Assessing the risk of a drug candidate inducing arrhythmia is a vital step in the drug development process. Due to the difficulty of directly assessing these potential arrhythmias, researchers rely on QT interval prolongation as a biomarker for arrhythmia risk. The QT interval relates to the time it takes for the ventricles of the heart to contract and recover, as measured by an ECG. Prolonging this time can disrupt the rhythm of the heart and lead to an arrhythmia. To assess the risk of QT prolongation from a drug, researchers must first correct for the influence heart rate has on the interval. This is done using QT correction methods that often ignore changes in the relationship between QT and heart rate over time or between individuals. These changes to relationship are represented in the attached figure by the different slopes of the relationship. This project used bootstrap sampling of ECG recording from non-human primates and canines to simulate thousands of ECG recordings. These were then used to compare the results of multiple QT correction methods, including some novel ones that account for differences between environmental light status. The results showed that the corrected QT values can have reduced variability and heart rate influence when  correction methods consider additional variables, such as subject specific, date specific, or environment specific differences.

Client: Nicholas Ether (Ph.D. Candidate, Pharmacology and Toxicology)

CSTAT collaborators: Sanket Jantre and Dhruv Sharma