A Computational Model to Predict the Effects of Class I Anti-Arrhythmic Drugs on Ventricular Rhythms

Abstract

A long-sought, and thus far elusive, goal has been to develop drugs to manage diseases of excitability. One such disease that affects millions each year is cardiac arrhythmia, which occurs when electrical impulses in the heart become disordered, sometimes causing sudden death. Pharmacological management of cardiac arrhythmia has failed because it is not possible to predict how drugs that target cardiac ion channels, and have intrinsically complex dynamic interactions with ion channels, will alter the emergent electrical behavior generated in the heart. Here, we applied a computational model, which was informed and validated by experimental data, that defined key measurable parameters necessary to simulate the interaction kinetics of the anti-arrhythmic drugs flecainide and lidocaine with cardiac sodium channels. We then used the model to predict the effects of these drugs on normal human ventricular cellular and tissue electrical activity in the setting of a common arrhythmia trigger, spontaneous ventricular ectopy. The model forecasts the clinically relevant concentrations at which flecainide and lidocaine exacerbate, rather than ameliorate, arrhythmia. Experiments in rabbit hearts and simulations in human ventricles based on magnetic resonance images validated the model predictions. This computational framework initiates the first steps toward development of a virtual drug-screening system that models drug-channel interactions and predicts the effects of drugs on emergent electrical activity in the heart.

Induced pluripotent stem cells used to reveal drug actions in a long QT syndrome family with complex genetics

“…impact of adding a second Na + channel blocker, flecainide, two clinical options frequently used empirically to treat LQTS-3. We first studied the effect of pulse frequency (heart rate) on I NaL in iPSC-CMs from the proband and parents because for some (Clancy et al, 2002), but not all, LQT-3 (Bankston et al, 2007a) mutants, heart rate (pulse frequency) alone can be a potent modifier of I NaL and late current block by drugs such as mexiletine, and flecainide is use dependent and increases with increased stimulation rate (Moreno et al, 2011). We found I NaL expressed in proband iPSC-CMs was very sensitive to the stimulation rate.…”

Molecular motions that shape the cardiac action potential: Insights from voltage clamp fluorometry

“…For example, traditional, HodgkineHuxley type, models imply that each of the channel "gates" must be open before the channel is able to conduct ionic current. This requirement has persisted to date, even in modern Markov type models that simulate complex drug interactions (Moreno et al, 2011). In contrast, the above DII-VSD results imply that the Na V 1.5 pore may open even if the DII-VSD gate remains in the resting conformation, which would require an allosteric model.…”

Population-Based Mechanistic Modeling Allows for Quantitative Predictions of Drug Responses across Cell Types

“…These complexities could be included through the use of more complex Markov models, which have been developed for many critical channels. [46][47][48] For these predictions to be accurate, however, the same kinetic scheme and drug binding characteristics would have to be used in both the source and target cell models, which is not generally the case at present. Second, although the regression model performed extremely well with simulated data, the experimental validity of these predictions remains to be tested.…”