ICH S7B In Vitro Assays Do Not Address Mechanisms of QTC Prolongation for Peptides and Proteins - Data in Support of Not Needing Dedicated QTC Studies.

Current cardiac safety testing focuses on detecting drug-induced QTC prolongation as a surrogate for risk of Torsade de Pointes. The nonclinical strategy, described in International Conference on Harmonization (ICH) S7B, includes in vitro assessment of hERG block or ventricular repolarization delay and in vivo QT prolongation. Several studies have reported predictive values of ICH S7B results for clinical QTC outcomes for small molecules; none has examined peptides and proteins other than monoclonal antibodies. To address this knowledge gap, information for peptides and proteins submitted to the US Food and Drug Administration (FDA) was collected. Results of hERG assays, ventricular repolarization assays, and in vivo QT assessment were compared with clinical QTC study outcomes. The results show that 14% clinical QTC studies for approved and investigational products failed to exclude 10-ms QTC prolongation. Clinical QTC prolongation for these molecules lacked concentration-dependence which is expected for hERG block-mediated mechanism or QTC prolongation could not be excluded due to characterization in the clinical study. The hERG and ventricular repolarization assays do not identify clinical QTC prolongation potential for peptides and proteins. Lack of alignment between hERG and ventricular repolarization assay results and clinical QTC outcomes suggests that the mechanisms of QTC prolongation by some peptides and proteins are unrelated to direct cardiac ion channel block. Similar to large targeted proteins and monoclonal antibodies, peptides and proteins regardless of size have a low likelihood of direct cardiac ion channel interactions. This characteristic supports waiving the requirement for thorough QT assessment for products comprised of naturally occurring amino acids unless proarrhythmia potential is suggested by nonclinical or clinical data.

Innovations in Pediatric Therapeutics Development: Principles for the Use of Bridging Biomarkers in Pediatric Extrapolation.

Even with recent substantive improvements in health care in pediatric populations, considerable need remains for additional safe and effective interventions for the prevention and treatment of diseases in children. The approval of prescription drugs and biological products for use in pediatric settings, as in adults, requires demonstration of substantial evidence of effectiveness and favorable benefit-to-risk. For diseases primarily affecting children, such evidence predominantly would be obtained in the pediatric setting. However, for conditions affecting both adults and children, pediatric extrapolation uses scientific evidence in adults to enable more efficiently obtaining a reliable evaluation of an intervention's effects in pediatric populations. Bridging biomarkers potentially have an integral role in pediatric extrapolation. In a setting where an intervention reliably has been established to be safe and effective in adults, and where there is substantive evidence that disease processes in pediatric and adult settings are biologically similar, a 'bridging biomarker' should satisfy three additional criteria: effects on the bridging biomarker should capture effects on the principal causal pathway through which the disease process meaningfully influences 'feels, functions, survives' measures; secondly, the experimental intervention should not have important unintended effects on 'feels, functions, survives' measures not captured by the bridging biomarker; and thirdly, in statistical analyses in adults, the intervention's net effect on 'feels, functions, survives' measures should be consistent with what would be predicted by its level of effect on the bridging biomarker. A validated bridging biomarker has considerable potential utility, since an intervention's efficacy could be extrapolated from adult to pediatric populations if evidence in children establishes the intervention not only to be safe but also to have substantive effects on that bridging biomarker. Proper use of bridging biomarkers could increase availability of reliably evaluated therapies approved for use in pediatric settings, enabling children and their caregivers to make informed choices about health care.

The Challenges of Predicting Drug-Induced QTc Prolongation in Humans.

