Building A Biomedical Knowledge Network

UCSF Profiles
UCSF Profiles
A National Academy of Sciences committee co-chaired by UCSF Chancellor Susan Desmond-Hellmann, MD, MPH, recommends the creation of a Google maps-like data network that could transform the future of medical discovery, diagnosis and treatment. The so-called “Knowledge Network” would integrate the wealth of data emerging on the molecular basis of disease with information on environmental factors and patients’ electronic medical records, with the goal of developing more diagnostics and treatments tailored to individual patients — known as “precision medicine.” The development of this broadly accessible data network would allow scientists to share emerging research findings faster, thereby accelerating the development of tailored treatments. It also would allow clinicians to make more informed decisions about treatments. It would reduce health care costs and ultimately improve care. While the potential impact of the Knowledge Network on patients is clear, the impact on basic research would be profound as well, said Yamamoto, UCSF professor of cellular and molecular pharmacology.  In the database ‘cloud’ envisioned by the committee, he said, “One could imagine pulling down information about who’s studying a given type of molecular mechanism, or cross-correlating that mechanism to a disease, and asking, ‘What other diseases are linked?’ ‘What environmental factors influence this mechanism’, ‘Who are the people doing this type of work?’ “If you swept out in bigger and bigger areas of the network, pretty quickly studies, and the people doing them, would show up that you didn’t know about. You’d ask, ‘Who are these people? How are they approaching some of the same questions that interest me?’ In this imagined network, there would be a self-assembled team of collaborators. You’d be motivated to sit down with them and learn from each other. You could ask and answer questions you couldn’t possibly answer by yourself.” The strategy for fostering new research collaborations is similar to that of the UCSF Clinical and Translational Science Institute’s Profiles database, which works by providing a quick search to discover people, research expertise, and networks of co-authors and similar people.  Keep reading
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