Key clinical considerations for demonstrating the utility of preclinical models to predict clinical drug-induced torsades de pointes

A simple accurate method for concentration-QTc analysis in preclinical animal models

INTRODUCTION

In preclinical cardiovascular safety pharmacology studies, statistical analysis of the rate corrected QT interval (QTc) is the focus for predicting QTc interval changes in the clinic. Modeling of a concentration/QTc relationship, common clinically, is limited due to minimal pharmacokinetic (PK) data in nonclinical testing. It is possible, however, to relate the average drug plasma concentration from sparse PK samples over specific times to the mean corrected QTc. We hypothesize that averaging drug plasma concentration and the QTc-rate relationship over time provides a simple, accurate concentration-QTc relationship bridging statistical and concentration/QTc modeling.

METHODS

Cardiovascular telemetry studies were conducted in non-human primates (NHP; n = 48) and canines (n = 8). Pharmacokinetic samples were collected on separate study days in both species. Average plasma concentrations for specific intervals (CAverage0-X) were calculated for moxifloxacin in canines and NHP using times corresponding to super-intervals for the QTc data statistical analysis. The QTc effect was calculated for each super-interval using a linear regression correction incorporating QT and HR data from the whole super-interval. The concentration QTc effects were then modeled.

RESULTS

In NHP, a 10.9 ± 0.06 ms (mean ± 95% CI) change in QTc was detected at approximately 1.5× the moxifloxacin plasma concentration that causes a 10 ms QTc change in humans, based on a 0-24 h super-interval. When simulating a drug without QT effects, mock, no effect on QTc was detected at up to 3× the clinical concentration. Similarly, in canines, a 16.6 ± 0.1 ms change was detected at 1.7× critical clinical moxifloxacin concentration, and a 0.04 ± 0.1 ms change was seen for mock.

CONCLUSIONS

While simultaneous PK and QTc data points are preferred, practical constraints and the need for QTc averaging did not prevent concentration-QTc analyses. Utilizing a 0-24 h super-interval method illustrates a simple and effective method to address cardiovascular questions when preclinical drug exposures exceed clinical concentrations.

QT Ratio: A simple solution to individual QT correction

Preclinical risk assessment of drug-induced arrhythmias is critical for drug development and relies on heart rate corrected QT interval (QT) prolongation as a biomarker for arrhythmia risk. However, the methods used to correct QT vary in complexity and don't account for all changes in the QT-rate relationship. Thus, we developed the novel Ratio QT correction method which characterizes that relationship at each timepoint using the ratio between QT, adjusted for a species-specific constant, and rate (RR interval). This ratio represents the slope between the intercept and the datapoint being corrected, which is then used in a linear equation like individual methods. A unique correction coefficient for each datapoint avoids assuming static relationships. We hypothesize that the simple and dynamic nature of the Ratio method will provide more consistent rate correction and error reduction compared to Bazett's and individual regression methods. Comparisons were made using ECG data from non-human primates (NHPs) treated with dofetilide or moxifloxacin, separated into small groups (n = 4). The methods were compared based on corrected QT vs RR slopes, standard error, and minimal detectable difference (MDD) for each method. The Ratio method resulted in smaller corrected QT-rate relationship slopes than Bazett's, more closely matching those of individual methods. It produced similar or lower MDDs compared to individual and Bazett's correction, respectively, with more consistent reduction in standard error. This simple and effective method has the potential for easy translatability across species.