The content of this article derives from a Health and Environmental Sciences Institute (HESI) consortium with a focus to improve cardiac safety during drug development. A detailed literature review was conducted to evaluate the concordance between nonclinical repolarization assays and the clinical thorough QT (TQT) study. Food and Drug Administration and HESI developed a joint database of nonclinical and clinical data, and a retrospective analysis of 150 anonymized drug candidates was reviewed to compare the performance of 3 standard nonclinical assays with clinical TQT study findings as well as investigate mechanism(s) potentially responsible for apparent discrepancies identified. The nonclinical assays were functional (IKr) current block (Human ether-a-go-go related gene), action potential duration, and corrected QT interval in animals (in vivo corrected QT). Although these nonclinical assays demonstrated good specificity for predicting negative clinical QT prolongation, they had relatively poor sensitivity for predicting positive clinical QT prolongation. After review, 28 discordant TQT-positive drugs were identified. This article provides an overview of direct and indirect mechanisms responsible for QT prolongation and theoretical reasons for lack of concordance between clinical TQT studies and nonclinical assays. We examine 6 specific and discordant TQT-positive drugs as case examples. These were derived from the unique HESI/Food and Drug Administration database. We would like to emphasize some reasons for discordant data including, insufficient or inadequate nonclinical data, effects of the drug on other cardiac ion channels, and indirect and/or nonelectrophysiological effects of drugs, including altered heart rate. We also outline best practices that were developed based upon our evaluation.

Understanding Circadian Mechanisms of Sudden Cardiac Death: A Report From the National Heart, Lung, and Blood Institute Workshop, Part 1: Basic and Translational Aspects.

Sudden cardiac death (SCD), the unexpected death due to acquired or genetic cardiovascular disease, follows distinct 24-hour patterns in occurrence. These 24-hour patterns likely reflect daily changes in arrhythmogenic triggers and the myocardial substrate caused by day/night rhythms in behavior, the environment, and endogenous circadian mechanisms. To better address fundamental questions regarding the circadian mechanisms, the National Heart, Lung, and Blood Institute convened a workshop, Understanding Circadian Mechanisms of Sudden Cardiac Death. We present a 2-part report of findings from this workshop. Part 1 summarizes the workshop and serves to identify research gaps and opportunities in the areas of basic and translational research. Among the gaps was the lack of standardization in animal studies for reporting environmental conditions (eg, timing of experiments relative to the light dark cycle or animal housing temperatures) that can impair rigor and reproducibility. Workshop participants also pointed to uncertainty regarding the importance of maintaining normal circadian rhythmic synchrony and the potential pathological impact of desynchrony on SCD risk. One related question raised was whether circadian mechanisms can be targeted to reduce SCD risk. Finally, the experts underscored the need for studies aimed at determining the physiological importance of circadian clocks in the many different cell types important to normal heart function and SCD. Addressing these gaps could lead to new therapeutic approaches/molecular targets that can mitigate the risk of SCD not only at certain times but over the entire 24-hour period.

Understanding Circadian Mechanisms of Sudden Cardiac Death: A Report From the National Heart, Lung, and Blood Institute Workshop, Part 2: Population and Clinical Considerations.

Sudden cardiac death (SCD) is the sudden, unexpected death due to abrupt loss of heart function secondary to cardiovascular disease. In certain populations living with cardiovascular disease, SCD follows a distinct 24-hour pattern in occurrence, suggesting day/night rhythms in behavior, the environment, and endogenous circadian rhythms result in daily spans of increased vulnerability. The National Heart, Lung, and Blood Institute convened a workshop, Understanding Circadian Mechanisms of Sudden Cardiac Death to identify fundamental questions regarding the role of the circadian rhythms in SCD. Part 2 summarizes research gaps and opportunities in the areas of population and clinical research identified in the workshop. Established research supports a complex interaction between circadian rhythms and physiological responses that increase the risk for SCD. Moreover, these physiological responses themselves are influenced by several biological variables, including the type of cardiovascular disease, sex, age, and genetics, as well as environmental factors. The emergence of new noninvasive biotechnological tools that continuously measure key cardiovascular variables, as well as the identification of biomarkers to assess circadian rhythms, hold promise for generating large-scale human data sets that will delineate which subsets of individuals are most vulnerable to SCD. Additionally, these data will improve our understanding of how people who suffer from circadian disruptions develop cardiovascular diseases that increase the risk for SCD. Emerging strategies to identify new biomarkers that can quantify circadian health (eg, environmental, behavioral, and internal misalignment) may lead to new interventions and therapeutic targets to prevent the progression of cardiovascular diseases that cause SCD.

Translational Models and Tools to Reduce Clinical Trials and Improve Regulatory Decision Making for QTc and Proarrhythmia Risk (ICH E14/S7B Updates).

