Why the study?
Regulatory guidance on the in vivo QTc assay lacks recommendations on study execution or quality, leading to variable study designs and experimental approaches in nonclinical assessments.
A double Latin square cross-over design with N=8 provides consistent and reproducible sensitivity for in vivo QTc assessment in dogs and NHPs, supporting nonclinical pro-arrhythmia risk evaluation.
Consistent nonclinical QTc protocols support reproducible signal detection; leaves open optimal standards for human risk assessment.
(hERG) and in vivo QTc assay for human risk assessment of new drug products, but the guidance is devoid of recommendations on study execution or quality. In the absence of standard practice, multiple study designs and experimental approaches have been utilized, especially with the nonclinical QTc assay. Since 2009, our approach to the in vivo QTc assay has been consistent for small molecules and yields reproducible and sensitive levels for QTc signal detection. Our database and experience indicate that nonrodent telemetry studies can achieve high sensitivity and a calculated metric of study power can be used to indicate study quality. Using a retrospective statistical power analysis of multiple studies (n = 14 dog; n = 6 NHP), the detection sensitivity for a specific study design (N = 8; double Latin square cross-over) was determined. The output of the power analysis is the minimal detectable effect at 80% power and a 95% probability level. The design provided an average sensitivity to detect a 4.7 (2.0%) and 6.5 (1.9%) msec QTcI change in dog and NHP, respectively. These findings suggest that this experimental approach has a consistent and reproducible sensitivity to enable a robust QTcI risk evaluation and can be used confidently to support an integrated nonclinical-clinical pro-arrhythmia risk assessment. The inclusion of power analysis (i.e., QTc sensitivity) data in a regulatory submission provides key information to critical stakeholders about the quality of the in vivo QTc assessment and its value for human safety testing.
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Baublits et al. (2021) studied this question.
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