Magnitude of error introduced by application of heart rate correction formulas to the canine QT interval

Best practice considerations for nonclinical in vivo cardiovascular telemetry studies in non-rodent species: Delivering high quality QTc data to support ICH E14/S7B Q&As

The ICH E14/S7B Questions and Answers (Q&As) guideline introduces the concept of a "double negative" nonclinical scenario (negative hERG assay and negative in vivo QTc study) to demonstrate that a drug does not produce a clinically relevant QT prolongation (i.e., no QT liability). This nonclinical "double negative" data package, along with negative Phase 1 clinical QTc data, may be sufficient to substitute for a clinical Thorough QT (TQT) study in some specific cases. While standalone GLP in vivo cardiovascular studies in non-rodent species are standard practice during nonclinical drug development for small molecule programs, a variety of approaches to the design, conduct, analysis and interpretation are utilized across pharmaceutical companies and contract research organizations (CROs) that may, in some cases, negatively impact the stringent sensitivity needed to fulfill the new Q&As. Subject matter experts from both Pharma and CROs have collaborated to recommend best practices for more robust nonclinical cardiovascular telemetry studies in non-rodent species, with input from clinical and regulatory experts. The aim was to increase consistency and harmonization across the industry and to ensure delivery of high quality nonclinical QTc data to meet the proposed sensitivities defined within the revised ICH E14/S7B Q&As guideline (Q&As 5.1 and 6.1). The detailed best practice recommendations presented here cover the design and execution of the safety pharmacology cardiovascular study, including optimal methods for acquiring, analyzing, reporting, and interpreting the resulting QTc and pharmacokinetic data to allow for direct comparison to clinical exposures and assessment of safety margin for QTc prolongation.

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.

QT interval in healthy dogs: which method of correcting the QT interval in dogs is appropriate for use in small animal clinics?

The electrocardiography (ECG) QT interval is influenced by fluctuations in heart rate (HR) what may lead to misinterpretation of its length. Considering that alterations in QT interval length reflect abnormalities of the ventricular repolarisation which predispose to occurrence of arrhythmias, this variable must be properly evaluated. The aim of this work is to determine which method of correcting the QT interval is the most appropriate for dogs regarding different ranges of normal HR (different breeds). Healthy adult dogs (n=130; German Shepherd, Boxer, Pit Bull Terrier, and Poodle) were submitted to ECG examination and QT intervals were determined in triplicates from the bipolar limb II lead and corrected for the effects of HR through the application of three published formulae involving quadratic, cubic or linear regression. The mean corrected QT values (QTc) obtained using the diverse formulae were significantly different (ρ<0.05), while those derived according to the equation QTcV = QT + 0.087(1- RR) were the most consistent (linear regression). QTcV values were strongly correlated (r=0.83) with the QT interval and showed a coefficient of variation of 8.37% and a 95% confidence interval of 0.22-0.23 s. Owing to its simplicity and reliability, the QTcV was considered the most appropriate to be used for the correction of QT interval in dogs.

Interferences of the autonomic nervous system with drug induced QT prolongation: a point to consider in non-clinical safety studies

INTRODUCTION

QT interval assessment by telemetry has become one of the most useful models in testing strategies adopted for detection of drug induced QT prolongation in non-clinical safety pharmacology studies. This study reports experimental data showing that the autonomic nervous system might influence drug induced QT prolongation.

METHODS

Animals were instrumented with telemetric transmitters and epicardial ECG leads. Effects on QT interval of reference drugs such as thioridazine and terfenadine were analysed with different approaches, the Holzgrefe's probabilistic method, the QT shift method and an individual analysis of beat-to-beat QT/RR pair distribution visualised as points-cloud.

RESULTS

Two cases of unexpected absence of QT interval prolongation are reported with thioridazine and terfenadine in conscious beagle dogs under conditions of concomitant tachycardia. The pro-arrhythmic properties of these two molecules were unmasked by co-treatment with sympatholytic agents, atenolol and clonidine respectively suggesting that sympathetic activation and/or parasympathetic withdrawal might impair a drug induced QT prolongation.

DISCUSSION

The apparent absence of changes in the QT interval due to novel drug candidates should be interpreted cautiously under conditions of concomitant tachycardia or elevated heart rate levels in non-clinical safety studies.

The effect of changes in core body temperature on the QT interval in beagle dogs: a previously ignored phenomenon, with a method for correction

Background and purpose:

Body core temperature (Tc) changes affect the QT interval, but correction for this has not been systematically investigated. It may be important to correct QT intervals for drug-induced changes in Tc.

Experimental approach:

Anaesthetized beagle dogs were artificially cooled (34.2 °C) or warmed (42.1 °C). The relationship between corrected QT intervals (QTcV; QT interval corrected according to the Van de Water formula) and Tc was analysed. This relationship was also examined in conscious dogs where Tc was increased by exercise.

Key results:

When QTcV intervals were plotted against changes in Tc, linear correlations were observed in all individual dogs. The slopes did not significantly differ between cooling (−14.85±2.08) or heating (−13.12±3.46) protocols. We propose a correction formula to compensate for the influence of Tc changes and standardize the QTcV duration to 37.5 °C: QTcVcT (QTcV corrected for changes in core temperature)=QTcV–14 (37.5 – Tc). Furthermore, cooled dogs were re-warmed (from 34.2 to 40.0 °C) and marked QTcV shortening (−29%) was induced. After Tc correction, using the above formula, this decrease was abolished. In these re-warmed dogs, we observed significant increases in T-wave amplitude and in serum [K⁺] levels. No arrhythmias or increase in pro-arrhythmic biomarkers were observed. In exercising dogs, the above formula completely compensated QTcV for the temperature increase.

Conclusions and implications:

This study shows the importance of correcting QTcV intervals for changes in Tc, to avoid misleading interpretations of apparent QTcV interval changes. We recommend that all ICH S7A, conscious animal safety studies should routinely measure core body temperature and correct QTcV appropriately, if body temperature and heart rate changes are observed.

ILSI–HESI cardiovascular safety subcommittee dataset: An analysis of the statistical properties of QT interval and rate-corrected QT interval (QTc)

INTRODUCTION

The Health and Environmental Sciences Institute of the International Life Sciences Institute (ILSI/HESI) Cardiovascular Safety Subcommittee outlined a set of in vivo telemetry studies to determine how well this preclinical model identified compounds known to cause torsades de pointes (TdP) and prolong QT interval in humans. In the original analysis of these data, QT, QTcB (Bazett model), QTcF (Fridericia model), and QTcQ (animal-specific model) were evaluated. We further evaluate the statistical properties of these measurements, using a method that can properly account for the sources of variability in the dataset.

METHODS

The ILSI/HESI telemetry studies were conducted as a double Latin square design where eight dogs each received a vehicle control and three dose levels of a compound on four separate dosing days. We statistically analyzed the QT/QTc intervals using a repeated measures analysis of covariance and evaluate the powers for QT, QTcF and QTcQ based on simulations.

RESULTS

The analyses for QTcF and QTcB intervals show that all six compounds which were known to cause TdP in humans were identified as positive and all six compounds known to be free of TdP events in their clinical use had no statistically significant treatment-related effects, while the analyses for QTcQ identified all positive compounds except pimozide. The power analysis shows that the method can detect a 7% increment of QT, a 5% increment of QTcF, and a 4% increment of QTcQ, with greater than 80% of power when n=8.

DISCUSSION

We describe a repeated measures procedure to perform statistical analysis of covariance on Latin square designs and show that it can be used to detect meaningful changes in the analysis of QT/QTc intervals.