Abstract: The burgeoning development of new technologies presents an interesting set of problems, especially in the health care arena. Federal regulatory agencies, industry, academia and constituency support groups are faced with the dilemma of providing the general population with the greatest and earliest exposure to technology without putting them at risk of premature product introduction – the tension between above all do no harm and rush to treat. It has become impossible to run clinical trials for long enough to identify rare, but potentially fatal events, and not impede technology transfer. Preclinical models are artificial and similarly constrained to consider only a subset of states. Only computational in silico models can embody the conceptual framework of device and drug interaction with pathology states, and in reasonable time simultaneously consider multiple permutations and combinations of anatomic structures, physiologic phenomena, pathologic states and possible interventions, device and drugs. 

Nowhere are these issues more acute than in the cardiovascular space – where diseases and dysfunction are responsible for the greatest causes of morbidity and mortality around the world. Innovation in every phase of live and medicine has reduced death from cardiovascular disease four-fold in the last 60 years. As we rush to sustain this momentum the balance of boldness and caution is increasingly threatened. At every stage computational modeling has played a role – critical to the understanding normal cardiac and vascular anatomy and physiology, characterization of the nature of disease, creation of innovative interventions, and delineation of response to these technologies.

The development, use and teaching of the discipline of modeling has evolved with insight into cardiovascular biology and medicine. Pioneers like Leonardo Da’Vinci helped make anatomy a scientific investigation simultaneous with development of quantitative methods; like his use of particle velocimetry tracking blades of grass flowing through fluid filled glass models of the heart and aorta. The last five centuries have seen what Howard Lord Florey noted was the concomitant synergistic development of science and technology. In this Florian paradigm new scientific insights advance our knowledge of disease, leading to development of new therapies and new devices which in turn require quantitative characterization of effect for full definition of their safety and efficacy.

Our obligation is to harness computational modeling to meld biology and engineering, medicine and science, for only then can we continue to advance health, educate communities and suggest lifestyle modification, produce novel medications based on deep insights and offer innovative interventions to improve the quality of life for all.

Bio: Elazer R. Edelman is Edward Poitras Professor Medical Engineering and Science MIT, Professor of Medicine Harvard Medical School, and Senior Attending Physician Brigham and Women’s Hospital. He directs MIT’s Institute for Medical Engineering and Sciences dedicated to applying physical sciences to biologic processes and disease mechanisms, and home to graduate and medical doctoral degrees programs. His research interests meld medical and scientific training leveraging pathophysiologic insight to improve clinical decision-making and device design.