IBM and JDRF, a charitable organisation dedicated to funding type 1 diabetes research, are collaborating to develop and apply machine learning methods to analyse global type 1 diabetes research data and identify factors leading to the onset of the disease in children.
This new research collaboration is expected to create an entry point for type 1 diabetes in the field of precision medicine, by combining JDRF’s connections to research teams around the world and its subject matter expertise in type 1 diabetes 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 JDRF President and CEO, Derek Rapp.
“JDRF supports researchers all over the world, but never before have we been able to analyse their data comprehensively, in a way that can tell us why some children who are at risk get type 1 diabetes and others do not. IBM’s analysis of the existing data could open the door to understanding the risk factors of type 1 diabetes in a whole new way, and to one day finding a way to prevent type 1 diabetes altogether,” continued Rapp.
IBM scientists will look across at least three different data sets and apply machine learning algorithms to help find patterns and factors at play, with the goal of identifying ways that could delay or prevent type 1 diabetes in children.
In order to match variables and data formats and compare the differing data sets, the scientists plan to leverage previously collected data from global research projects. Data analysis will explore the inclusion of genetic, familial, autoantibody and other variables to create a foundational set of features that is common to all data sets.
The models that will be produced will quantify the risk for type 1 diabetes from the combined dataset using this foundational set of features. As a result, JDRF will be in a better position to identify top predictive risk factors for type 1 diabetes, cluster patients based on top risk factors, and explore a number of data-driven models for predicting onset.
“Nearly 40,000 new cases of type 1 diabetes will be diagnosed in the US this year. And each new patient creates new records and new data points that, if leveraged, could provide additional understanding of the disease,” said Senior Manager and Program Director at the Center for Computational Health at IBM Research, Jianying Hu.
“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 towards the prevention and management of diabetes,” continued Hu.
In the future, the collaboration hopes to better understand the causes of type 1 diabetes by analysing more complex datasets, such as microbiome and genomics or transcriptomics data. JDRF hopes the knowledge gained through the collaboration could help them develop a cure for people with type 1 diabetes.