Molecular biology findings must be included, it says

By Rajendrani Mukhopadhyay 

Late last year, the National Research Council released a report calling for a new data network to integrate the latest research on the molecular causes of diseases with clinical data from individual patients. The report said that the network could lead to a more accurate classification of disease and, in turn, a new taxonomy, which would improve clinical diagnoses and treatments. The committee that put together the report argued that the time was right to embark on this change, given the richness of current biological data, advances in information technology and the changes needed in the U.S. health-care system. The NRC undertook this study at the request of Francis S. Collins, the director of the National Institutes of Health.

“Currently, a disconnect exists between the wealth of scientific advances in research and the incorporation of this information into the clinic,” Susan Desmond-Hellmann, co-chair of the committee that authored the report and chancellor of the University of California, San Francisco, said in a statement. “Often it can take years for biomedical research information to trickle to doctors and patients, and in the meantime wasteful health care expenditures are carried out for treatments that are only effective in specific subgroups. In addition, researchers don’t have access to comprehensive and timely information from the clinic.”

To develop the new disease taxonomy, the committee recommended creating an “information commons” to bring fundamental molecular research (such as findings in epigenetics, metabolomics, genomics and proteomics) together with medical histories,environmental exposures and treatment outcomes of individual patients. The information commons then would be mined to understand and integrate the connections between the different types of data to produce a knowledge network. The new disease taxonomy would rise from a better understanding of the connections between molecular biology and clinical data derived from large patient numbers within the knowledge network.

Molecular biologists and biochemists stand to benefit from this proposed setup. Keith Yamamoto, a molecular biologist at the University of California, San Francisco, who served on the committee, explains that the information commons and knowledge network will broaden the scope of fundamental research. With a database at their fingertips that links disparate types of data — for example, genomic analyses and behavioral studies— investigators will find it easier to identify interesting hypotheses to pursue and to find potential collaborators with the specific expertise to build the multidisciplinary team necessary to tackle the hypotheses. “The knowledge network will allow you to fi nd things you were not looking for, much the way that Google does,” explained Yamamoto.