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Research Collaboration to Use Big Data for Diabetes Prevention


Researchers in Indiana will leverage big data analytics techniques to explore the prevention and treatment of type 2 diabetes.

In an effort to improve the treatment and understanding of type 2 diabetes in various patient populations, a new collaboration between the Indiana Bioscience Research Institute (IBRI), Eli Lilly and Company, Roche Diagnostics, the Regenstrief Institute and Indiana University School of Medicine will use big data to conduct research into the metabolic disease.

With access to data on more than 800,000 diabetics in the state of Indiana, the project will leverage a connection to biology and technology to improve population health management of diabetic patients.

“One of the areas of focus for the IBRI is the convergence between life science research, informatics and technology,” said David Broecker, President and CEO of the IBRI. “Every life science organization is working to understand how to connect biology to technology to drive both new discoveries and interventions, particularly in complex diseases like diabetes.”

“Given our unique position as an independent research institute, the IBRI is able to bring together leading companies like Lilly and Roche with academic collaborators like Regenstrief and Indiana University to explore a big problem from multiple perspectives and data sources,” Broecker added.  “This is the essence of ‘big data’ and we believe that this initial project will lead to future collaborations in other areas.”

By analyzing patient data from the Regenstrief Institute’s Indiana Network of Patient Care database, researchers will develop a sample diabetic population to identify variations in the disease and explore potential treatment options.

“As a global leader in diabetes research and care, Lilly is pleased to be a part of this groundbreaking research taking place in our home state of Indiana,” said Darren Carroll, Senior Vice President of Corporate Business Development at Eli Lilly and Company. “The outcome of the work conducted by this collaboration will give us important and new insights into type 2 diabetes – hopefully leading us to improved therapies and tools to care for patients with this disease.”

Diabetes results in billions of dollars in care costs for the healthcare system, and may result in spending of up to $10,000 per patient each year.  Researchers and providers leveraging big data analytics techniques hope to lower these costs, and the quality-of-life impacts on patients, by developing improved care models and personalized chronic disease management programs.

Their efforts may already be paying off, as population health management techniques driven by big data have contributed to a steady drop in the number of new diabetes cases since 2009.

“As a leader in diabetes management solutions we find it increasingly important to utilize data of large patient populations to ensure our customer solutions solve patient needs and create true medical value,” said Brian Heald, Head of Global Research & Development, Roche Diabetes Care, Inc.

“This research project will aid us in understanding the future potential to utilize predictive computational phenotyping to establish solutions for patients that help avoid disease complications and disease progression. The ultimate aim is to learn how to use insights from existing data to establish options to help people with diabetes live healthier lives.”

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