Improving corrected QT; Why individual correction is not enough

The use of QT-prolongation as a biomarker for arrhythmia risk requires that researchers correct the QT-interval (QT) to control for the influence of heart rate (HR). QT correction methods can vary but most used are the universal correction methods, such as Bazett's or Van de Water's, which use a single correction formula to correct QT-intervals in all the subjects of a study. Such methods fail to account for differences in the QT/HR relationship between subjects or over time, instead relying on the assumption that this relationship is consistent. To address these changes in rate relationships, we test the effectiveness of linear and non-linear individual correction methods. We hypothesize that individual correction methods that account for additional influences on the rate relationship will result in more effective and consistent correction. To increase the scope of this study we use bootstrap sampling on ECG recordings from non-human primates and beagle canines dosed with vehicle control. We then compare linear and non-linear individual correction methods through their ability to reduce HR correlation and standard deviation of corrected QT values. From these results, we conclude that individual correction methods based on post-treatment data are most effective with the linear methods being the best option for most cases in both primates and canines. We also conclude that the non-linear methods are more effective in canines than primates and that accounting for light status can improve correction while examining the data from the light periods separately. Individual correction requires careful consideration of inter-subject and intra-subject variabilities.

Sex Differences in Drug-Induced Arrhythmogenesis

The electrical activity in the heart varies significantly between men and women and results in a sex-specific response to drugs. Recent evidence suggests that women are more than twice as likely as men to develop drug-induced arrhythmia with potentially fatal consequences. Yet, the sex-specific differences in drug-induced arrhythmogenesis remain poorly understood. Here we integrate multiscale modeling and machine learning to gain mechanistic insight into the sex-specific origin of drug-induced cardiac arrhythmia at differing drug concentrations. To quantify critical drug concentrations in male and female hearts, we identify the most important ion channels that trigger male and female arrhythmogenesis, and create and train a sex-specific multi-fidelity arrhythmogenic risk classifier. Our study reveals that sex differences in ion channel activity, tissue conductivity, and heart dimensions trigger longer QT-intervals in women than in men. We quantify the critical drug concentration for dofetilide, a high risk drug, to be seven times lower for women than for men. Our results emphasize the importance of including sex as an independent biological variable in risk assessment during drug development. Acknowledging and understanding sex differences in drug safety evaluation is critical when developing novel therapeutic treatments on a personalized basis. The general trends of this study have significant implications on the development of safe and efficacious new drugs and the prescription of existing drugs in combination with other drugs.

Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning

Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for all new therapeutic compounds. Unfortunately, these have proven to be poor predictors of torsadogenic risk, and are likely to have prevented safe compounds from reaching clinical phases. Although this has stimulated numerous efforts to define new paradigms for cardiac safety, none of the recently developed strategies accounts for patient conditions. In particular, despite being a well-established independent risk factor for TdP, female sex is vastly under-represented in both basic research and clinical studies, and thus current TdP metrics are likely biased toward the male sex. Here, we apply statistical learning to synthetic data, generated by simulating drug effects on cardiac myocyte models capturing male and female electrophysiology, to develop new sex-specific classification frameworks for TdP risk. We show that (i) TdP classifiers require different features in females vs. males; (ii) male-based classifiers perform more poorly when applied to female data; and (iii) female-based classifier performance is largely unaffected by acute effects of hormones (i.e., during various phases of the menstrual cycle). Notably, when predicting TdP risk of intermediate drugs on female simulated data, male-biased predictive models consistently underestimate TdP risk in women. Therefore, we conclude that pipelines for preclinical cardiotoxicity risk assessment should consider sex as a key variable to avoid potentially life-threatening consequences for the female population.

Electrophysiological and ECG Effects of Perhexiline, a Mixed Cardiac Ion Channel Inhibitor, Evaluated in Nonclinical Assays and in Healthy Subjects

