prediction of clinical proarrhythmia risk. The CiPA effort is led by a Steering Team that provides guidance, expertise and oversight to the various working groups and includes partners from US FDA, HESI, CSRC, SPS, EMA, Health Canada, Japan NIHS, and PMDA. The working groups address the three pillars of CiPA that evaluate drug effects on: 1) human ventricular ionic channel currents in heterologous expression systems, 2) in silico integration of cellular electrophysiologic effects based on ionic current effects, the ion channel effects, and 3) fully integrated biological systems (stem-cell-derived cardiac myocytes and the human ECG). This article provides an update on the progress of the initiative towards its target date of December 2017 for completing validation.
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paper_title: Quantitative Systems Pharmacology: A Case for Disease Models

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Quantitative systems pharmacology (QSP) has emerged as an innovative approach in model-informed drug discovery and development, supporting program decisions from exploratory research through late-stage clinical trials. In this commentary, we discuss the unique value of disease-scale “platform” QSP models that are amenable to reuse and repurposing to support diverse clinical decisions in ways distinct from other pharmacometrics strategies.
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paper_title: Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium.

paper_content:

This white paper provides a summary of a scientific proposal presented at a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/Food and Drug Administration–sponsored Think Tank, held at Food and Drug Administration's White Oak facilities, Silver Spring, MD, on July 23, 2013, with the intention of moving toward consensus on defining a new paradigm in the field of cardiac safety in which proarrhythmic risk would be primarily assessed using nonclinical in vitro human models based on solid mechanistic considerations of torsades de pointes proarrhythmia. This new paradigm would shift the emphasis from the present approach that strongly relies on QTc prolongation (a surrogate marker of proarrhythmia) and could obviate the clinical Thorough QT study during later drug development. These discussions represent current thinking and suggestions for furthering our knowledge and understanding of the public health case for adopting a new, integrated nonclinical in vitro/in silico paradigm, the Comprehensive In Vitro Proarrhythmia Assay, for the assessment of a candidate drug's proarrhythmic liability, and for developing a public-private collaborative program to characterize the data content, quality, and approaches required to assess proarrhythmic risk in the absence of a Thorough QT study. This paper seeks to encourage multistakeholder input regarding this initiative and does not represent regulatory guidance.
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paper_title: Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development.

paper_content:

OBJECTIVE ::: To attempt to determine the relative value of preclinical cardiac electrophysiology data (in vitro and in vivo) for predicting risk of torsade de pointes (TdP) in clinical use. ::: ::: ::: METHODS ::: Published data on hERG (or I(Kr)) activity, cardiac action potential duration (at 90% repolarisation; APD(90)), and QT prolongation in dogs were compared against QT effects and reports of TdP in humans for 100 drugs. These data were set against the free plasma concentrations attained during clinical use (effective therapeutic plasma concentrations; ETPC(unbound)). The drugs were divided into five categories: (1) Class Ia and III antiarrhythmics; (2) Withdrawn from market due to TdP; (3) Measurable incidence/numerous reports of TdP in humans; (4) Isolated reports of TdP in humans; (5) No reports of TdP in humans. ::: ::: ::: RESULTS ::: Data from hERG (or I(Kr)) assays in addition to ETPC(unbound) data were available for 52 drugs. For Category 1 drugs, data for hERG/I(Kr) IC(50), APD(90), QTc in animals and QTc in humans were generally close to or superimposed on the ETPC(unbound) values. This relationship was uncoupled in the other categories, with more complex relationships between the data. In Category 1 (except amiodarone), the ratios between hERG/I(Kr) IC(50) and ETPC(unbound) (max) ranged from 0.1- to 31-fold. Similar ranges were obtained for drugs in Category 2 (0.31- to 13-fold) and Category 3 (0.03- to 35-fold). A large spread was found for Category 4 drugs (0.13- to 35700-fold); this category embraced an assortment of mechanisms ranging from drugs which may well be affecting I(Kr) currents in clinical use (e.g. sparfloxacin) to others such as nifedipine (35700-fold) where channel block is not involved. Finally, for the majority of Category 5 drugs there was a >30-fold separation between hERG/I(Kr) activity and ETPC(unbound) values, with the notable exception of verapamil (1.7-fold), which is free from QT prolongation in man; this is probably explained by its multiple interactions with cardiac ion channels. ::: ::: ::: CONCLUSIONS ::: The dataset confirms the widely-held belief that most drugs associated with TdP in humans are also associated with hERG K(+) channel block at concentrations close to or superimposed upon the free plasma concentrations found in clinical use. A 30-fold margin between C(max) and hERG IC(50) may suffice for drugs currently undergoing clinical evaluation, but for future drug discovery programmes, pharmaceutical companies should consider increasing this margin, particularly for drugs aimed at non-debilitating diseases. However, interactions with multiple cardiac ion channels can either mitigate or exacerbate the prolongation of APD and QT that would ensue from block of I(Kr) currents alone, and delay of repolarisation per se is not necessarily torsadogenic. Clearly, an integrated assessment of in vitro and in vivo data is required in order to predict the torsadogenic risk of a new candidate drug in humans.
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paper_title: Mechanistic Model‐Informed Proarrhythmic Risk Assessment of Drugs: Review of the “CiPA” Initiative and Design of a Prospective Clinical Validation Study

paper_content:

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.
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paper_title: Focal and Reentrant Mechanisms of Torsades de Pointes: EAD, Reentry, or Chimera?

paper_content:

Torsades de pointes (TdP. is characterized not only by its electrocardiographic morphology but also by a tendency to spontaneously terminate. Although clinical and experimental studies suggested that TdP is triggered exclusively by early afterdepolarization, the reentrant mechanism seems to play a certain role in its maintenance. In this article, I review the studies that investigated the origin and activation sequences of the twisting QRS complexes of TdP, and discuss whether it is fortunate or unfortunate for us if TdP has something to do with reentry.
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paper_title: Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms

paper_content:

The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unresolved issue in drug development. Current assays to evaluate arrhythmia risk are limited by poor specificity and a lack of mechanistic insight. We addressed this important unresolved issue through a novel computational approach that combined simulations of drug effects on dynamics with statistical analysis and machine-learning. Drugs that blocked multiple ion channels were simulated in ventricular myocyte models, and metrics computed from the action potential and intracellular (Ca(2+) ) waveform were used to construct classifiers that distinguished between arrhythmogenic and nonarrhythmogenic drugs. We found that: (1) these classifiers provide superior risk prediction; (2) drug-induced changes to both the action potential and intracellular (Ca(2+) ) influence risk; and (3) cardiac ion channels not typically assessed may significantly affect risk. Our algorithm demonstrates the value of systematic simulations in predicting pharmacological toxicity.
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paper_title: Cellular basis of drug-induced torsades de pointes

paper_content:

