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Colleen E. Clancy, PhD
Sex, Drugs, and Funky Rhythms in Silico
Associate Professor, Pharmacology, University of California, Davis
2 Riverside Circle, Roanoke, VA 24016
A long-sought goal has been to develop drugs to manage diseases of excitability. One such disease is cardiac arrhythmia, which occurs when electrical impulses in the heart become disordered. A primary reason that pharmacological management of cardiac arrhythmia has failed is because there is currently no way to predict how ion-channel-blocking drugs with intrinsically complex properties, active metabolites, and off-target effects will alter emergent electrical behavior generated in the heart.
To begin to bridge this gap, we have begun to develop a novel computationally based framework by constructing detailed mathematical models of the interactions between common antiarrhythmic drugs and their targets. These models are then incorporated into virtual human cells and tissues to predict effects of clinically relevant concentrations in the setting of common arrhythmia triggers. The model was also used to predict how sex-based differences can affect drug-induced arrhythmia and revealed specific activation sequences where clinically relevant concentrations of antiarrhythmic drugs will prevent or cause arrhythmia. Experiments in mammalian cells and tissues were used to validate the model predictions.
The results presented derive from an interdisciplinary approach combining experiments, computational biology, high performance computing, and clinical observation intended to determine situations when drugs intended to treat cardiac arrhythmia will succeed or fail. The computational approach also allowed revelation of the specific players in the complex interactions underlying observed behaviors.