The National Institutes of Health (NIH) will pour $24 million per year into Big Data to Knowledge Centers of Excellence, investigator-initiated facilities that will research data science. The deal will extend for four years, bringing NIH’s investment in the initiative to a little under $100 million.
That’s quite a bit of money, but it could result in some big dividends: biomedical research is a lucrative and potentially world-changing area of study—and one that requires the efficient crunching of some truly epic datasets. The Big Data to Knowledge Centers of Excellence (an awkward name reduced to the equally unwieldy semi-acronym of “BD2K Centers of Excellence”) will offer training for students and researchers, in addition to the development of more innovative approaches and software for data analytics.
NIH defines the major challenges facing biomedical Big Data as… well, pretty much everything, from training researchers who can use data effectively to developing new methods for analyzing data. “The ability of researchers to locate, analyze, and use Big Data (and more generally all biomedical and behavioral data) is often limited for reasons related to access to relevant software and tools, expertise, and other factors,” read a note posted on NIH’s BD2K Webpage. “BD2K aims to develop the new approaches, standards, methods, tools, software, and competencies that will enhance the use of biomedical Big Data by supporting research, implementation, and training in data science and other relevant fields.”
Program applicants will need to provide NIH with a research topic, with the expectation that the results of the research will be shared with the broader research community; applications are due November 20.
“This funding opportunity represents a concerted effort to leverage the power of NIH in developing cutting-edge systems to address data science challenges,” NIH Director Francis S. Collins, M.D., Ph.D, wrote in a statement. “The goal is to help researchers translate data into knowledge that will advance discoveries and improve health, while reducing costs and redundancy.”
Meanwhile, private industry is also hard at work on healthcare analytics. IBM, for example, has become a prominent player in the field, thanks in large part to its Watson supercomputing platform. In February, Memorial Sloan-Kettering Cancer Center in New York City announced that, for the past year, it has partnered with IBM and WellPoint to train Watson in processing and interpreting oncology data.
Other hospitals and tech companies are exploring how data analytics can improve everything from cancer treatments to intensive-care units. So NIH isn’t the first to realize the potential impact of Big Data on the nation’s health—but its efforts could still improve things for everyone.