After multiple drugs were removed from the market secondary to drug-induced torsade de pointes (TdP) risk, the International Council for Harmonisation (ICH) released guidelines in 2005 that focused on the nonclinical (S7B) and clinical (E14) assessment of surrogate biomarkers for TdP. Recently, Vargas et al. published a pharmaceutical-industry perspective making the case that "double-negative" nonclinical data (negative in vitro hERG and in vivo heart-rate corrected QT (QTc) assays) are associated with such low probability of clinical QTc prolongation and TdP that potentially all double-negative drugs would not need detailed clinical QTc evaluation. Subsequently, the ICH released a new E14/S7B Draft Guideline containing Questions and Answers (Q&As) that defined ways that double-negative nonclinical data could be used to reduce the number of "Thorough QT" (TQT) studies and reach a low-risk determination when a TQT or equivalent could not be performed. We review the Vargas et al. proposal in the context of what was contained in the ICH E14/S7B Draft Guideline and what was proposed by the ICH E14/S7B working group for a "stage 2" of updates (potential expanded roles for nonclinical data and details for assessing TdP risk of QTc-prolonging drugs). Although we do not agree with the exact probability statistics in the Vargas et al. paper because of limitations in the underlying datasets, we show how more modest predictive value of individual assays could still result in low probability for TdP with double-negative findings. Furthermore, we expect that the predictive value of the nonclinical assays will improve with implementation of the new ICH E14/S7B Draft Guideline.

Enrichment Benefits of Risk Algorithms for Pulmonary Arterial Hypertension Clinical Trials.

Rationale: Event-driven primary endpoints are increasingly used in pulmonary arterial hypertension clinical trials, substantially increasing required sample sizes and trial lengths. The U.S. Food and Drug Administration advocates the use of prognostic enrichment of clinical trials by preselecting a patient population with increased likelihood of experiencing the trial's primary endpoint.Objectives: This study compares validated clinical scales of risk (Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension, the French score, and Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management [REVEAL] 2.0) to identify patients who are likely to experience a clinical worsening event for trial enrichment.Methods: Baseline data from three pulmonary arterial hypertension clinical trials (AMBITION [a Study of First-Line Ambrisentan and Tadalafil Combination Therapy in Subjects with Pulmonary Arterial Hypertension], SERAPHIN [Study of Macitentan on Morbidity and Mortality in Patients with Symptomatic Pulmonary Arterial Hypertension], and GRIPHON [Selexipag in Pulmonary Arterial Hypertension]) were pooled and standardized. Receiver operating curves were used to measure each algorithm's performance in predicting clinical worsening within the pooled placebo cohort. Power simulations were conducted to determine sample size and treatment time reductions for multiple enrichment strategies. A cost analysis was performed to illustrate potential financial savings by applying enrichment to GRIPHON.Measurements and Main Results: All risk algorithms were compared using area under the receiver operating curve and substantially outperformed prediction per New York Heart Association Functional Class. The REVEAL 2.0's risk grouping provided the greatest time and sample size savings in AMBITION and GRIPHON for all enrichment strategies but lacked appropriate inputs (i.e., N-terminal-proB-type natriuretic peptide) to perform as well in SERAPHIN. Cost analysis applied to GRIPHON demonstrated the greatest financial benefit by enrolling patients with a REVEAL score ≥8.Conclusions: This preliminary study demonstrates the feasibility of risk algorithms for pulmonary arterial hypertension trial enrichment and a need for further investigation.

Detection and impact of hysteresis when evaluating a drug's QTc effect using concentration-QTc analysis.