Perhexiline has been used to treat hypertrophic cardiomyopathy. In addition to its effect on carnitine-palmitoyltransferase-1, it has mixed ion channel effects through inhibition of several cardiac ion currents. Effects on cardiac ion channels expressed in mammalian cells were assayed using a manual patch-clamp technique, action potential duration (APD) was measured in ventricular trabeculae of human donor hearts, and electrocardiogram effects were evaluated in healthy subjects in a thorough QT (TQT) study. Perhexiline blocked several cardiac ion currents at concentrations within the therapeutic range (150-600 ng/mL) with IC₅₀ for hCav1.2 ∼ hERG < late hNav1.5. A significant APD shortening was observed in perhexiline-treated cardiomyocytes. The TQT study was conducted with a pilot part in 9 subjects to evaluate a dosing schedule that would achieve therapeutic and supratherapeutic perhexiline plasma concentrations on days 4 and 6, respectively. Guided by the results from the pilot, 104 subjects were enrolled in a parallel-designed part with a nested crossover comparison for the positive control. Perhexiline caused QTc prolongation, with the largest effect on ΔΔQTcF, 14.7 milliseconds at therapeutic concentrations and 25.6 milliseconds at supratherapeutic concentrations and a positive and statistically significant slope of the concentration-ΔΔQTcF relationship (0.018 milliseconds per ng/mL; 90%CI, 0.0119-0.0237 milliseconds per ng/mL). In contrast, the JTpeak interval was shortened with a negative concentration-JTpeak relationship, a pattern consistent with multichannel block. Further studies are needed to evaluate whether this results in a low proarrhythmic risk.

Time for a Fully Integrated Nonclinical-Clinical Risk Assessment to Streamline QT Prolongation Liability Determinations: A Pharma Industry Perspective

Defining an appropriate and efficient assessment of drug‐induced corrected QT interval (QTc) prolongation (a surrogate marker of torsades de pointes arrhythmia) remains a concern of drug developers and regulators worldwide. In use for over 15 years, the nonclinical International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) S7B and clinical ICH E14 guidances describe three core assays (S7B: in vitro hERG current & in vivo QTc studies; E14: thorough QT study) that are used to assess the potential of drugs to cause delayed ventricular repolarization. Incorporating these assays during nonclinical or human testing of novel compounds has led to a low prevalence of QTc‐prolonging drugs in clinical trials and no new drugs having been removed from the marketplace due to unexpected QTc prolongation. Despite this success, nonclinical evaluations of delayed repolarization still minimally influence ICH E14‐based strategies for assessing clinical QTc prolongation and defining proarrhythmic risk. In particular, the value of ICH S7B‐based “double‐negative” nonclinical findings (low risk for hERG block and in vivo QTc prolongation at relevant clinical exposures) is underappreciated. These nonclinical data have additional value in assessing the risk of clinical QTc prolongation when clinical evaluations are limited by heart rate changes, low drug exposures, or high‐dose safety considerations. The time has come to meaningfully merge nonclinical and clinical data to enable a more comprehensive, but flexible, clinical risk assessment strategy for QTc monitoring discussed in updated ICH E14 Questions and Answers. Implementing a fully integrated nonclinical/clinical risk assessment for compounds with double‐negative nonclinical findings in the context of a low prevalence of clinical QTc prolongation would relieve the burden of unnecessary clinical QTc studies and streamline drug development.

Relationship of clinical adverse event reports to models of arrhythmia risk

A vital aspect of the drug discovery and development process is the identification and filtering of drugs with high risk of dangerous adverse events. Torsade de Pointes (TdP) is one example of an adverse event that requires thorough in vitro and in vivo drug screening. This is because TdP, a tachycardic ventricular arrhythmia, can develop into fatal cardiac events if left unresolved and has been missed during drug development with profound consequences. These factors led to the development of pre-clinical screening guidelines based on the presence of drug induced QT prolongation (QTp), which has been linked to TdP. These guidelines have high sensitivity, but low specificity, as they tend to predict QTp, which precedes TdP events but does not always lead to TdP. Computational models have the potential to improve these prediction methods by bridging the gaps between preclinical and clinical data. This study proposes the use of adverse event reports obtained from the FDA Adverse Event Reporting System as a representation of clinical TdP risk. By incorporating these reports into computational models, a more accurate risk prediction may be developed.

Meet the relatives: a reintroduction to the clinical pharmacology of ‘typical’ antipsychotics (Part 2)

This second of two articles on the ‘typical’ (‘first-generation’) antipsychotics covers non-phenothiazines: thioxanthenes (flupentixol and zuclopenthixol), butyrophenones/diphenylbutylpiperidines (including one-time world market-leader haloperidol, and pimozide) and sulpiride, for many years the only substituted benzamide available in the UK. Several tolerability issues ascribed specifically or more frequently to older antipsychotics are also discussed.