Striking QT prolongation and the morphologically distinctive ventricular tachycardia torsades de pointes can occur in up to 5% of patients treated with certain antiarrhythmic drugs. This adverse drug reaction also occurs, albeit far less frequently, during therapy with a range of drugs not used for cardiovascular indications; examples include certain antibiotics, antipsychotics and antihistamines. The common mechanism for drug-induced torsades de pointes is inhibition of a specific repolarizing potassium current, I(Kr). The key question facing clinicians, regulators and those who develop drugs is why torsades de pointes only occurs in some patients exposed to I(Kr) block. This paper reviews the clinical, cellular, molecular and genetic features of the arrhythmia that may provide an answer to this question and proposes future studies in this area.
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paper_title: Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium.

paper_content:

This white paper provides a summary of a scientific proposal presented at a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/Food and Drug Administration–sponsored Think Tank, held at Food and Drug Administration's White Oak facilities, Silver Spring, MD, on July 23, 2013, with the intention of moving toward consensus on defining a new paradigm in the field of cardiac safety in which proarrhythmic risk would be primarily assessed using nonclinical in vitro human models based on solid mechanistic considerations of torsades de pointes proarrhythmia. This new paradigm would shift the emphasis from the present approach that strongly relies on QTc prolongation (a surrogate marker of proarrhythmia) and could obviate the clinical Thorough QT study during later drug development. These discussions represent current thinking and suggestions for furthering our knowledge and understanding of the public health case for adopting a new, integrated nonclinical in vitro/in silico paradigm, the Comprehensive In Vitro Proarrhythmia Assay, for the assessment of a candidate drug's proarrhythmic liability, and for developing a public-private collaborative program to characterize the data content, quality, and approaches required to assess proarrhythmic risk in the absence of a Thorough QT study. This paper seeks to encourage multistakeholder input regarding this initiative and does not represent regulatory guidance.
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paper_title: Pause induced early afterdepolarizations in the long QT syndrome: a simulation study.

paper_content:

OBJECTIVE ::: The long QT syndrome (LQTS) is characterized by prolonged repolarization and propensity to syncope and sudden death due to polymorphic ventricular tachycardias such as torsade de pointes (TdP). The exact mechanism of TdP is unclear, but pause-induced early afterdepolarizations (EADs) have been implicated in its initiation. In this study we investigate the mechanism of pause-induced EADs following pacing at clinically relevant rates and characterize the sensitivity of different cell types (epicardial, midmyocardial, and endocardial) to EAD development. ::: ::: ::: METHODS ::: Simulations were conducted using the Luo-Rudy (LRd) model of the mamalian ventricular action potential (AP). Three cell types--epicardial, midmyocardial (M), and enocardial--are represented by altering the channel density of the slow delayed rectifier current, IKs. LQTS is modelled by enhanced late sodium current (LQT3), or reduced density of functional channels that conduct IKr (LQT2) and IKs (LQT1). The cell is paced 40 times at a constant Basic Cycle Length (BCL) of 500 ms. Following a 1500 ms pause, an additional single stimulus is applied. ::: ::: ::: RESULTS ::: Our results demonstrate that pause-induced EADs develop preferentially in M cells under conditions of prolonged repolarization. These EADs develop at plateau potentials ('plateau EADs'). Mechanistic investigation shows that prolongation of the plateau phase of the post-pause AP due to a smaller delayed rectifier potassium current, IKs' and enhancement of the sodium-calcium exchange current, INaCa, allows for the reactivation of the L-type calcium current, ICa(L), which depolarizes the membrane to generate the EAD. ::: ::: ::: CONCLUSIONS ::: APD is a very important determinant of arrhythmogenesis and its prolongation, either due to acquired or congenital LQTS, can result in the appearance of EADs. The formation of pause-induced EADs preferentially in M cells suggests a possible role for these cells in the generation of arrhythmias that are associated with abnormalities of repolarization (e.g., TdP). The ionic mechanism of pause-induced EADs involves reactivation of the L-type calcium current during the prolonged plateau of the post-pause AP.
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paper_title: MICE Models: Superior to the HERG Model in Predicting Torsade de Pointes

paper_content:

Drug-induced block of the cardiac hERG (human Ether-a-go-go-Related Gene) potassium channel delays cardiac repolarization and increases the risk of Torsade de Pointes (TdP), a potentially lethal arrhythmia. A positive hERG assay has been embraced by regulators as a non-clinical predictor of TdP despite a discordance of about 30%. To test whether assaying concomitant block of multiple ion channels (Multiple Ion Channel Effects or MICE) improves predictivity we measured the concentration-responses of hERG, Nav1.5 and Cav1.2 currents for 32 torsadogenic and 23 non-torsadogenic drugs from multiple classes. We used automated gigaseal patch clamp instruments to provide higher throughput along with accuracy and reproducibility. Logistic regression models using the MICE assay showed a significant reduction in false positives (Type 1 errors) and false negatives (Type 2 errors) when compared to the hERG assay. The best MICE model only required a comparison of the blocking potencies between hERG and Cav1.2.
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paper_title: Early Afterdepolarizations and Cardiac Arrhythmias

paper_content:

Early afterdepolarizations (EADs) are an important cause of lethal ventricular arrhythmias in long QT syndromes and heart failure, but the mechanisms by which EADs at the cellular scale cause arrhythmias such as polymorphic ventricular tachycardia (PVT) and torsades de pointes (TdP) at the tissue scale are not well understood. Here we summarize recent progress in this area, discussing (1) the ionic basis of EADs, (2) evidence that deterministic chaos underlies the irregular behavior of EADs, (3) mechanisms by which chaotic EADs synchronize in large numbers of coupled cells in tissue to overcome source–sink mismatches, (4) how this synchronization process allows EADs to initiate triggers and generate mixed focal reentrant ventricular arrhythmias underlying PVT and TdP, and (5) therapeutic implications.
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paper_title: Simulation of multiple ion channel block provides improved early prediction of compounds’ clinical torsadogenic risk

paper_content:

