Today, advanced modeling and simulation technologies are allowing medical researchers to create “computational” models of even the most complex human systems such as the heart and brain. Using mathematical algorithms, patient data and simulation-based predictive computational techniques, researchers can simulate, predict, and understand the most intricate subsystems of human organs and systems, providing new opportunities to develop improved treatments.
No one is more surprised at these advances than Dr. Julius Guccione, a professor and cardiothoracic surgery researcher at the University of California, San Francisco, School of Medicine (USA), who initially believed many of the human body’s systems were simply too complex to model. Yes, simulation and biomechanics have been widely used in orthopedic surgery for treatments such as knee and hip replacements, but bones are structural components akin to the mechanical structures designed by manufacturers. Human organs, Guccione believed, were an entirely different challenge.
“Modeling and simulation have been used very successfully in the design of automobiles and airplanes, but many of us viewed the heart as being orders of magnitude more complicated than any other engineering structure being tackled,” Guccione said. “But when I saw firsthand the complexity of the mathematical models used in these other industries, it really changed my mind. The detail and size of the models and the computational time is very, very impressive.”
“IT’S UNUSUAL FOR A SOLID TO HAVE SUCH EXTRAORDINARY MATERIAL PROPERTIES.”DR. JULIUS GUCCIONE
PROFESSOR AND CARDIOTHORACIC SURGERY RESEARCHER, UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, SCHOOL OF MEDICINE, SPEAKING ABOUT THE HUMAN HEART
Heart fibers undergo extreme deformations, with at least 20% elongation and contraction throughout the cardiac cycle, Guccione said. “It’s a much more nonlinear problem than modeling human bone, where any deformation is difficult to detect,” he said. “It’s unusual for a solid to have such extraordinary material properties.”
Today, however, Guccione and his colleagues are using mathematical modeling and simulation techniques to test the safety and efficacy of a biopolymer gel injection designed to strengthen and stabilize the human heart during episodes of heart failure. Using these techniques to understand the mechanism of individual patients’ hearts will allow researchers to tailor the amount of gel and the administered location to achieve the most beneficial effect for each patient.
Another important frontier for the use of human modeling and simulation technologies is in regulatory approval. Dawn Bardot, senior program manager for modeling and simulation at the Medical Device Innovation Consortium (MDIC), a public-private partnership that aims to advance regulatory science for the medical device industry, said that medical device manufacturers use modeling and simulation extensively to sort through competing designs and examine field failures. But they have not yet gained the credibility required by regulators for making safety and efficacy decisions.
Developing model and simulation techniques to the regulatory level will require new approaches and a collaborative effort to better understand complex inputs such as material properties, human anatomy, physiological conditions and disease states, according to MDIC. In parallel, researchers such as Guccione’s team focus on developing systems-level models.
“We really don’t have good cartography of the human body’s variability from an anatomical, physiological or material property perspective yet,” Bardot said. “But when we have those system-level models and simulations, we can move away from bench-top tests that attempt to represent something about a human, eliminate animal testing, and reduce the number of clinical trials and patients involved in them.”
Researchers like Guccione and his colleagues are on the leading edge of a new push to better understand the biological pathways and systems that connect and drive the intricate systems of human body, said Dr. Alan Louie, research director at IDC Health Insights, based in Framingham, Massachusetts (USA). “We’re very early in understanding the interactions of the different biological pathways, systems and organs of the human body – and they’re very different than the physical systems, such as bone and skeletal muscle,” Louie said. “But we’re beginning to be able to simulate some of these models.”
The research is still in the early stages of development. “Translating a model into a computational-based system is, to a large extent, ‘linear’ thinking, and some of these complex systems cannot be explained using linear thinking,” Louie said. “The ability to bring the right pieces together is the hard part.”
Many new tools are emerging that have the potential to deliver some value in this space, he said. One well-known example is Watson, the IBM supercomputer best known for beating the best human competitor in the US knowledge game show “Jeopardy.” “Watson takes stores of knowledge as decision-making points and overlays that onto available data sets,” Louie said.
Watson helps researchers overlay health data, including electronic medical records, with genomic discoveries, population biology data, social media insights on the comparative effectiveness of drugs, and other medically relevant data from diverse sources. Watson then filters those inputs through a system that identifies commonalities.
“Simulation of human systems is coming,” Louie said. “It relies on systems to connect vast amounts of diverse and far-flung data, accommodate nonlinear thinking and capture the immense complexity, but the ability to visualize all of these interactions is going to be a very powerful enabler.”