Lack of relationship between plasma levels of escitalopram and QTc-interval length

Despite safety concerns raised by the European Medicines Agency (EMA), evidence supporting QT-lengthening effects of escitalopram is far to be conclusive. We aimed to evaluate the relationship between escitalopram plasma levels (Escit-PL) and corrected QT-interval length (QTc-length) in 91 outpatients recruited from a hospital setting. Fifteen patients had an abnormally prolonged QTc-interval, and 3 had QTc-intervals ≥500 ms. No correlation between Escit-PL and QTc-length was found (r = 0.08; p = 0.45). Linear/logistic regression analyses were also conducted taking into account potential confounders such as age, gender, personal history of heart disease, medication load and concomitant use of antipsychotic/tricyclic antidepressants. Escit-PL did not predict either QTc-length or abnormally prolonged QTc-interval. Only antipsychotics/tricyclics use (adjusted β = 0.26, SE = 9.1; p = 0.01) was an independent predictor of QTc-length (R ² = 0.096, F = 4.68, df = 2,88; p = 0.01). Only antipsychotics/tricyclics use (OR 3.56 [95% CI 1.01-12.52]; p < 0.05) and medication load (OR 1.32 [95% CI 1.06-1.64]; p < 0.01) were significantly associated with an increased risk of abnormally prolonged QTc-interval (Omnibus test χ ² = 9.5, df = 2; p < 0.01). Our study did not find a significant relationship between Escit-PL and QTc-length even when recognized modulating factors of the QT-interval were controlled for. Concomitant use of other potentially arrhythmogenic agents may help to explain the apparent link between escitalopram and QT prolongation previously suggested. The advisability of maintaining the EMA warning is once again called into question.

High-throughput cardiac safety evaluation and multi-parameter arrhythmia profiling of cardiomyocytes using microelectrode arrays

Microelectrode arrays (MEAs) recording extracellular field potentials of human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) provide a rich data set for functional assessment of drug response. The aim of this work is the development of a method for a systematic analysis of arrhythmia using MEAs, with emphasis on the development of six parameters accounting for different types of cardiomyocyte signal irregularities. We describe a software approach to carry out such analysis automatically including generation of a heat map that enables quick visualization of arrhythmic liability of compounds. We also implemented signal processing techniques for reliable extraction of the repolarization peak for field potential duration (FPD) measurement even from recordings with low signal to noise ratios. We measured hiPS-CM's on a 48 well MEA system with 5minute recordings at multiple time points (0.5, 1, 2 and 4h) after drug exposure. We evaluated concentration responses for seven compounds with a combination of hERG, QT and clinical proarrhythmia properties: Verapamil, Ranolazine, Flecainide, Amiodarone, Ouabain, Cisapride, and Terfenadine. The predictive utility of MEA parameters as surrogates of these clinical effects were examined. The beat rate and FPD results exhibited good correlations with previous MEA studies in stem cell derived cardiomyocytes and clinical data. The six-parameter arrhythmia assessment exhibited excellent predictive agreement with the known arrhythmogenic potential of the tested compounds, and holds promise as a new method to predict arrhythmic liability.

Screening system for drug-induced arrhythmogenic risk combining a patch clamp and heart simulator

To save time and cost for drug discovery, a paradigm shift in cardiotoxicity testing is required. We introduce a novel screening system for drug-induced arrhythmogenic risk that combines in vitro pharmacological assays and a multiscale heart simulator. For 12 drugs reported to have varying cardiotoxicity risks, dose-inhibition curves were determined for six ion channels using automated patch clamp systems. By manipulating the channel models implemented in a heart simulator consisting of more than 20 million myocyte models, we simulated a standard electrocardiogram (ECG) under various doses of drugs. When the drug concentrations were increased from therapeutic levels, each drug induced a concentration-dependent characteristic type of ventricular arrhythmia, whereas no arrhythmias were observed at any dose with drugs known to be safe. We have shown that our system combining in vitro and in silico technologies can predict drug-induced arrhythmogenic risk reliably and efficiently.