Aims: The level of inhibition of the human Ether-a-go-go Related Gene (hERG) channel is one of the earliest preclinical markers used to predict the risk of a compound causing Torsade-de-Pointes (TdP) arrhythmias. Whilst avoiding the use of drugs with maximum therapeutic concentrations within 30-fold of their hERG IC50 values has been suggested, there are drugs which are exceptions to this rule: hERG inhibitors that do not cause TdP, and drugs that can cause TdP but are not strong hERG inhibitors. In this study, we investigate whether a simulated evaluation of multichannel effects could be used to improve this early prediction of TdP risk. ::: ::: Methods and Results: We collected multiple ion channel data (hERG, Na, L-type Ca) on 31 drugs associated with varied risks of TdP. To integrate the information on multi-channel block we have performed simulations with a variety of mathematical models of cardiac cells (for rabbit, dog and human ventricular myocyte models). Drug action is modelled using IC50 values and therapeutic drug concentrations to calculate the proportion of blocked channels and the channel conductances are modified accordingly. Various pacing protocols are simulated, and classification analysis is performed to evaluate the predictive power of the models for TdP risk. ::: ::: We find that simulation of action potential duration prolongation, at therapeutic concentrations, provides improved prediction of the TdP risk associated with a compound, above that provided by existing markers. ::: ::: Conclusion: The suggested calculations improve the reliability of early cardiac safety assessments, beyond those based solely on a hERG block effect.
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paper_title: Complex versus simple models: ion-channel cardiac toxicity prediction

paper_content:

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established cardiac models, gold-standard and cardiac safety simulator, and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category based on information within CredibleMeds. The predictive performance of each model within each data-set was assessed via a leave-one-out cross validation. In two of the data-sets Bnet performed equally as well as the leading cardiac model, cardiac safety simulator, both of these outperformed the gold-standard model. In the 3rd data-set, which contained the most detailed ion-channel pharmacology, Bnet outperformed both cardiac models. These results highlight the importance of benchmarking models but also encourage the development of simple models.
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paper_title: Focal and Reentrant Mechanisms of Torsades de Pointes: EAD, Reentry, or Chimera?

paper_content:

Torsades de pointes (TdP. is characterized not only by its electrocardiographic morphology but also by a tendency to spontaneously terminate. Although clinical and experimental studies suggested that TdP is triggered exclusively by early afterdepolarization, the reentrant mechanism seems to play a certain role in its maintenance. In this article, I review the studies that investigated the origin and activation sequences of the twisting QRS complexes of TdP, and discuss whether it is fortunate or unfortunate for us if TdP has something to do with reentry.
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paper_title: Early assessment of proarrhythmic risk of drugs using the in vitro data and single-cell-based in silico models: proof of concept.

paper_content:

BACKGROUND AND PURPOSE ::: To determine the predictive performance of in silico models using drug-specific preclinical cardiac electrophysiology data to investigate drug-induced arrhythmia risk (e.g. Torsade de pointes (TdP)) in virtual human subjects. ::: ::: ::: EXPERIMENTAL APPROACH ::: To assess drug proarrhythmic risk, we used a set of in vitro electrophysiological measurements describing ion channel inhibition triggered by the investigated drugs. The Cardiac Safety Simulator version 2.0 (CSS; Simcyp, Sheffield, UK) platform was used to simulate human left ventricular cardiac myocyte action potential models. ::: ::: ::: RESULTS ::: This study shows the impact of drug concentration changes on particular ionic currents by using available experimental data. The simulation results display safety threshold according to drug concentration threshold and log (threshold concentration/ effective therapeutic plasma concentration (ETPC)). ::: ::: ::: CONCLUSION AND IMPLICATIONS ::: We reproduced the underlying biophysical characteristics of cardiac cells resulted in effects of drugs associated with cardiac arrhythmias (action potential duration (APD) and QT prolongation and TdP) which were observed in published 3D simulations, yet with much less computational burden.
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paper_title: Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms

paper_content:

The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unresolved issue in drug development. Current assays to evaluate arrhythmia risk are limited by poor specificity and a lack of mechanistic insight. We addressed this important unresolved issue through a novel computational approach that combined simulations of drug effects on dynamics with statistical analysis and machine-learning. Drugs that blocked multiple ion channels were simulated in ventricular myocyte models, and metrics computed from the action potential and intracellular (Ca(2+) ) waveform were used to construct classifiers that distinguished between arrhythmogenic and nonarrhythmogenic drugs. We found that: (1) these classifiers provide superior risk prediction; (2) drug-induced changes to both the action potential and intracellular (Ca(2+) ) influence risk; and (3) cardiac ion channels not typically assessed may significantly affect risk. Our algorithm demonstrates the value of systematic simulations in predicting pharmacological toxicity.
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paper_title: Global Optimization of Ventricular Myocyte Model to Multi-Variable Objective Improves Predictions of Drug-Induced Torsades de Pointes

paper_content:

In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity.
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paper_title: Cellular basis of drug-induced torsades de pointes

paper_content:

Striking QT prolongation and the morphologically distinctive ventricular tachycardia torsades de pointes can occur in up to 5% of patients treated with certain antiarrhythmic drugs. This adverse drug reaction also occurs, albeit far less frequently, during therapy with a range of drugs not used for cardiovascular indications; examples include certain antibiotics, antipsychotics and antihistamines. The common mechanism for drug-induced torsades de pointes is inhibition of a specific repolarizing potassium current, I(Kr). The key question facing clinicians, regulators and those who develop drugs is why torsades de pointes only occurs in some patients exposed to I(Kr) block. This paper reviews the clinical, cellular, molecular and genetic features of the arrhythmia that may provide an answer to this question and proposes future studies in this area.
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paper_title: Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicator

paper_content:

Drug-induced Torsades de Pointes (TdP) arrhythmia is of major interest in predictive toxicology. Drugs which cause TdP block the hERG cardiac potassium channel. However, not all drugs that block hERG cause TdP. As such, further understanding of the mechanistic route to TdP is needed. Early afterde-polarisations (EADs) are a cell-level phenomenon in which the membrane of a cardiac cell depolarises a second time before repolarisation, and EADs are seen in hearts during TdP. Therefore, we propose a method of predicting TdP using induced EADs combined with multiple ion channel block in simulations using biophysically-based mathematical models of human ventricular cell electrophysiology. EADs were induced in cardiac action potential models using interventions based on diseases that are known to cause EADs, including: increasing the conduction of the L-type calcium channel, decreasing the conduction of the hERG channel, and shifting the inactivation curve of the fast sodium channel. The threshold of intervention that was required to cause an EAD was used to classify drugs into clinical risk categories. The metric that used L-type calcium induced EADs was the most accurate of the EAD metrics at classifying drugs into the correct risk categories, and increased in accuracy when combined with action potential duration measurements. The EAD metrics were all more accurate than hERG block alone, but not as predictive as simpler measures such as simulated action potential duration. This may be because different routes to EADs represent risk well for different patient subgroups, something that is difficult to assess at present.
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paper_title: hERG Inhibitors with Similar Potency But Different Binding Kinetics Do Not Pose the Same Proarrhythmic Risk: Implications for Drug Safety Assessment

paper_content:

