Exposure-response (ER) modelling (concentration-QTc analysis) is gaining as much acceptance as the traditional by-time analysis of the placebo-adjusted change from baseline in the QTc interval (ΔΔQTcF). It has been postulated that intensive ECG analysis and ER modelling during early-phase drug development could be a cost-effective approach of estimating QT liability of a new drug, in a small number of subjects. We used a highly automated analysis of ECGs from 46 subjects from a crossover thorough QT/QTc study to detect ΔΔQTcF with moxifloxacin. Using these data, we also simulated (bootstrapped) 1000 datasets of a parallel study with eight subjects receiving moxifloxacin and eight others receiving placebo. The slope from the concentration-QTc analysis for moxifloxacin in 46 subjects was 4.12ms of ΔΔQTcF per μg(-1) mL(-1) ; at mean Cmax of 2.95μg·mL(-1) , estimated ΔΔQTcF was 13.4ms (90% confidence interval 11.3, 15.4ms). In the 1000 simulated datasets, in 996 datasets, ER modelling showed that the upper bound of the 90% confidence interval for ΔΔQTcF at geometric mean Cmax exceeded 10ms. In 895 of these 996 datasets, the slope of the ER relationship was statistically significantly positive. Thus, with a small sample size (eight subjects on active drug and eight on placebo), moxifloxacin-induced QTc prolongation was demonstrated using ER analysis with statistical power of >80%. Our study adds to the growing body of data supporting intensive ECG collection and analysis in early-phase studies to estimate QT liability.