Jacques Beaumont’s work could point the way to a medication or device to aid patients with cardiac arrhythmia, which affects at least 1 in 2,500 people. Experts do not understand what makes a myocardial infarction, or heart attack, fatal to some patients with this condition and not to others. For now, most patients with arrhythmia — an irregular heartbeat — receive an implantable cardiac defibrillator. Medications work well for some but not others.

In the particular condition that Beaumont studies, inherited arrhythmia, scientists know that some three dozen proteins play a role in the defect. Simulation enables Beaumont to test potential procedures in a model pig’s heart before attempting to extrapolate the results for the human heart.

“Naturally, you cannot do experiments in the human heart,” says Beaumont, an associate professor of bioengineering at Binghamton University. “An animal model is not the same as a human’s, but the animals that are closest are the pig and the dog. What we try to do is take advantage of the data gathered from an animal model. We can build a simulation that parallels the animal model and then validate that our procedure works.”

Beaumont creates visual models with underlying mathematical models in his search for the mechanism of arrhythmia. He hopes to link the molecular aspect of cellular excitation to the phenomenon at the microscopic level. The simulation doesn’t yet include the application of possible therapies, though that’s a dream of his.

Scientists can identify those at high risk for arrhythmia, but they don’t know how it occurs or what triggers it. “It’s almost impossible to study this solely on the basis of experimentation,” Beaumont says. “Simulation is very useful. We have tremendous technology at our disposal in bioengineering. Among other things, we can get imaging of tissue and organs at high resolution and even map the distribution of protein expression. The decoding of the genome is allowing us to easily determine whether an individual is harboring defective proteins. All of this constitutes a massive amount of information. The future of medicine lies in better ways to integrate and exploit this data to develop cures.”

In cardiac modeling, there are many interrelated bits of data involved in the computation and differential equations to be solved along the way. That’s why — even with a supercomputer — it can take one to four days to run one of Beaumont’s simulations. “The exchange of information during computation is like circulation on a very congested highway,” he says. “If you have a bottleneck somewhere, a lot of other things are affected and it becomes hard to control traffic.”

He compares the moment that a simulation delivers a particularly surprising or amazing result to his childhood experiences of athletic victory.  “You are traversed by a wave of satisfaction from toe to head,” he says, grinning.

Beaumont says he and his colleagues are motivated by an opportunity to save lives, to put their model into the hands of clinicians and develop a therapy. “There is,” he says, “no better way to study a multi-scale problem like this.”