INTRODUCTION: Since the discovery of the link that exists between drug-induced hERG inhibition and Torsade de Pointes (TdP), extreme attention has been given to avoid new drugs inhibiting this channel. hERG inhibition is routinely screened for in new drugs and, typically, IC50 values are compared to projected plasma concentrations to define a safety margin. METHODS AND RESULTS: We aimed to show that drugs with similar hERG potency are not uniformly pro-arrhythmic-this depends on the drug binding kinetics and mode of action (trapped or not) rather than the IC50 value only. We used a mathematical model of hERG and its related encoded current IKr to simulate drug binding in different configurations. Expression systems mimicking the screening process were first investigated. hERG model was then incorporated into a canine action potential (AP) and tissue model to study the impact of drug binding configurations on AP and pseudo-ECG (QT interval prolongation). Our data show that: (1) trapped and not trapped configurations and different binding kinetics could be identified during hERG screening; (2) slow binding, not trapped drugs, induced less AP prolongation and minimal QT interval prolongation (4.7%) at a concentration equal to the IC50 whereas maximal pro-arrhythmic risk was observed for trapped drugs at the same concentration (QT interval prolongation, 23.1%). CONCLUSION: Our study demonstrates the need for screening for hERG binding configurations rather than potency alone. It also demonstrates the potential link between hERG, drug mode of action and TdP, and the need to question the current regulatory guidance.
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paper_title: MICE Models: Superior to the HERG Model in Predicting Torsade de Pointes

paper_content:

Drug-induced block of the cardiac hERG (human Ether-a-go-go-Related Gene) potassium channel delays cardiac repolarization and increases the risk of Torsade de Pointes (TdP), a potentially lethal arrhythmia. A positive hERG assay has been embraced by regulators as a non-clinical predictor of TdP despite a discordance of about 30%. To test whether assaying concomitant block of multiple ion channels (Multiple Ion Channel Effects or MICE) improves predictivity we measured the concentration-responses of hERG, Nav1.5 and Cav1.2 currents for 32 torsadogenic and 23 non-torsadogenic drugs from multiple classes. We used automated gigaseal patch clamp instruments to provide higher throughput along with accuracy and reproducibility. Logistic regression models using the MICE assay showed a significant reduction in false positives (Type 1 errors) and false negatives (Type 2 errors) when compared to the hERG assay. The best MICE model only required a comparison of the blocking potencies between hERG and Cav1.2.
---
paper_title: Simulation of multiple ion channel block provides improved early prediction of compounds’ clinical torsadogenic risk

paper_content:

Aims: The level of inhibition of the human Ether-a-go-go Related Gene (hERG) channel is one of the earliest preclinical markers used to predict the risk of a compound causing Torsade-de-Pointes (TdP) arrhythmias. Whilst avoiding the use of drugs with maximum therapeutic concentrations within 30-fold of their hERG IC50 values has been suggested, there are drugs which are exceptions to this rule: hERG inhibitors that do not cause TdP, and drugs that can cause TdP but are not strong hERG inhibitors. In this study, we investigate whether a simulated evaluation of multichannel effects could be used to improve this early prediction of TdP risk. ::: ::: Methods and Results: We collected multiple ion channel data (hERG, Na, L-type Ca) on 31 drugs associated with varied risks of TdP. To integrate the information on multi-channel block we have performed simulations with a variety of mathematical models of cardiac cells (for rabbit, dog and human ventricular myocyte models). Drug action is modelled using IC50 values and therapeutic drug concentrations to calculate the proportion of blocked channels and the channel conductances are modified accordingly. Various pacing protocols are simulated, and classification analysis is performed to evaluate the predictive power of the models for TdP risk. ::: ::: We find that simulation of action potential duration prolongation, at therapeutic concentrations, provides improved prediction of the TdP risk associated with a compound, above that provided by existing markers. ::: ::: Conclusion: The suggested calculations improve the reliability of early cardiac safety assessments, beyond those based solely on a hERG block effect.
---
paper_title: Complex versus simple models: ion-channel cardiac toxicity prediction

paper_content:

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established cardiac models, gold-standard and cardiac safety simulator, and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category based on information within CredibleMeds. The predictive performance of each model within each data-set was assessed via a leave-one-out cross validation. In two of the data-sets Bnet performed equally as well as the leading cardiac model, cardiac safety simulator, both of these outperformed the gold-standard model. In the 3rd data-set, which contained the most detailed ion-channel pharmacology, Bnet outperformed both cardiac models. These results highlight the importance of benchmarking models but also encourage the development of simple models.
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paper_title: Uncertainty and variability in computational and mathematical models of cardiac physiology

paper_content:

Key points ::: Mathematical and computational models of cardiac physiology have been an integral component of cardiac electrophysiology since its inception, and are collectively known as the Cardiac Physiome. ::: We identify and classify the numerous sources of variability and uncertainty in model formulation, parameters and other inputs that arise from both natural variation in experimental data and lack of knowledge. ::: The impact of uncertainty on the outputs of Cardiac Physiome models is not well understood, and this limits their utility as clinical tools. ::: We argue that incorporating variability and uncertainty should be a high priority for the future of the Cardiac Physiome. ::: We suggest investigating the adoption of approaches developed in other areas of science and engineering while recognising unique challenges for the Cardiac Physiome; it is likely that novel methods will be necessary that require engagement with the mathematics and statistics community. ::: ::: Abstract ::: The Cardiac Physiome effort is one of the most mature and successful applications of mathematical and computational modelling for describing and advancing the understanding of physiology. After five decades of development, physiological cardiac models are poised to realise the promise of translational research via clinical applications such as drug development and patient-specific approaches as well as ablation, cardiac resynchronisation and contractility modulation therapies. For models to be included as a vital component of the decision process in safety-critical applications, rigorous assessment of model credibility will be required. This White Paper describes one aspect of this process by identifying and classifying sources of variability and uncertainty in models as well as their implications for the application and development of cardiac models. We stress the need to understand and quantify the sources of variability and uncertainty in model inputs, and the impact of model structure and complexity and their consequences for predictive model outputs. We propose that the future of the Cardiac Physiome should include a probabilistic approach to quantify the relationship of variability and uncertainty of model inputs and outputs.
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paper_title: Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment

paper_content:

