Comparison of in silico predictions of action potential duration in response to inhibition of IKr and ICaL with new human ex vivo recordings.

During drug development, candidate compounds are extensively tested for proarrhythmic risk and in particular risk of Torsade de Pointes (TdP), as indicated by prolongation of the QT interval. Drugs that inhibit the rapid delayed rectifier [Formula: see text] current ([Formula: see text]) can prolong the action potential duration (APD) and thereby the QT interval, and so are routinely rejected. However, simultaneous inhibition of the L-type [Formula: see text] current ([Formula: see text]) can mitigate the effect of [Formula: see text] inhibition, so that including both effects can improve test specificity. Mathematical models of the action potential (AP) can be used to predict the APD prolongation resulting from a given level of [Formula: see text] and [Formula: see text] inhibition, but for use in safety-testing their predictive capabilities should first be carefully verified. We present the first systematic comparison between experimental drug-induced APD and predictions by AP models. New experimental data were obtained ex vivo for APD response to [Formula: see text] and/or [Formula: see text] inhibition by applying 9 compounds at different concentrations to adult human ventricular trabeculae at physiological temperature. Compounds with similar effects on [Formula: see text] and [Formula: see text] exhibited less APD prolongation compared to selective [Formula: see text] inhibitors. We then integrated in vitro [Formula: see text] patch-clamp data for [Formula: see text] and [Formula: see text] inhibition by the tested compounds into simulations with AP models. Models were assessed against the ex vivo data on their ability to recapitulate drug-induced APD changes observed experimentally. None of the tested AP models reproduced the APD changes observed experimentally across all combinations and degrees of [Formula: see text] and/or [Formula: see text] inhibition: they matched the data either for selective [Formula: see text] inhibitors or for compounds with comparable effects on [Formula: see text] and [Formula: see text]. This work introduces a new benchmarking framework to assess the predictivity of current and future AP models for APD response to [Formula: see text] and/or [Formula: see text] inhibition. This is an essential primary step towards an in silico framework that integrates in vitro data for translational clinical cardiac safety.