Key clinical considerations for demonstrating the utility of preclinical models to predict clinical drug-induced torsades de pointes.
While the QT/QTc interval is currently the best available clinical surrogate for the development of drug-induced torsades de pointes, it is overall an imperfect biomarker. In addition to low specificity for predicting arrhythmias, other issues relevant to using QT as a biomarker include (1) an apparent dissociation, for some drugs (for example, amiodarone, sodium pentobarbital, ranolazine) between QT/QTc interval prolongation and TdP risk, (2) Lack of clarity regarding what determines the relationship between QTc prolongation and TdP risk for an individual drug, (3) QT measurement issues, including effects of heart rate and autonomic perturbations, (4) the significant circadian changes to the QT/QTc interval and (5) concerns that the development, regulatory and commercial implications of finding even a mild QT prolongation effect during clinical development has significant impact the pharmaceutical discovery pipeline. These issues would be significantly reduced, clinical development simplified and marketing approval for some drugs might be accelerated if there were a battery of preclinical tests that could reliably predict a drug's propensity to cause TdP in humans, even in the presence of QTc interval prolongation. This approach is challenging and for it to be acceptable to pharmaceutical developers, the scientific community and regulators, it would need to be scientifically well validated. A very high-negative predictive value demonstrated in a wide range of drugs with different ionic effects would be critical. This manuscript explores the issues surrounding the use of QT as a clinical biomarker and potential approaches for validating preclinical assays for this purpose against clinical data sets.
Cardiovascular Research, CardioDx Inc, Palo Alto, CA 94303, USA. PSager@CardioDx.com
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D000818:Animals; D015415:Biomarkers; D054849:Cardiac Electrophysiology / Q000379:methods; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D004562:Electrocardiography; D006801:Humans; D018570:Risk Assessment / Q000379:methods; D016171:Torsades de Pointes / Q000139:chemically induced*; D018675:Toxicity Tests / Q000379:methods
D015415:Biomarkers