Drug-induced Torsade-de-Pointes (TdP) has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA) was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr) with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model). We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs), and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at concentrations both near and higher than clinical exposure, and a physiological framework to check the relationship between a metric and EAD. These findings provide a solid foundation for using in silico models for the regulatory assessment of TdP risk under the CiPA paradigm.
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paper_title: Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative

paper_content:

International Council on Harmonization S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are proarrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures This suggests that the current CiPA model/metric is fit for regulatory use, and standard experimental protocols and quality control criteria could increase the model prediction accuracy even further.
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paper_title: Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology

paper_content:

Perhaps the most mature area of multi-scale systems biology is the modelling of the heart. Current models are grounded in over fifty years of research in the development of biophysically detailed models of the electrophysiology (EP) of cardiac cells, but one aspect which is inadequately addressed is the incorporation of uncertainty and physiological variability. Uncertainty quantification (UQ) is the identification and characterisation of the uncertainty in model parameters derived from experimental data, and the computation of the resultant uncertainty in model outputs. It is a necessary tool for establishing the credibility of computational models, and will likely be expected of EP models for future safety-critical clinical applications. The focus of this paper is formal UQ of one major sub-component of cardiac EP models, the steady-state inactivation of the fast sodium current, INa. To better capture average behaviour and quantify variability across cells, we have applied for the first time an ‘individual-based’ statistical methodology to assess voltage clamp data. Advantages of this approach over a more traditional ‘population-averaged’ approach are highlighted. The method was used to characterise variability amongst cells isolated from canine epi and endocardium, and this variability was then ‘propagated forward’ through a canine model to determine the resultant uncertainty in model predictions at different scales, such as of upstroke velocity and spiral wave dynamics. Statistically significant differences between epi and endocardial cells (greater half-inactivation and less steep slope of steady state inactivation curve for endo) was observed, and the forward propagation revealed a lack of robustness of the model to underlying variability, but also surprising robustness to variability at the tissue scale. Overall, the methodology can be used to: (i) better analyse voltage clamp data; (ii) characterise underlying population variability; (iii) investigate consequences of variability; and (iv) improve the ability to validate a model. To our knowledge this article is the first to quantify population variability in membrane dynamics in this manner, and the first to perform formal UQ for a component of a cardiac model. The approach is likely to find much wider applicability across systems biology as current application domains reach greater levels of maturity.
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paper_title: Early assessment of proarrhythmic risk of drugs using the in vitro data and single-cell-based in silico models: proof of concept.

paper_content:

BACKGROUND AND PURPOSE ::: To determine the predictive performance of in silico models using drug-specific preclinical cardiac electrophysiology data to investigate drug-induced arrhythmia risk (e.g. Torsade de pointes (TdP)) in virtual human subjects. ::: ::: ::: EXPERIMENTAL APPROACH ::: To assess drug proarrhythmic risk, we used a set of in vitro electrophysiological measurements describing ion channel inhibition triggered by the investigated drugs. The Cardiac Safety Simulator version 2.0 (CSS; Simcyp, Sheffield, UK) platform was used to simulate human left ventricular cardiac myocyte action potential models. ::: ::: ::: RESULTS ::: This study shows the impact of drug concentration changes on particular ionic currents by using available experimental data. The simulation results display safety threshold according to drug concentration threshold and log (threshold concentration/ effective therapeutic plasma concentration (ETPC)). ::: ::: ::: CONCLUSION AND IMPLICATIONS ::: We reproduced the underlying biophysical characteristics of cardiac cells resulted in effects of drugs associated with cardiac arrhythmias (action potential duration (APD) and QT prolongation and TdP) which were observed in published 3D simulations, yet with much less computational burden.
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paper_title: The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative — Update on progress

paper_content:

The implementation of the ICH S7B and E14 guidelines has been successful in preventing the introduction of potentially torsadogenic drugs to the market, but it has also unduly constrained drug development by focusing on hERG block and QT prolongation as essential determinants of proarrhythmia risk. The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative was established to develop a new paradigm for assessing proarrhythmic risk, building on the emergence of new technologies and an expanded understanding of torsadogenic mechanisms beyond hERG block. An international multi-disciplinary team of regulatory, industry and academic scientists are working together to develop and validate a set of predominantly nonclinical assays and methods that eliminate the need for the thorough-QT study and enable a more precise prediction of clinical proarrhythmia risk. The CiPA effort is led by a Steering Team that provides guidance, expertise and oversight to the various working groups and includes partners from US FDA, HESI, CSRC, SPS, EMA, Health Canada, Japan NIHS, and PMDA. The working groups address the three pillars of CiPA that evaluate drug effects on: 1) human ventricular ionic channel currents in heterologous expression systems, 2) in silico integration of cellular electrophysiologic effects based on ionic current effects, the ion channel effects, and 3) fully integrated biological systems (stem-cell-derived cardiac myocytes and the human ECG). This article provides an update on the progress of the initiative towards its target date of December 2017 for completing validation.
---
paper_title: Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms

paper_content:

The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unresolved issue in drug development. Current assays to evaluate arrhythmia risk are limited by poor specificity and a lack of mechanistic insight. We addressed this important unresolved issue through a novel computational approach that combined simulations of drug effects on dynamics with statistical analysis and machine-learning. Drugs that blocked multiple ion channels were simulated in ventricular myocyte models, and metrics computed from the action potential and intracellular (Ca(2+) ) waveform were used to construct classifiers that distinguished between arrhythmogenic and nonarrhythmogenic drugs. We found that: (1) these classifiers provide superior risk prediction; (2) drug-induced changes to both the action potential and intracellular (Ca(2+) ) influence risk; and (3) cardiac ion channels not typically assessed may significantly affect risk. Our algorithm demonstrates the value of systematic simulations in predicting pharmacological toxicity.
---
paper_title: 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

paper_content:

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 th...
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paper_title: Global Optimization of Ventricular Myocyte Model to Multi-Variable Objective Improves Predictions of Drug-Induced Torsades de Pointes

paper_content:

