Once Natalia Trayanova latches onto a goal, she’s not the type to let go of it anytime soon. In fact, she traces her life’s obsession with the natural laws of science to cherished moments spent on her father’s knee back home in Bulgaria. “I remember him reading this book to me about rockets,” she says, traces of her homeland still present in her accent. “It was just so fascinating to me, the laws of physics and how they work when things are going up like that and out of the world. I couldn’t stop asking questions.”
She fantasized as a little girl about becoming an astrophysicist, but it turned out her father, a physiologist, wasn’t done with that business of sharing books that would change her life. During her college years he returned home from an academic conference in the United States with a book titled Bioelectric Phenomena, which explores the way electrical activity functions in nerves and muscles.
“That book was just so amazing to me,” Trayanova says, lifting her head skyward and throwing both arms in the air. “It was the first time I ever really thought about the ways that physics might be applied to biological structures.”
And so Trayanova pulled her sights back from outer space and turned her attention instead to the inner workings of the human body. Today, as the Murray B. Sachs Professor of Biomedical Engineering, she directs the Computational Cardiology Lab (CCL) at the Institute for Computational Medicine, where her team is at the forefront of efforts to understand the intricacies of the workings of the human heart—and to do so in ways that are now showing great potential to help people live longer and healthier lives.
PEOPLE TEND TO THINK about human disease as if it were a linear phenomenon. Sickness has a beginning, and it has an end. It has a cause, and then it has effects. You can plot this way of thinking along a flat chronological line—genetic flaw A leads to biological process B and ends in disease C.
But the human body is not a linear operation, of course, and the mysteries of an organ like the human heart can run as deep in the biological sense as they do in the emotional one.
The landscape where disease unfolds is an astonishingly complex place with genes, proteins, molecules, and cells interacting at every turn as they tackle their tasks. The lines of communication involved don’t just move up from genes toward the organ, but back down as well. And the outside environment, with its pollutants and toxins and other triggers, is always knocking at the door, too.
“There are so many of these interactions going on in the heart, and they are all nonlinear,” Trayanova says. “Even if you know everything that’s happening at the molecular level, you won’t know what that means for the whole heart. The behaviors you end up with at that level of the whole heart often turn out to be much bigger than the sum of the parts.”
Capturing this complexity is what computational medicine is all about. The field traces its roots to the 1950s when British scientists Alan Lloyd Hodgkin and Andrew Huxley developed novel ways to express biological phenomena in mathematical terms. That Nobel Prize–winning work opened the door to creating computer models that mimic biological processes in all their dizzying complexity.
Since arriving in the United States on a National Academy of Sciences fellowship in 1986, Trayanova has focused her modeling work on the heart. Her first post on these shores placed her in the lab of Duke biomedical engineer Robert Plonsey, the man who wrote Bioelectric Phenomena back in 1969. Trayanova went back to Bulgaria briefly after the fellowship but soon returned to the United States and set up her lab first at Duke and then at Tulane.
She came to Johns Hopkins in 2006, one year after the Institute for Computational Medicine was launched as a collaboration between the School of Medicine and the Whiting School of Engineering. Trayanova brought with her a team of 11. Today, 15 researchers are at work in the Computational Cardiology Lab, which receives slightly more than $1 million a year in direct funding and publishes at the rather prolific rate of more than a dozen papers a year.
In building a virtual heart, Trayanova’s team starts by constructing a geometric scaffolding of the organ out of data from magnetic resonance imaging (MRI) scans and computed tomography (CT) scans. Then, they flesh out that scaffolding one piece a time, “populating” the structure with computational representations of the inner workings of the heart, all the way down to cells, molecules, and electrical activity.