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Owing to its association with Torsades de Pointes, drug-induced QT interval prolongation has been and remains a significant hurdle to the development of safe, effective medicines. Genetic and pharmacological evidence highlighting the pivotal role the human ether-a-go-go-related gene (hERG) channel was a critical step in understanding how to start addressing this issue. It led to the development of hERG assays with the rapid throughput needed for the short timescales required in early drug discovery. The resulting volume of hERG data has fostered in silico models to help chemists design compounds with reduced hERG potency. In early drug discovery, a pragmatic approach based on exceeding a given potency value has been required to decide when a compound is likely to carry a low QT risk, to support its progression to late-stage discovery. At this point, the in vivo efficacy and metabolism characteristics of the potential drug are generally defined, as well its safety profile, which includes usually a dog study to assess QT interval prolongation risk. The hERG and in vivo QT data, combined with the likely indication and the estimated free drug level for efficacy, are put together to assess the risk that the potential drug will prolong QT in man. Further data may be required to refine the risk assessment before making the major investment decisions for full development. The non-clinical data are essential to inform decisions about compound progression and to optimize the design of clinical QT studies.

Non-clinical QT-related assays aligned to the pharmaceutical drug discovery and development phases are used in several ways. During the early discovery phases, assays are used for hazard identification and wherever possible for hazard elimination. The data generated enable us to: (i) establish structure-activity relationships and thereby; (ii) influence the medicinal chemistry design and provide tools for effective decision making; and provide structure-activity data for in silico predictive databases; (iii) solve problems earlier; (iv) provide reassurance for compound or project to progress; and (v) refine strategies as scientific and technical knowledge grows. For compounds progressing into pre-clinical development, the 'core battery' QT-related data enable an integrated risk assessment to: (i) fulfil regulatory requirements; (ii) assess the safety and risk-benefit for compound progression to man; (iii) contribute to defining the starting dose during the phase I clinical trials; (iv) influence the design of the phase I clinical trials; (v) identify clinically relevant safety biomarkers; and (vi) contribute to the patient risk management plan. Once a compound progresses into clinical development, QT-related data can be applied in the context of risk management and risk mitigation. The data from 'follow-up' studies can be used to: (i) support regulatory approval; (ii) investigate discrepancies that may have emerged within and/or between non-clinical and clinical data; (iii) understand the mechanism of an undesirable pharmacodynamic effect; (iv) provide reassurance for progression into multiple dosing in humans and/or large-scale clinical trials; and (v) assess drug-drug interactions. Based on emerging data, the integrated risk assessment is then reviewed in this article, and the benefit-risk for compound progression was re-assessed. Project examples are provided to illustrate the impact of non-clinical data to support compound progression throughout the drug discovery and development phases, and regulatory approval.

Drug-induced prolongation of the QT interval is having a significant impact on the ability of the pharmaceutical industry to develop new drugs. The development implications for a compound causing a significant effect in the 'Thorough QT/QTc Study' -- as defined in the clinical regulatory guidance (ICH E14) -- are substantial. In view of this, and the fact that QT interval prolongation is linked to direct inhibition of the hERG channel, in the early stages of drug discovery the focus is on testing for and screening out hERG activity. This has led to understanding of how to produce low potency hERG blockers whilst retaining desirable properties. Despite this, a number of factors mean that when an integrated risk assessment is generated towards the end of the discovery phase (by conducting at least an in vivo QT assessment) a QT interval prolongation risk is still often apparent; inhibition of hERG channel trafficking and partitioning into cardiac tissue are just two confounding factors. However, emerging information suggests that hERG safety margins have high predictive value and that when hERG and in vivo non-clinical data are combined, their predictive value to man, whilst not perfect, is >80%. Although understanding the anomalies is important and is being addressed, of greater importance is developing a better understanding of TdP, with the aim of being able to predict TdP rather than using an imperfect surrogate marker (QT interval prolongation). Without an understanding of how to predict TdP risk, high-benefit drugs for serious indications may never be marketed.

Background and Purpose: The rabbit isolated Langendorff heart model (SCREENIT) was used to investigate the proarrhythmic potential of a range of marketed drugs or drugs intended for market. These data were used to validate the SCREENIT model against clinical outcomes., Experimental Approach: Fifty-five drugs, 3 replicates and 2 controls were tested in a blinded manner. Proarrhythmia variables included a 10% change in MAPD(60), triangulation, instability and reverse frequency-dependence of the MAP. Early after-depolarisations, ventricular tachycardia, TdP and ventricular fibrillation were noted. Data are reported at nominal concentrations relative to EFTPC(max). Proarrhythmic scores were assigned to each drug and each drug category., Key Results: Category 1 and 2 drugs have the highest number of proarrhythmia variables and overt proarrhythmia while Category 5 drugs have the lowest, at every margin. At 30-fold the EFTPC(max), the mean proarrhythmic scores are: Category 1, 101+/-24; Category 2, 101+/-14; Category 3, 72+/-20; Category 4, 59+/-16 and Category 5, 22+/-9 points. Only drugs in Category 5 have mean proarrhythmic scores, below 30-fold, that remain within the Safety Zone., Conclusions and Implications: A 30-fold margin between effects and EFTPC(max) is sufficiently stringent to provide confidence to proceed with a new chemical entity, without incurring the risk of eliminating potentially beneficial drugs. The model is particularly useful where compounds have small margins between the hERG IC(50) and predicted EFTPC(max). These data suggest this is a robust and reliable assay that can add value to an integrated QT/TdP risk assessment.