In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity.
---
paper_title: Cellular basis of drug-induced torsades de pointes

paper_content:

Striking QT prolongation and the morphologically distinctive ventricular tachycardia torsades de pointes can occur in up to 5% of patients treated with certain antiarrhythmic drugs. This adverse drug reaction also occurs, albeit far less frequently, during therapy with a range of drugs not used for cardiovascular indications; examples include certain antibiotics, antipsychotics and antihistamines. The common mechanism for drug-induced torsades de pointes is inhibition of a specific repolarizing potassium current, I(Kr). The key question facing clinicians, regulators and those who develop drugs is why torsades de pointes only occurs in some patients exposed to I(Kr) block. This paper reviews the clinical, cellular, molecular and genetic features of the arrhythmia that may provide an answer to this question and proposes future studies in this area.
---
paper_title: Variability in high-throughput ion-channel screening data and consequences for cardiac safety assessment

paper_content:

Abstract Introduction Unwanted drug interactions with ionic currents in the heart can lead to an increased pro-arrhythmic risk to patients in the clinic. It is therefore a priority for safety pharmacology teams to detect block of cardiac ion channels, and new technologies have enabled the development of automated and high-throughput screening assays using cell lines. As a result of screening multiple ion-channels there is a need to integrate information, particularly for compounds affecting more than one current, and mathematical electrophysiology in-silico action potential models are beginning to be used for this. Methods We quantified the variability associated with concentration-effect curves fitted to recordings from high-throughput Molecular Devices IonWorks® Quattro™ screens when detecting block of I Kr (hERG), I Na (NaV1.5), I CaL (CaV1.2), I Ks (KCNQ1/minK) and I to (Kv4.3/KChIP2.2), and the Molecular Devices FLIPR® Tetra fluorescence screen for I CaL (CaV1.2), for control compounds used at AstraZeneca and GlaxoSmithKline. We examined how screening variability propagates through in-silico action potential models for whole cell electrical behaviour, and how confidence intervals on model predictions can be estimated with repeated simulations. Results There are significant levels of variability associated with high-throughput ion channel electrophysiology screens. This variability is of a similar magnitude for different cardiac ion currents and different compounds. Uncertainty in the Hill coefficients of reported concentration-effect curves is particularly high. Depending on a compound's ion channel blocking profile, the uncertainty introduced into whole-cell predictions can become significant. Discussion Our technique allows confidence intervals to be placed on computational model predictions that are based on high-throughput ion channel screens. This allows us to suggest when repeated screens should be performed to reduce uncertainty in a compound's action to acceptable levels, to allow a meaningful interpretation of the data.
---
paper_title: Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment

paper_content:

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 (Cmax). However, when drug effects were extrapolated above 10× Cmax, 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.
---
paper_title: Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium.

paper_content:

This white paper provides a summary of a scientific proposal presented at a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/Food and Drug Administration–sponsored Think Tank, held at Food and Drug Administration's White Oak facilities, Silver Spring, MD, on July 23, 2013, with the intention of moving toward consensus on defining a new paradigm in the field of cardiac safety in which proarrhythmic risk would be primarily assessed using nonclinical in vitro human models based on solid mechanistic considerations of torsades de pointes proarrhythmia. This new paradigm would shift the emphasis from the present approach that strongly relies on QTc prolongation (a surrogate marker of proarrhythmia) and could obviate the clinical Thorough QT study during later drug development. These discussions represent current thinking and suggestions for furthering our knowledge and understanding of the public health case for adopting a new, integrated nonclinical in vitro/in silico paradigm, the Comprehensive In Vitro Proarrhythmia Assay, for the assessment of a candidate drug's proarrhythmic liability, and for developing a public-private collaborative program to characterize the data content, quality, and approaches required to assess proarrhythmic risk in the absence of a Thorough QT study. This paper seeks to encourage multistakeholder input regarding this initiative and does not represent regulatory guidance.
---
paper_title: Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicator

paper_content:

Drug-induced Torsades de Pointes (TdP) arrhythmia is of major interest in predictive toxicology. Drugs which cause TdP block the hERG cardiac potassium channel. However, not all drugs that block hERG cause TdP. As such, further understanding of the mechanistic route to TdP is needed. Early afterde-polarisations (EADs) are a cell-level phenomenon in which the membrane of a cardiac cell depolarises a second time before repolarisation, and EADs are seen in hearts during TdP. Therefore, we propose a method of predicting TdP using induced EADs combined with multiple ion channel block in simulations using biophysically-based mathematical models of human ventricular cell electrophysiology. EADs were induced in cardiac action potential models using interventions based on diseases that are known to cause EADs, including: increasing the conduction of the L-type calcium channel, decreasing the conduction of the hERG channel, and shifting the inactivation curve of the fast sodium channel. The threshold of intervention that was required to cause an EAD was used to classify drugs into clinical risk categories. The metric that used L-type calcium induced EADs was the most accurate of the EAD metrics at classifying drugs into the correct risk categories, and increased in accuracy when combined with action potential duration measurements. The EAD metrics were all more accurate than hERG block alone, but not as predictive as simpler measures such as simulated action potential duration. This may be because different routes to EADs represent risk well for different patient subgroups, something that is difficult to assess at present.
---
paper_title: Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development.

paper_content:

