Collaboration between IBM and the Juvenile Diabetes Research Fund (JDRF), one of the leading groups funding the fight against type 1 diabetes, will apply machine learning to troves of worldwide research data accumulated over the years with the aim of uncovering commonalities that could point to diabetes risks in children.
“Nearly 40,000 new cases of type 1 diabetes will be diagnosed in the U.S. this year. And each new patient creates new records and new data points that, if leveraged, could provide additional understanding of the disease,” said Jianying Hu, senior manager and program director at the Center for Computational Health at IBM Research. “The deep expertise our team has in artificial intelligence applied to healthcare data makes us uniquely positioned to help JDRF unlock the insights hidden in this massive data set and advance the field of precision medicine toward the prevention and management of diabetes.”
Type 1 diabetes (T1D) affects about 1.25 million Americans, and to date does not have a cure. What the research collaboration will attempt to do is create an entry point in the field of precision medicine — combining JDRF’s connections to research teams around the globe, and its subject matter expertise in T1D research
, with the technical capability and computing power of IBM.“At JDRF, we are absolutely committed to seeing a world without type 1 diabetes, and with this partnership, we’re adding some of the most advanced computing power in the world to our mission,” said Derek Rapp, JDRF President and CEO, in a statement. “JDRF supports researchers all over the world, but never before have we been able to analyze their data comprehensively, in a way that can tell us why some children who are at risk get T1D and others do not. IBM’s analysis of the existing data could open the door to understanding the risk factors of T1D in a whole new way, and to one day finding a way to prevent T1D altogether.”
IBM scientists will look across at least three different data sets and apply machine learning algorithms to help find patterns and factors that may be at play, with the goal of identifying ways that could delay or prevent T1D in children.
While research has gathered volumes of data, it’s been difficult to make generalizations based on the data to understand it, says Jessica Dunne, director of discovery research for JDRF, in a blog on the organization’s web site. Research has revealed that type 1 diabetes develops differently in different people, she says.
“We know factors like a person’s age can influence disease course,” Dunne adds. “We also know that type 1 diabetes progresses through a series of defined stages, and we have supported multiple long-term studies tracking disease progression in different groups of people. This has yielded detailed timelines of disease course in tens of thousands of people, along with records on family history of type 1 diabetes, genetics, other medical history, environmental factors and diet.”
To maximize the potential of all these factors, “We need to view the data holistically. Unfortunately, the data sets are independent, having been collected in different ways, at different times, in different locations and by different people.”
The organization recognized that it needed more computing power, making the collaboration with IBM a natural fit. Dunne says JDRF and IBM scientists will analyze at least three previously collected data sets from global research and apply machine learning algorithms to find patterns and factors at play. “This large-scale data analysis will lead to deeper understanding of the risk factors and causes of type 1 diabetes and eventually finding a way to prevent it entirely.”
Future phases of the collaboration may consist of furthering the analysis of big data toward the goal of better understanding causes of type 1 diabetes. They may also consist of analyzing more complex datasets, such as microbiome and genomics or transcriptomics data.
