Optimized J to T peak and T peak to T end measurements in nonclinical species administered moxifloxacin and amiodarone.

INTRODUCTION: Cardiovascular safety and the risk of developing the potentially fatal ventricular tachyarrhythmia, Torsades de Pointes (TdP), have long been major concerns of drug development. TdP is associated with a delayed ventricular repolarization represented by QT interval prolongation in the electrocardiogram (ECG), typically due to block of the potassium channel encoded by the human ether-a-go-go related gene (hERG). Importantly however, not all drugs that prolong the QT interval are torsadagenic and not all hERG blockers prolong the QT interval. Recent clinical reports suggest that partitioning the QT interval into early (J to T peak; JTp) and late repolarization (T peak to T end; TpTe) components may be valuable for distinguishing low-risk mixed ion channel blockers (hERG plus calcium and/or late sodium currents) from high-risk pure hERG channel blockers. This strategy, if true for nonclinical animal models, could be used to de-risk QT prolonging compounds earlier in the drug development process. METHODS: To explore this, we investigated JTp and TpTe in ECG data collected from telemetered dogs and/or monkeys administered moxifloxacin or amiodarone at doses targeting relevant clinical exposures. An optimized placement of the Tpeak fiducial mark was utilized, and all intervals were corrected for heart rate (QTc, JTpc, TpTec). RESULTS: Increases in QTc and JTpc intervals with administration of the pure hERG blocker moxifloxacin and an initial QTc and JTpc shortening followed by prolongation with the mixed ion channel blocker amiodarone were detected as expected, aligning with clinical data. However, anticipated increases in TpTec by both standard agents were not detected. DISCUSSION: The inability to detect changes in TpTec reduces the utility of these subintervals for prediction of arrhythmias using continuous single­lead ECGs collected from freely moving dogs and monkeys.

A method for assessing and monitoring consistency of nonclinical ECG analysis.

Cardiovascular safety is a key area of concern for new drugs in development, and the collection and analysis of electrocardiograms (ECGs) is a standard and major component of nonclinical testing. Digital data capture technology allows for high-throughput and long-duration ECG collections, resulting in large volumes of data. Consistent analysis of these ECG data is critical for detecting meaningful changes during nonclinical drug development. We developed a method to assess the consistency of nonclinical ECG analysis for a group of analysts over time. Eight­lead ECGs were collected from conscious dogs using Ponemah (v5.2, DSI). Analysts placed Pstart, Qstart, Rpeak, Send, and Tend marks on six waveforms for each animal. The ECG files were randomized and re-marked under blinded conditions 4 to 14 days following initial mark placement. Averages of each parameter measured (RR interval, QRS duration, PR interval, and QT interval) were compiled for each marking session and analyst. A Gage R&R evaluation was completed. Graphical output from the Gage R&R evaluation showed distinct variability on group and individual analyst levels. Differences in inter- and intra-analyst variability (reproducibility and repeatability, respectively) were observed between trained analysts and analysts in training. The Gage R&R method is an effective tool for assessing consistency of digital ECG mark placement at a group level. Furthermore, it is able to identify areas of improvement for individual ECG analysts and to assess ECG analyst consistency during their training period. The assessment results are useful for facilitating discussions on best practices and maintaining consistency of mark placement.