Early-phase studies quantifying the QTc prolongation potential for a new drug often use linear concentration-QTc (C-QTc) models, assuming no delay between plasma concentrations and QTc changes. However, that assumption is not always correct. The term "hysteresis" has been utilized to describe a time lag present between a measurable concentration and a measurable effect. To detect and quantify hysteresis and its impact on study interpretation, studies with hysteresis of 0.25-4 h were simulated with different doses, half-lives, and sampling schedules in a crossover design. Hysteresis was quantified using a novel method termed exposure-normalized GRI (enGRI), a proposed modification of the Glomb-Ring Index (GRI), to account for delay and magnitude of QTc effects. With realistic sampling, the rate of false negative studies (FN) increased proportionally to the delay, even for delays shorter than 1 h. Using an enGRI threshold (γ) of 2 ms resulted in FN with undetected delay and FN without hysteresis at approximately the same rate. For γ = 2 ms, the specificity of enGRI was > 90% throughout the investigated scenarios. We therefore propose the incorporation of enGRI when interpreting results from C-QTc analysis with the intent of characterizing QTc effects.

Redefining Blood Pressure Assessment - The Role of the Ambulatory Blood Pressure Monitoring Study for Drug Safety.

According to models developed from large epidemiological studies, mean increases in systolic blood pressure of 2-3 mmHg can increase the risk of cardiovascular (CV) adverse events, especially in patients with a high risk for CV disease. There are new regulatory recommendations for the use of a safety ambulatory blood pressure monitoring (ABPM) study to assess the blood pressure (BP) effects of drugs used chronically. The ABPM study collects BP measurements over 24 hours at baseline and during treatment in patients with underlying CV risk. Our evaluation of ABPM studies submitted to the US Food and Drug Administration (FDA) shows these studies can provide precise estimates of BP changes and lack a pronounced placebo response. With the assessment of BP effects in development programs, opportunities exist for developing quantitative safety models to predict CV risk, support dose selection, identify patients with increased BP response, and provide insight into underlying mechanisms.

Heart Rate Correction of the J-to-Tpeak Interval.

Drug-induced changes of the J to T peak (JTp) and J to the median of area under the T wave (JT50) were reported to differentiate QT prolonging drugs that are predominant blockers of the delayed potassium rectifier current from those with multiple ion channel effects. Studies of drug-induced JTp/JT50 interval changes might therefore facilitate cardiac safety evaluation of new pharmaceuticals. It is not known whether formulas for QT heart rate correction are applicable to JTp and JT50 intervals. QT/RR, JTp/RR, and JT50/RR profiles were studied in 523 healthy subjects aged 33.5 ± 8.4 years (254 females). In individual subjects, 1,256 ± 220 electrocardiographic measurements of QT, JTp, and JT50 intervals were available including a 5-minute history of RR intervals preceding each measurement. Curvilinear, linear and log-linear regression models were used to characterize individual QT/RR, JTp/RR, and JT50/RR profiles both without and with correction for heart rate hysteresis. JTp/RR and JT50/RR hysteresis correction needs to be included but the generic universal correction for QT/RR hysteresis is also applicable to JTp/RR and JT50/RR profiles. Once this is incorporated, median regression coefficients of the investigated population suggest linear correction formulas JTpc = JTp + 0.150(1-RR) and JT50c = JT50 + 0.117(1-RR) where RR intervals of the underlying heart rate are hysteresis-corrected, and all measurements expressed in seconds. The established correction formulas can be proposed for future clinical pharmacology studies that show drug-induced heart rate changes of up to approximately 10 beats per minute.

Detection of T Wave Peak for Serial Comparisons of JTp Interval.