OBJECTIVE ::: To attempt to determine the relative value of preclinical cardiac electrophysiology data (in vitro and in vivo) for predicting risk of torsade de pointes (TdP) in clinical use. ::: ::: ::: METHODS ::: Published data on hERG (or I(Kr)) activity, cardiac action potential duration (at 90% repolarisation; APD(90)), and QT prolongation in dogs were compared against QT effects and reports of TdP in humans for 100 drugs. These data were set against the free plasma concentrations attained during clinical use (effective therapeutic plasma concentrations; ETPC(unbound)). The drugs were divided into five categories: (1) Class Ia and III antiarrhythmics; (2) Withdrawn from market due to TdP; (3) Measurable incidence/numerous reports of TdP in humans; (4) Isolated reports of TdP in humans; (5) No reports of TdP in humans. ::: ::: ::: RESULTS ::: Data from hERG (or I(Kr)) assays in addition to ETPC(unbound) data were available for 52 drugs. For Category 1 drugs, data for hERG/I(Kr) IC(50), APD(90), QTc in animals and QTc in humans were generally close to or superimposed on the ETPC(unbound) values. This relationship was uncoupled in the other categories, with more complex relationships between the data. In Category 1 (except amiodarone), the ratios between hERG/I(Kr) IC(50) and ETPC(unbound) (max) ranged from 0.1- to 31-fold. Similar ranges were obtained for drugs in Category 2 (0.31- to 13-fold) and Category 3 (0.03- to 35-fold). A large spread was found for Category 4 drugs (0.13- to 35700-fold); this category embraced an assortment of mechanisms ranging from drugs which may well be affecting I(Kr) currents in clinical use (e.g. sparfloxacin) to others such as nifedipine (35700-fold) where channel block is not involved. Finally, for the majority of Category 5 drugs there was a >30-fold separation between hERG/I(Kr) activity and ETPC(unbound) values, with the notable exception of verapamil (1.7-fold), which is free from QT prolongation in man; this is probably explained by its multiple interactions with cardiac ion channels. ::: ::: ::: CONCLUSIONS ::: The dataset confirms the widely-held belief that most drugs associated with TdP in humans are also associated with hERG K(+) channel block at concentrations close to or superimposed upon the free plasma concentrations found in clinical use. A 30-fold margin between C(max) and hERG IC(50) may suffice for drugs currently undergoing clinical evaluation, but for future drug discovery programmes, pharmaceutical companies should consider increasing this margin, particularly for drugs aimed at non-debilitating diseases. However, interactions with multiple cardiac ion channels can either mitigate or exacerbate the prolongation of APD and QT that would ensue from block of I(Kr) currents alone, and delay of repolarisation per se is not necessarily torsadogenic. Clearly, an integrated assessment of in vitro and in vivo data is required in order to predict the torsadogenic risk of a new candidate drug in humans.
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paper_title: Simulation of multiple ion channel block provides improved early prediction of compounds’ clinical torsadogenic risk

paper_content:

Aims: The level of inhibition of the human Ether-a-go-go Related Gene (hERG) channel is one of the earliest preclinical markers used to predict the risk of a compound causing Torsade-de-Pointes (TdP) arrhythmias. Whilst avoiding the use of drugs with maximum therapeutic concentrations within 30-fold of their hERG IC50 values has been suggested, there are drugs which are exceptions to this rule: hERG inhibitors that do not cause TdP, and drugs that can cause TdP but are not strong hERG inhibitors. In this study, we investigate whether a simulated evaluation of multichannel effects could be used to improve this early prediction of TdP risk. ::: ::: Methods and Results: We collected multiple ion channel data (hERG, Na, L-type Ca) on 31 drugs associated with varied risks of TdP. To integrate the information on multi-channel block we have performed simulations with a variety of mathematical models of cardiac cells (for rabbit, dog and human ventricular myocyte models). Drug action is modelled using IC50 values and therapeutic drug concentrations to calculate the proportion of blocked channels and the channel conductances are modified accordingly. Various pacing protocols are simulated, and classification analysis is performed to evaluate the predictive power of the models for TdP risk. ::: ::: We find that simulation of action potential duration prolongation, at therapeutic concentrations, provides improved prediction of the TdP risk associated with a compound, above that provided by existing markers. ::: ::: Conclusion: The suggested calculations improve the reliability of early cardiac safety assessments, beyond those based solely on a hERG block effect.
---
paper_title: Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative

paper_content:

International Council on Harmonization S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are proarrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures This suggests that the current CiPA model/metric is fit for regulatory use, and standard experimental protocols and quality control criteria could increase the model prediction accuracy even further.
---
paper_title: The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative — Update on progress

paper_content:

The implementation of the ICH S7B and E14 guidelines has been successful in preventing the introduction of potentially torsadogenic drugs to the market, but it has also unduly constrained drug development by focusing on hERG block and QT prolongation as essential determinants of proarrhythmia risk. The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative was established to develop a new paradigm for assessing proarrhythmic risk, building on the emergence of new technologies and an expanded understanding of torsadogenic mechanisms beyond hERG block. An international multi-disciplinary team of regulatory, industry and academic scientists are working together to develop and validate a set of predominantly nonclinical assays and methods that eliminate the need for the thorough-QT study and enable a more precise prediction of clinical proarrhythmia risk. The CiPA effort is led by a Steering Team that provides guidance, expertise and oversight to the various working groups and includes partners from US FDA, HESI, CSRC, SPS, EMA, Health Canada, Japan NIHS, and PMDA. The working groups address the three pillars of CiPA that evaluate drug effects on: 1) human ventricular ionic channel currents in heterologous expression systems, 2) in silico integration of cellular electrophysiologic effects based on ionic current effects, the ion channel effects, and 3) fully integrated biological systems (stem-cell-derived cardiac myocytes and the human ECG). This article provides an update on the progress of the initiative towards its target date of December 2017 for completing validation.
---
paper_title: Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms

paper_content:

The ventricular arrhythmia Torsades de Pointes (TdP) is a common form of drug-induced cardiotoxicity, but prediction of this arrhythmia remains an unresolved issue in drug development. Current assays to evaluate arrhythmia risk are limited by poor specificity and a lack of mechanistic insight. We addressed this important unresolved issue through a novel computational approach that combined simulations of drug effects on dynamics with statistical analysis and machine-learning. Drugs that blocked multiple ion channels were simulated in ventricular myocyte models, and metrics computed from the action potential and intracellular (Ca(2+) ) waveform were used to construct classifiers that distinguished between arrhythmogenic and nonarrhythmogenic drugs. We found that: (1) these classifiers provide superior risk prediction; (2) drug-induced changes to both the action potential and intracellular (Ca(2+) ) influence risk; and (3) cardiac ion channels not typically assessed may significantly affect risk. Our algorithm demonstrates the value of systematic simulations in predicting pharmacological toxicity.
---
paper_title: Global Optimization of Ventricular Myocyte Model to Multi-Variable Objective Improves Predictions of Drug-Induced Torsades de Pointes

paper_content:

In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity.
---
paper_title: Cellular basis of drug-induced torsades de pointes

paper_content:

Striking QT prolongation and the morphologically distinctive ventricular tachycardia torsades de pointes can occur in up to 5% of patients treated with certain antiarrhythmic drugs. This adverse drug reaction also occurs, albeit far less frequently, during therapy with a range of drugs not used for cardiovascular indications; examples include certain antibiotics, antipsychotics and antihistamines. The common mechanism for drug-induced torsades de pointes is inhibition of a specific repolarizing potassium current, I(Kr). The key question facing clinicians, regulators and those who develop drugs is why torsades de pointes only occurs in some patients exposed to I(Kr) block. This paper reviews the clinical, cellular, molecular and genetic features of the arrhythmia that may provide an answer to this question and proposes future studies in this area.
---
paper_title: Characterization of loperamide-mediated block of hERG channels at physiological temperature and its proarrhythmia propensity.

