title: 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.
authors: Tri-Institutional MD-PhD Program, Weill Cornell Medical College/The Rockefeller University/Sloan-Kettering Cancer Institute, New York, NY 10021, USA.
authors: Jonathan D
authors: JD
authors: Moreno
authors: Z Iris
authors: ZI
authors: Zhu
authors: Pei-Chi
authors: PC
authors: Yang
authors: John R
authors: JR
authors: Bankston
authors: Mao-Tsuen
authors: MT
authors: Jeng
authors: Chaoyi
authors: C
authors: Kang
authors: Lianguo
authors: L
authors: Wang
authors: Jason D
authors: JD
authors: Bayer
authors: David J
authors: DJ
authors: Christini
authors: Natalia A
authors: NA
authors: Trayanova
authors: Crystal M
authors: CM
authors: Ripplinger
authors: Robert S
authors: RS
authors: Kass
authors: Colleen E
authors: CE
authors: Clancy
mesh_terms: D000818:Animals; D000889:Anti-Arrhythmia Agents / Q000627:therapeutic use*; D001145:Arrhythmias, Cardiac / Q000188:drug therapy* / Q000503:physiopathology; D003198:Computer Simulation; D005424:Flecainide / Q000494:pharmacology; D006329:Heart Conduction System / Q000187:drug effects / Q000503:physiopathology; D006333:Heart Failure / Q000188:drug therapy; D006352:Heart Ventricles / Q000187:drug effects* / Q000473:pathology* / Q000503:physiopathology; D006801:Humans; D007700:Kinetics; D008012:Lidocaine / Q000494:pharmacology; D008955:Models, Cardiovascular; D011817:Rabbits; D015203:Reproducibility of Results; D015222:Sodium Channels / Q000378:metabolism
chemical_list: D000889:Anti-Arrhythmia Agents; D015222:Sodium Channels; D008012:Lidocaine; D005424:Flecainide