Electrocardiogram (ECG) studies of drug-induced prolongation of the interval between the J point and the peak of the T wave (JTp interval) distinguished QT prolonging drugs that predominantly block the delayed potassium rectifier current from those affecting multiple cardiac repolarisation ion channel currents. Since the peak of the T wave depends on ECG lead, a "global" T peak requires to combine ECG leads into one-dimensional signal in which the T wave peak can be measured. This study aimed at finding the optimum one-dimensional representation of 12-lead ECGs for the most stable JTp measurements. Seven different one-dimensional representations were investigated including the vector magnitude of the orthogonal XYZ transformation, root mean square of all 12 ECG leads, and the vector magnitude of the 3 dominant orthogonal leads derived by singular value decomposition. All representations were applied to the median waveforms of 660,657 separate 10-s 12-lead ECGs taken from repeated day-time Holter recordings in 523 healthy subjects aged 33.5 ± 8.4 years (254 women). The JTp measurements were compared with the QT intervals and with the intervals between the J point and the median point of the area under the T wave one-dimensional representation (JT50 intervals) by means of calculating the residuals of the subject-specific curvilinear regression models relating the measured interval to the hysteresis-corrected RR interval of the underlying heart rate. The residuals of the regression models (equal to the intra-subject standard deviations of individually heart rate corrected intervals) expressed intra-subject stability of interval measurements. For both the JTp intervals and the JT50 intervals, the curvilinear regression residuals of measurements derived from the orthogonal XYZ representation were marginally but statistically significantly lower compared to the other representations. Using the XYZ representation, the residuals of the QT/RR, JTp/RR and JT50/RR regressions were 5.6 ± 1.1 ms, 7.2 ± 2.2 ms, and 4.9 ± 1.2 ms, respectively (all statistically significantly different; p < 0.0001). The study concludes that the orthogonal XYZ ECG representation might be proposed for future investigations of JTp and JT50 intervals. If the ability of classifying QT prolonging drugs is further confirmed for the JT50 interval, it might be appropriate to replace the JTp interval since with JT50 it appears more stable.

Errors of Fixed QT Heart Rate Corrections Used in the Assessment of Drug-Induced QTc Changes.

The accuracy of studies of drug-induced QTc changes depends, among others, on the accuracy of heart rate correction of QT interval. It has been recognized that when a drug leads to substantial heart rate changes, fixed universal corrections cannot be used and that alternative methods such as subject-specific corrections established for each study participant need to be considered. Nevertheless, the maximum heart rate change that permits use of fixed correction with reasonable accuracy has not been systematically investigated. We have therefore used full QT/heart-rate profiles of 751 healthy subjects (mean age 34.2 ± 9.6, range 18-61 years, 335 females) and compared their subject-specific corrections with 6 fixed corrections, namely Bazett, Fridericia, Framingham, Hodges, Rautaharju, and Sarma formulae. The comparison was based on statistical modeling experiments which simulated clinical studies of N = 10 or N = 50 female or male subjects. The experiments compared errors of ΔQTc intervals calculated as differences between QTc intervals at an initial heart rate (in the range of 40 to 120 beats per minute, bpm) and after a heart rate change (in the range from -20 to +20 bpm). The experiments also investigated errors due to spontaneous heart rate fluctuation and due to omission of correction for QT/RR hysteresis. In each experiment, the absolute value of the single-sided 90th percentile most remote from zero was used as the error estimate. Each experiment was repeated 10,000 times with random selection of modeled study group. From these repetitions, median and upper 80th percentile was derived and graphically displayed for all different combinations of initial heart rate and heart rate change. The results showed that Fridericia formula might be reasonable (with estimated errors of ΔQTc below 8 ms) in large studies if the heart rate does not change more than ± 10 bpm and that the errors by fixed corrections and the errors due to omission of QR/RR hysteresis are additive. Additionally, the results suggest that the variability introduced into QTc data by not correcting for the underlying heart rate accurately might have a greater impact in smaller studies. The errors by Framingham formula were practically the same as with the Fridericia formula. Other investigated fixed heart rate corrections led to larger ΔQTc errors.

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

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

Correction to: Implications of Individual QT/RR Profiles-Part 1: Inaccuracies and Problems of Population-Specific QT/Heart Rate Corrections.

The Open Access license, which previously read.

Correction to: Implications of Individual QT/RR Profiles-Part 2: Zero QTc/RR Correlations Do Not Prove QTc Correction Accuracy in Studies of QTc Changes.

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License which permits unrestricted use.

Implications of Individual QT/RR Profiles-Part 2: Zero QTc/RR Correlations Do Not Prove QTc Correction Accuracy in Studies of QTc Changes.