Electrocardiographic effects of class 1 selective histone deacetylase inhibitor romidepsin

Romidepsin is a histone deacetylase inhibitor approved by the FDA for the treatment of patients with cutaneous or peripheral T-cell lymphoma who have received prior systemic therapy. The objective of this analysis was to evaluate the potential QTc effects of romidepsin. Patients with advanced malignancy received 4-h infusions of 14 mg/m² romidepsin on days 1, 8, and 15 of a 28-day cycle. In cycle 2, a subset of patients received 1-h infusions of 8–12 mg/m² romidepsin. Patients were administered antiemetics before each romidepsin dose and electrolyte supplementation as needed. Electrocardiogram readings were performed prior to antiemetic administration, prior to romidepsin administration, and at specified time points over the subsequent 24 h. Romidepsin exposure and heart rate were also assessed. In the electrocardiogram-evaluable population, 26 patients received romidepsin at 14 mg/m² over 4 h. The maximum mean increases from the preantiemetic baseline for QTcF and heart rate were 10.1 msec (upper 90% CI, 14.5 msec) and 18.2 beats per minute, respectively. No patient in this study had an absolute QTcF value >450 msec and only one patient had an increase from the preantiemetic baseline of >60 msec. There was a mild reduction in the PR interval and no meaningful changes in the QRS interval. Despite the use of QT-prolonging antiemetics, treatment with romidepsin did not markedly prolong the QTc interval through 24 h. Increases in calculated QTc may have been exaggerated as a consequence of transient increases in heart rate.

Evidence for a crucial modulating role of the sodium channel in the QTc prolongation related to antipsychotics

Blockade of the cardiac hERG channel is recognized as the main mechanism underlying the QT prolongation induced by many classes of drugs, including antipsychotics. However, antipsychotics interact with a variety of other pharmacological targets that could also modulate cardiac function. The present study aims to identify those key factors involved in the QT prolongation induced by antipsychotics. The interactions of 28 antipsychotics were measured on a variety of pharmacological targets. Binding affinity (K(i)), functional channel blockade (IC₅₀), and the corresponding ratios to total and free plasma drug concentration were compared with the corrected QT changes (QTc) associated with the therapeutic use of these drugs by multivariable linear regression analysis to determine the best predictors of QTc. Besides confirming hERG as the primary predictor of QTc, all analyses consistently show the concomitant involvement of Na(V)1.5 channel as modulating factor of the QTc related to hERG blockade. In particular, the hERG/Na(V)1.5 ratio explains the 57% of the overall QTc variability associated with antipsychotics. Since it is known that inhibition of late I Na could offset the dysfunctional effects of hERG blockade, we hypothesize the inhibition of late I(Na) as a crucial compensatory mechanism of the QTc associated with antipsychotics and hence an important factor to consider concomitantly with hERG blockade to appraise the arrhythmogenic risk of these drugs more accurately.

Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium

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.

MICE models: superior to the HERG model in predicting Torsade de Pointes

Drug-induced block of the cardiac hERG (human Ether-à-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.

Methodologies to characterize the QT/corrected QT interval in the presence of drug-induced heart rate changes or other autonomic effects

This White Paper, written collaboratively by members of the Cardiac Safety Research Consortium from academia, industry, and regulatory agencies, discusses different methods to characterize the QT effects for drugs that have a substantial direct or indirect effect on heart rate. Descriptions and applications are provided for individualized QT-R-R correction, Holter bin, dynamic QT beat-to-beat, pharmacokinetic-pharmacodynamic modeling, and QT assessment at constant heart rate. Most of these techniques are optimally performed using continuous electrocardiogram data obtained in clinical studies designed to characterize a drug's effect on the QT interval. An important study design element is the collection of drug-free data over a range of heart rates seen on treatment. The range of heart rates is increased at baseline by using ambulatory electrocardiogram recordings in addition to those collected under semisupine, resting conditions. Discussions in this study summarize areas of emerging consensus and other areas in which consensus remains elusive and provide suggestions for additional research to further increase our knowledge and understanding of this topic.

