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An Engineering Approach to Translational Medicine

Physician-scientists may benefit from an approach that emphasizes solving problems over generating hypotheses

Michael Liebman

In the years since the completion of the Human Genome Project, physician-scientists have applied new energy to translating findings from the laboratory into better treatments for patients. Yet this accelerated, unidirectional transfer of knowledge from the bench to the bedside, a practice that goes by the name of translational medicine, is hitting an obstacle: The generation of data is far outstripping scientists' ability to convert it into usable knowledge. I believe that, paradoxically, this problem stems from the tightly focused approach that gives science much of its power. Genomics, proteomics and other high-throughput technologies are seductively powerful, but that seduction may limit our view of the complex problems of physiology and disease.

Breast-cancer diagnosis and treatment...Click to Enlarge Image

For example, scientists can now correlate a disease with a specific pattern of gene expression. Such experiments are straightforward and fairly quick when the tools are available, and they provide a massive quantity of data. However, by diverting limited resources of time, money and personnel, mining this wealth of data may actually lead investigators away from grasping the governing laws from which they could build predictive models of the disease.

I am not suggesting that investigators should give up high-throughput, brute-force methods. Today's technology is a boon to science and a powerful component of my own research. However, as clinical investigators, we stand to reap significant benefits on behalf of society by expanding our focus and viewing translational medicine not through the eyes of a scientist, but as an engineer might.

Why an engineer? Because an engineer uses the fruits of science to feed the appetite of technology. Unlike scientists, who tend to approach problems from a "bottom-up" perspective by collecting data and seeking patterns, engineers take a "top-down" approach, probing a specific system for clues, taking it apart and considering how each component can be handled in a tailored solution. An engineer is a problem solver rather than a hypothesis generator.

The two perspectives are neatly symbiotic in physics and chemistry, for which fundamental laws yield predictive models. But in the life sciences, biologists, including physicians, must be more aware of the gap between science and technology—we still know too little about the complexity of living systems to make many generalizations from first principles.

I propose that an engineering approach, what might be called "real systems analysis," may be a better way for scientists to identify and develop solutions for biomedical problems. This kind of problem solving requires that translational-medicine research place more emphasis on going from the bedside to the bench, rather than the other way around. The Clinical Breast Care Program (CBCP) is a collaboration between Windber Research Institute and Walter Reed Army Medical Center, and it is the prototype for an integrated approach to the study of breast cancer. Here, I present some examples of how top-down problem solving in the CBCP has provided unique insights.

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