Impact of disease state on arrhythmic event detection by action potential modelling in cardiac safety pharmacology

Abstract

IntroductionThe use of in silico cardiac action potential simulations is one of the pillars of the CiPA initiative (Comprehensive in vitro Proarrhythmia Assay) currently under evaluation designed to detect more accurately proarrhythmic liabilities of new drug candidate. In order to take into account the variability of clinical situations, we propose to improve this method by studying the impact of various disease states on arrhythmic events induced by 30 torsadogenic or non-torsadogenic compounds. MethodIn silico modelling was done on the human myocytes using the Dutta revised O'Hara-Rudy algorithm. Results were analysed using a new metric based on the compound IC50s against the seven cardiac ionic currents considered to be the most important by the CiPA initiative (IKr, IKs, INa, INaL, IK1, Ito, ICaL) and the minimal rate of action potential voltage decrease calculated at the early-afterdepolarization (EAD) take-off membrane voltage (Vmin). ResultsThe specific threshold at which each torsadogenic compounds induced EAD, was exacerbated by the presence of cardiac risk factors ranked as follows: congestive heart failure > hypertrophic cardiomyopathy > cardiac pause > no risk factor. Non-torsadogenic compounds induced no EAD even in the presence of cardiac risk factors. DiscussionThe present study highlighted the impact of pre-existing cardiovascular disease on arrhythmic event detection suggesting that disease state modelling may need to be incorporated in order to fully realize the goal of the CiPA paradigm in a more accurate predictability of proarrhythmic liabilities of new drug candidate.