Estimating the risk of drug-induced proarrhythmia using human induced pluripotent stem cell-derived cardiomyocytes

Improved in vitro systems for predicting drug-induced toxicity are needed in the pharmaceutical and biotechnology industries to decrease late-stage drug attrition. One unmet need is an early screen for cardiotoxicity, which accounts for about one third of safety-based withdrawn pharmaceuticals. Herein, the first published report of a high-throughput functional assay employing a monolayer of beating human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) is described, detailing a model that accurately detects drug-induced cardiac abnormalities. Using 96-well plates with interdigitated electrode arrays that assess impedance, the rhythmic, synchronous contractions of the iPSC-CMs were detected. Treatment of the iPSC-CMs with 28 different compounds with known cardiac effects resulted in compound-specific changes in the beat rate and/or the amplitude of the impedance measurement. Changes in impedance for the compounds tested were comparable with the results from a related technology, electric field potential assessment obtained from microelectrode arrays. Using the results from the set of compounds, an index of drug-induced arrhythmias was calculated, enabling the determination of a drug's proarrhythmic potential. This system of interrogating human cardiac function in vitro opens new opportunities for predicting cardiac toxicity and studying cardiac biology.

Successful drug development despite adverse preclinical findings part 2: examples

To illustrate the process of addressing adverse preclinical findings (APFs) as outlined in the first part of this review, a number of cases with unexpected APF in toxicity studies with drug candidates is discussed in this second part. The emphasis is on risk characterization, especially regarding the mode of action (MoA), and risk evaluation regarding relevance for man. While severe APFs such as retinal toxicity may turn out to be of little human relevance, minor findings particularly in early toxicity studies, such as vasculitis, may later pose a real problem. Rodents are imperfect models for endocrine APFs, non-rodents for human cardiac effects. Liver and kidney toxicities are frequent, but they can often be monitored in man and do not necessarily result in early termination of drug candidates. Novel findings such as the unusual lesions in the gastrointestinal tract and the bones presented in this review can be difficult to explain. It will be shown that well known issues such as phospholipidosis and carcinogenicity by agonists of peroxisome proliferator-activated receptors (PPAR) need to be evaluated on a case-by-case basis. The latter is of particular interest because the new PPAR α and dual α/γ agonists resulted in a change of the safety paradigm established with the older PPAR α agonists. General toxicologists and pathologists need some understanding of the principles of genotoxicity and reproductive toxicity testing. Both types of preclinical toxicities are major APF and clinical monitoring is difficult, generally leading to permanent use restrictions.

Successful drug development despite adverse preclinical findings part 1: processes to address issues and most important findings

Unexpected adverse preclinical findings (APFs) are not infrequently encountered during drug development. Such APFs can be functional disturbances such as QT prolongation, morphological toxicity or carcinogenicity. The latter is of particular concern in conjunction with equivocal genotoxicity results. The toxicologic pathologist plays an important role in recognizing these effects, in helping to characterize them, to evaluate their risk for man, and in proposing measures to mitigate the risk particularly in early clinical trials. A careful scientific evaluation is crucial while termination of the development of a potentially useful drug must be avoided. This first part of the review discusses processes to address unexpected APFs and provides an overview over typical APFs in particular classes of drugs. If the mode of action (MoA) by which a drug candidate produces an APF is known, this supports evaluation of its relevance for humans. Tailor-made mechanistic studies, when needed, must be planned carefully to test one or several hypotheses regarding the potential MoA and to provide further data for risk evaluation. Safety considerations are based on exposure at no-observed-adverse-effect levels (NOAEL) of the most sensitive and relevant animal species and guide dose escalation in clinical trials. The availability of early markers of toxicity for monitoring of humans adds further safety to clinical studies. Risk evaluation is concluded by a weight of evidence analysis (WoE) with an array of parameters including drug use, medical need and alternatives on the market. In the second part of this review relevant examples of APFs will be discussed in more detail.

