QT interval correction on measured ECGs is an important issue for pharmaceutical research on the way to new drugs. Pharmaceutical industries have to thoroughly investigate potential effects of their drugs on QT intervals since QT pro- longation is considered as a marker of the proarrhythmia risk. As QT interval depends on RR interval there is an obvious in- terest in modeling the QT-RR relationship. Static formulas to correct QT for RR are well known, but a dynamic dependency is also observed. Two models of dynamic QT-RR relationships are introduced to eliminate the heart rate dependent part out of the QT interval. These models are based on heart cell measure- ments and simulations and are validated by Holter ECG data.