INTRODUCTION: In studies of drug-induced corrected QT (QTc) changes, fixed universal heart rate (HR) corrections (e.g., the Fridericia correction) are potentially misleading when assessing the effects of drugs that change HR. When data-specific corrections are designed, tests of their validity are needed. The proposed tests include zero correlations between QTc and corresponding RR values in the complete study data (pooling on-treatment and off-treatment interval measurements). OBJECTIVE: To document that this approach is potentially highly misleading, a statistical modeling study was conducted based on the full profiles of QT/RR data of 523 healthy subjects-254 females, mean age 33.5 years. METHODS: In each of the subjects, 50 baseline QT/RR readings were selected to model baseline data. In repeated experiments, groups of ten and 50 subjects were randomly selected and drug-induced HR increases between 0 and 25 beats per minute combined with QTc changes between - 20 and + 20 ms were modeled. In each experiment, subject-specific as well as population-specific HR corrections were designed so that the QTc interval data were uncorrelated to the corresponding RR interval data. RESULTS: The simulation experiments showed that when zero correlations of QTc data with RR data are combined with more than trivial HR increases, the HR corrections are substantially biased and underestimate or fully eliminate any drug-induced QTc interval changes. This result is in full agreement with theoretical considerations of HR correction principles. CONCLUSIONS: The lack of correlation of QTc versus RR durations including on-treatment data does not prove any validity of HR corrections. Correlations of QTc versus RR in study data pooling on- and off-drug measurements should not be used to prove the appropriateness of HR corrections.

Implications of Individual QT/RR Profiles-Part 1: Inaccuracies and Problems of Population-Specific QT/Heart Rate Corrections.

INTRODUCTION: Universal QT correction formulas are potentially problematic in corrected QT (QTc) interval comparisons at different heart rates. Instead of individual-specific corrections, population-specific corrections are occasionally used based on QT/RR data pooled from all study subjects. OBJECTIVE: To investigate the performance of individual-specific and population-specific corrections, a statistical modeling study was performed using QT/RR data of 523 healthy subjects. METHODS: In each subject, full drug-free QT/RR profiles were available, characterized using non-linear regression models. In each subject, 50 baseline QT/RR readings represented baseline data of standard QT studies. Using these data, linear and log-linear heart rate corrections were optimized for each subject and for different groups of ten and 50 subjects. These corrections were applied in random combinations of heart rate changes between - 10 and + 25 beats per minute (bpm) and known QTc interval changes between - 25 and + 25 ms. RESULTS: Both the subject-specific and population-specific corrections based on the 50 baseline QT/RR readings tended to underestimate/overestimate the QTc interval changes when heart rate was increasing/decreasing, respectively. The result spread was much wider with population-specific corrections, making the estimates of QTc interval changes practically unpredictable. CONCLUSION: Subject-specific heart rate corrections based on limited baseline drug-free data may lead to inconsistent results and, in the presence of underlying heart rate changes, may potentially underestimate or overestimate QTc interval changes. The population-specific corrections lead to results that are much more influenced by the combination of individual QT/RR patterns than by the actual QTc interval changes. Subject-specific heart rate corrections based on full profiles derived from drug-free baseline recordings with wide QT/RR distribution should be used when studying drugs expected to cause heart rate changes.

Assessment of Multi-Ion Channel Block in a Phase I Randomized Study Design: Results of the CiPA Phase I ECG Biomarker Validation Study.

Balanced multi-ion channel-blocking drugs have low torsade risk because they block inward currents. The Comprehensive In Vitro Proarrhythmia Assay (CiPA) initiative proposes to use an in silico cardiomyocyte model to determine the presence of balanced block, and absence of heart rate corrected J-Tpeak (J-Tpeak c) prolongation would be expected for balanced blockers. This study included three balanced blockers in a 10-subject-per-drug parallel design; lopinavir/ritonavir and verapamil met the primary end point of ΔΔJ-Tpeak c upper bound < 10 ms, whereas ranolazine did not (upper bounds of 8.8, 6.1, and 12.0 ms, respectively). Chloroquine, a predominant blocker of the potassium channel encoded by the ether-à-go-go related gene (hERG), prolonged ΔΔQTc and ΔΔJ-Tpeak c by ≥ 10 ms. In a separate crossover design, diltiazem (calcium block) did not shorten dofetilide-induced ΔQTc prolongation, but shortened ΔJ-Tpeak c and prolonged ΔTpeak -Tend . Absence of J-Tpeak c prolongation seems consistent with balanced block; however, small sample size (10 subjects) may be insufficient to characterize concentration-response in some cases.