Assessing the probability of drug-induced QTc-interval prolongation during clinical drug development.

Early in the course of clinical development of new non-antiarrhythmic drugs, it is important to assess the propensity of these drugs to prolong the QT/QTc-interval. The current regulatory guidelines suggest using the largest time-matched mean difference between drug and placebo (baseline-adjusted) groups over the sampling interval, thereby neglecting any potential exposure-effect relationship and nonlinearity in the underlying physiological fluctuation in QT values. Thus far, most of the attempted models for characterizing drug-induced QTc-interval prolongation have disregarded the possibility of model parameterization in terms of drug-specific and system-specific properties. Using a database consisting of three compounds with known dromotropic activity, we built a bayesian hierarchical pharmacodynamic (PD) model to describe QT interval, encompassing an individual correction factor for heart rate, an oscillatory component describing the circadian variation, and a truncated maximum-effect model to account for drug effect. The explicit description of the exposure-effect relationship, incorporating various sources of variability, offers advantages over the standard regulatory approach.