paper_content:

BACKGROUND ::: Loperamide (Immodium®) is indicated for symptomatic control of diarrhea. It is a μ-opioid receptor agonist, and recently has been associated with misuse and abuse. At therapeutic doses loperamide has not been associated with cardiotoxicity. However, loperamide overdose is associated with proarrhythmia and death - two effects that are likely attributable to its block of cardiac ion channels that are critical for generating action potentials. In this study, we defined loperamide-hERG channel interaction characteristics, and used a ventricular myocyte action potential model to compare loperamide's proarrhythmia propensity to twelve drugs with defined levels of clinical risk. ::: ::: ::: METHODS AND RESULTS ::: Whole-cell voltage-clamp recordings were performed at 37°C on a HEK293 cell line stably expressing the hERG channel proteins, and loperamide was bath-applied to assess its effects on hERG current. Loperamide suppressed hERG current in a use- and voltage-dependent but frequency-independent manner, with a half-maximal inhibitory concentration <90nM. The onset of current suppression was concentration-dependent and appeared to follow a first-order reaction. Loperamide also altered the voltage-dependence of steady state hERG current properties. Electrophysiological data were integrated into a myocyte model that simulated dynamic drug-hERG channel interaction to estimate Torsade de Pointes risk through comparisons with reference drugs with defined clinical risk. In the context of overdose that would result in loperamide levels far exceeding those produced by therapeutic doses, loperamide is placed in the high risk category, alongside quinidine, bepridil, dofetilide, and sotalol. ::: ::: ::: CONCLUSIONS ::: The combined in vitro and in silico approach provides mechanistic insight regarding the potential for loperamide to generate cardiotoxicity in overdose situations. This strategy holds promise for improving cardiac safety assessment.
---
paper_title: Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment

paper_content:

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 (Cmax). However, when drug effects were extrapolated above 10× Cmax, 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.
---
paper_title: MICE Models: Superior to the HERG Model in Predicting Torsade de Pointes

paper_content:

Drug-induced block of the cardiac hERG (human Ether-a-go-go-Related Gene) potassium channel delays cardiac repolarization and increases the risk of Torsade de Pointes (TdP), a potentially lethal arrhythmia. A positive hERG assay has been embraced by regulators as a non-clinical predictor of TdP despite a discordance of about 30%. To test whether assaying concomitant block of multiple ion channels (Multiple Ion Channel Effects or MICE) improves predictivity we measured the concentration-responses of hERG, Nav1.5 and Cav1.2 currents for 32 torsadogenic and 23 non-torsadogenic drugs from multiple classes. We used automated gigaseal patch clamp instruments to provide higher throughput along with accuracy and reproducibility. Logistic regression models using the MICE assay showed a significant reduction in false positives (Type 1 errors) and false negatives (Type 2 errors) when compared to the hERG assay. The best MICE model only required a comparison of the blocking potencies between hERG and Cav1.2.
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paper_title: Next-Generation Model-Based Drug Discovery and Development: Quantitative and Systems Pharmacology

paper_content:

Pharmaceutical researchers have undertaken many initiatives and technologies to stem the rising costs of drug discovery and development. Biomarkers, adaptive trial designs, modeling, trial simulations, predictive metabolism, data mining, and disease models have reshaped the way in which researchers approach discovery and development. Quantitative pharmacology (QP), which leverages model-based approaches, operates at both cultural and technical levels to integrate data and scientific disciplines so as to utilize existing knowledge while concomitantly enhancing the ability to make predictions about future experiments and results.
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paper_title: Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium.

paper_content:

This white paper provides a summary of a scientific proposal presented at a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/Food and Drug Administration–sponsored Think Tank, held at Food and Drug Administration's White Oak facilities, Silver Spring, MD, on July 23, 2013, with the intention of moving toward consensus on defining a new paradigm in the field of cardiac safety in which proarrhythmic risk would be primarily assessed using nonclinical in vitro human models based on solid mechanistic considerations of torsades de pointes proarrhythmia. This new paradigm would shift the emphasis from the present approach that strongly relies on QTc prolongation (a surrogate marker of proarrhythmia) and could obviate the clinical Thorough QT study during later drug development. These discussions represent current thinking and suggestions for furthering our knowledge and understanding of the public health case for adopting a new, integrated nonclinical in vitro/in silico paradigm, the Comprehensive In Vitro Proarrhythmia Assay, for the assessment of a candidate drug's proarrhythmic liability, and for developing a public-private collaborative program to characterize the data content, quality, and approaches required to assess proarrhythmic risk in the absence of a Thorough QT study. This paper seeks to encourage multistakeholder input regarding this initiative and does not represent regulatory guidance.
---

Title: 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

Section 1: Introduction
Description 1: Provide an overview of the growth of quantitative systems pharmacology (QSP), its applications in drug development, the CiPA initiative, and the aim of the paper.

Section 2: TdP and Current Regulatory Paradigm
Description 2: Discuss the history of regulatory paradigms for assessing drug-induced prolonged QT intervals and TdP, and the limitations of current approaches.

Section 3: Comprehensive Understanding of TdP and the Use of In Silico Models in Proarrhythmia Risk Assessment
Description 3: Explain the mechanistic understanding of TdP, advancements in cardiac electrophysiology modeling, and the role of in silico models in predicting proarrhythmia risk.

Section 4: The CiPA In Silico Approach
Description 4: Describe the development and validation of the CiPA in silico model, the selection process for training and validation drugs, and the implementation of qNet for risk assessment.

Section 5: Lessons Learned and Considerations for Implementation
Description 5: Summarize key lessons from developing CiPA in silico models, and provide considerations for implementing similar models in regulatory paradigms and drug development.

Section 6: Promising Roles and Open Issues of QSP Models in a New Cardiac Safety Paradigm
Description 6: Explore potential future applications of QSP models in cardiac safety, including predicting other types of arrhythmias and integrating various pharmacodynamic effects.

Section 7: Concluding Remarks
Description 7: Conclude with the potential impact of QSP models on drug development, the significance of the CiPA in silico approach, and future directions for QSP-based cardiac safety assessments.