Introduction: Estimation of a direct effect of drugs on the duration of the electrocardiogram (ECG) QT interval can be confused by drug-induced increases in heart rate (HR). The objective of this assessment was to identify a correction formula that adequately corrects QT over a wide range of HRs., Methods: Paired recordings of HR and QT interval measurements were obtained from 177 conscious Beagle dogs from both sexes in 9 toxicology studies. ECGs used for this evaluation were collected in either control vehicle-treated dogs, or from dogs prior to the first dose of a daily dosing regimen. Where more than one recording was available per dog, only one was used in the analyses. The assessments were made based on the lowest and highest pre-dose HR for each dog. Correction factors according to [Bazett, H.C. (1920). An analysis of the time relationships or time-relations of electrocardiograms. Heart 7:353-380], [Sagie, A., Larson, M.G., Goldberg, R.J., Bengtson, J.R., & Levy, D. (1992). An improved method for adjusting the QT interval for heart rate (the Framingham heart study). American Journal of Cardiology 70:797-801], [Fridericia, L.S. (1920). Die sytolendauer in elektrokardiogramm bei normalen menschen und bei herzkranken. Acta Medica Scandinavica 53:469-505.], [Todt, H., Krumpl, G., Krejcy, K. & Raberger, G. (1992). Mode of QT correction for heart rate: implications for the detection of inhomogeneous repolarization after myocardial infarction. American Heart Journal 124(3):602-609.] and [Van de Water, A., Verheyen, J., Xhonneux, R., & Reneman, R.S. (1989). An improved method to correct the QT interval of the electrocardiogram for changes in heart rate. Journal of Pharmacological Methods 22:207-217.] were applied to these QT intervals and plotted against HR. Linear regression statistical analyses using a single or multiple (i.e., baseline, sex and study) parameters model was then applied to trend lines., Results: Although two correction factors ([Todt, H., Krumpl, G., Krejcy, K. & Raberger, G. (1992). Mode of QT correction for heart rate: implications for the detection of inhomogeneous repolarization after myocardial infarction. American Heart Journal 124(3):602-609.] and [Van de Water, A., Verheyen, J., Xhonneux, R., & Reneman, R.S. (1989). An improved method to correct the QT interval of the electrocardiogram for changes in heart rate. Journal of Pharmacological Methods 22:207-217.]) adequately corrected QT for changes in HR [i.e., slope of QTc versus HR not statistically significantly different from zero (p>0.05)] that of Van de Water showed a statistically superior correction. Although the method of analyses accounted for baseline, sex and study it was independently demonstrated that sex did not influence the outcome of the evaluations. Furthermore, higher HRs (i.e., maximum HRs for each dog) were better corrected than the lower HRs. In addition, statistical power analysis applied to these data showed that group sizes of 4-8 could, with 80% chance, detect a 10-5% change, respectively, in appropriately corrected QT., Discussion: Overall, the data suggest that an evaluation of the most appropriate correction factor should be applied to each laboratory using their own data collected by their own method in their particular strain of dog.

The inhibition of the hERG-encoded potassium channel can lead to prolongation of the cardiac action potential--manifested as a prolongation of the QT interval on the ECG. Although QT interval prolongation is not dangerous per se, in a small percentage of cases, it is associated with a potentially fatal arrhythmia: Torsades de Pointes (TdP). This channel type is pharmacologically promiscuous, so many compounds have caused QT interval prolongation in man and this has led to drugs being withdrawn from the market following evidence of TdP. From a drug discovery perspective, focusing as early as possible on screening out hERG activity is important. Retrospective analysis of hERG potency versus clinical incidence of TdP suggests provisional safety margins that could be used as target values by medicinal chemists. Large safety margins will not always be possible; however, and in such circumstances, if the risk-benefit ratio still favours developing the compound, a pre-clinical assessment of the likelihood that any QT interval prolongation will or will not lead to TdP in man may be important. An isolated rabbit heart model of arrhythmia shows promise in this respect, based on a comparison of clinical data with that obtained from this assay. Specific regulatory guidance on this topic is still in the draft form but the pre-clinical document (ICH S7B) contains a largely useful perspective on how an integrated risk assessment could be formed using in vitro and in vivo assays. The role of this document is evolving however, since the draft clinical guideline (E14) suggests that irrespective of the pre-clinical data, a thorough clinical ECG study will be required at some point during development.

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.

Proarrhythmia models use electrophysiological markers to predict the risk of torsade de pointes (TdP) in patients. The set of variables used by each model to predict the torsadogenic propensity of a drug has been reported to correlate with clinical outcome; however, these reports should be interpreted cautiously as no model has been independently assessed. Each model is discussed along with its merits and shortcomings; none, as yet, having shown a predictive value that makes it clearly superior to the others. As predictive as these models may become, extrapolation of results directly to the clinic must be exercised with caution. The use of in silico models, from subcellular to whole system, is rapidly beginning to form the first line of screening activity in many drug discovery programmes, indicating that biological experimentation may become secondary to analysis by simulation. In vitro proarrhythmia models challenge current perceptions of appropriate surrogates for TdP in man and question existing non-clinical strategies for assessing proarrhythmic risk. The rapid emergence of such models, compounded by the lack of a clear understanding of the key proarrhythmic mechanisms has resulted in a regulatory reluctance to embrace such models. The wider acceptance of proarrhythmia models is likely to occur when there is a clear understanding and agreement on the key proarrhythmia mechanisms. With greater acceptance and ongoing improvements, these models have the potential to unravel the complex mechanisms underlying TdP. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]