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Abnormalities in repolarization and its rate dependence are known to related to increased proarrhythmic risk. A number of repolarization-related electrophysiological properties are commonly used as preclinical biomarkers of arrhythmic risk. However, the variability and complexity of repolarization mechanisms make the use of cellular biomarkers to predict arrhythmic risk preclinically challenging. Our goal is to investigate the role of ionic current properties and their variability in modulating cellular biomarkers of arrhythmic risk to improve risk stratification and identification in humans. A systematic investigation into the sensitivity of the main preclinical biomarkers of arrhythmic risk to changes in ionic current conductances and kinetics was performed using computer simulations. Four stimulation protocols were applied to the ten Tusscher and Panfilov human ventricular model to quantify the impact of [+ or -] 15 and [+ or -] 30% variations in key model parameters on action potential (AP) properties, [Ca.sup.2+] and [Na.sup.+] dynamics, and their rate dependence. Simulations show that, in humans, AP duration is moderately sensitive to changes in all repolarization current conductances and in L-type [Ca.sup.2+] current ([I.sub.CaL]) and slow component of the delayed rectifier current ([I.sub.Ks]) inactivation kinetics. AP triangulation, however, is strongly dependent only on inward rectifier [K.sup.+] current ([I.sub.KI]) and delayed rectifier current ([I.sub.Kr]) conductances. Furthermore, AP rate dependence (i.e., AP duration rate adaptation and restitution properties) and intracellular [Ca.sup.2+] and [Na.sup.+] levels are highly sensitive to both [I.sub.CaL] and [Na.sup.+]/[K.sup.+] pump current ([I.sub.NaK]) properties. This study provides quantitative insights into the sensitivity of preclinical biomarkers of arrhythmic risk to variations in ionic current properties in humans. The results show the importance of sensitivity analysis as a powerful method for the in-depth validation of mathematical models in cardiac electrophysiology. biological variability: arrhytbmia: computer simulation doi:10.1152/ajpheart.00263.2009