Integrated risk assessment and predictive value to humans of non-clinical repolarization assays

The potential for drugs to be associated with the life-threatening arrhythmia, Torsades de Pointes (TdeP), continues to be a topic of regulatory, academic and industrial concern. Despite being an imperfect biomarker, prolongation of the QT interval of the surface ECG is used to assess the risk of a drug being associated with TdeP such that a thorough examination of drug effects on the QT interval is required for all new chemical entities. Numerous studies have investigated the relationship between non-clinical findings and the risk of TdeP and QT prolongation in the general population. There are many literature references supporting the strong correlation between the clinical safety margin over human ether-a-go-go (hERG) inhibitory potency and the risk of drug-induced arrhythmia and sudden death. A quantitative analysis of the relationship between non-clinical studies and the outcome of a human Thorough QT study has also been reported. In the current manuscript, based on the outcome of the non-clinical assays the sensitivity and specificity of each assay and an integrated risk assessment for predicting the outcome of the human Thorough QT study has been conducted. The data suggest that for QT prolongation mediated through inhibition of the hERG current the non-clinical assays are highly predictive of drug effects on the QT interval. Based on the literature review and specific quantitative analysis reported above it is concluded that non-clinical assays predict the risk of compounds to prolong the QT interval and cause TdeP in humans if the mechanism is through inhibition of the hERG current.

International Life Sciences Institute (Health and Environmental Sciences Institute, HESI) initiative on moving towards better predictors of drug-induced torsades de pointes

Knowledge of the cardiac safety of emerging new drugs is an important aspect of assuring the expeditious advancement of the best candidates targeted at unmet medical needs while also assuring the safety of clinical trial subjects or patients. Present methodologies for assessing drug-induced torsades de pointes (TdP) are woefully inadequate in terms of their specificity to select pharmaceutical agents, which are human arrhythmia toxicants. Thus, the critical challenge in the pharmaceutical industry today is to identify experimental models, composite strategies, or biomarkers of cardiac risk that can distinguish a drug, which prolongs cardiac ventricular repolarization, but is not proarrhythmic, from one that prolongs the QT interval and leads to TdP. To that end, the HESI Proarrhythmia Models Project Committee recognized that there was little practical understanding of the relationship between drug effects on cardiac ventricular repolarization and the rare clinical event of TdP. It was on that basis that a workshop was convened in Virginia, USA at which four topics were introduced by invited subject matter experts in the following fields: Molecular and Cellular Biology Underlying TdP, Dynamics of Periodicity, Models of TdP Proarrhythmia, and Key Considerations for Demonstrating Utility of Pre-Clinical Models. Contained in this special issue of the British Journal of Pharmacology are reports from each of the presenters that set out the background and key areas of discussion in each of these topic areas. Based on this information, the scientific community is encouraged to consider the ideas advanced in this workshop and to contribute to these important areas of investigations over the next several years.

Early clinical development: evaluation of drug-induced torsades de pointes risk

Drug-induced arrhythmias or QT interval prolongation is one of the two most common reasons for drugs to be denied regulatory approval or to have warnings imposed on their clinical labelling. The assessment of torsades de pointes (TdP) risk during clinical development of a new pharmaceutical compound has been an issue of debate since the original description of drug-induced proarrhythmia. TdP risk assessment is complicated by the very low incidence (e.g., <1/100,000 patient years of exposure) of clinical events for non-antiarrhythmic agents and thus the improbable likelihood of observing even one event during clinical development. Thus surrogate methods of determining risk are necessary. A clinical approach to the issue of TdP risk assessment during drug development has been developed and implemented internationally. These efforts have markedly reduced the likelihood that drugs with unknown TdP risks will be commercialized, have resulted in fostering extensive productive pre-clinical and clinical research, and subsequent improved understanding of drug-induced proarrhythmia. Current research efforts are directed to increasing the efficiency of clinical QT assessment and the impact of pre-clinical assessment on clinical development. This article describes the clinical evaluation of TdP risk during drug development and how pre-clinical assessment can impact the early clinical development TdP risk assessment.