University of Pittsburgh Gets Grant to Set up Big Data Center

With huge biomedical data sets scattered nationwide, often with incompatible computer software systems, accessing and analyzing the data for research and health-care benefits can be challenging. The National Institutes of Health now is working to correct the problem.

The NIH has awarded the University of Pittsburgh — with Carnegie Mellon University, the Pittsburgh Supercomputing Center and Yale as partners — an $11 million grant over four years to establish a Big Data to Knowledge Center of Excellence. It’s part of a 12-center nationwide network to develop “an amazing engine of discovery.”

Announcing formation of the network during a Thursday telebriefing, NIH Director Dr. Francis Collins said the goal is establishing better methods of storing, sharing and analyzing large data sets, all of which is necessary to coordinate research, drug development, genome analysis, and medical records and resources.

The initial NIH outlay of $32 million to establish the network will grow to $600 million through 2020 to fund the project.

“Much of science focuses on understanding the ‘why’ or ‘how’ in nature, and now the challenge is to find these answers within terabytes and petabytes of data, or what is now known as ‘Big Data,’ ” said Dr. Gregory Cooper, professor and vice chairman of the department of biomedical informatics in the Pitt School of Medicine and director of the new Center for Causal Modeling and Discovery.

“Individual biomedical researchers now have the technology to generate an enormous quantity and diversity of data. Adequately analyzing these data to discover new biomedical knowledge remains a major challenge, however,” Cooper said. “Our goal is to make it much easier for researchers to analyze big data to discover causal relationships in biomedicine.”

The grant will be used to establish the centers with components for education. The NIH also hopes to establish standards for biomedical data collection and use. The hope is for continued funding to operate and improve the centers once the initial grant ends.

Collins provided one example of how the network can be used: Understanding autism involves larger data sets of genetic information including variations in DNA, which play a role in the risk. Brain imaging and functional data also are available in various databases. The goal, he said, is “ trying to make sense of what that data is telling us.”

“The question is how to provide and use this data for prevention and treatment,” Collins said. “The centers will be the hub of that kind of activity.”

©2014 the Pittsburgh Post-Gazette