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J Pharmacol Toxicol Methods. 2006 Mar-Apr;53(2):174-83. Epub 2005 Sep 1.

Pharmacokinetic-pharmacodynamic modeling of drug-induced effect on the QT interval in conscious telemetered dogs.

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  • 1AstraZeneca R&D Södertälje, SE-151 85 Södertälje, Sweden.



To assure drug safety, the investigation of the relationship between plasma concentration and drug-induced prolongation of the QT interval of the ECG is a challenge in drug discovery. For this purpose, dofetilide was utilized to demonstrate the benefits of characterizing the complete time course of concentrations and effect in conscious beagle dogs in the assessment of drug safety.


On two separate occasions, four male and two female beagle dogs were given vehicle or the test substance, dofetilide (0.25 mumol/kg), over a 3-h intravenous infusion. Cardiovascular parameters, including QT intervals, were recorded for 24-h using radiotelemetry. The QT interval was corrected individually for heart rate, vehicle treatment, and serial correlation (QT(c)). Exposure (plasma concentration) to dofetilide was measured and described by a two-compartment model. The individual concentration-time course of dofetilide was linked to the QT(c) interval via an effect compartment and a pharmacodynamic E(max) model, to account for the observed hysteresis.


Dofetilide induced a concentration-dependent increase in the QT(c) interval, with an EC(50) of 9 nM (3-30 nM, 95% C.I.) and an E(max) of 59+/-9 ms. A hysteresis loop was observed by plotting plasma concentrations vs. QT interval in time order, indicating a delay in onset of effect. It was found to have an equilibrium half-life of 11+/-8 min. Based on the parameters potency and E(max), a representation was made of the drug-induced changes to the QT interval.


An effect compartment model was found to accurately mimic the QT interval prolongation following administration of the test substance, dofetilide. The assessment of the individual concentration-effect relationship and confounding factors such as hysteresis might provide a better prediction of the safety profiles of new drug candidates.

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