Findings are the result of a year-long collaboration of Roche Diabetes Care GmbH, IBM, Eli Lilly and Company, the Regenstrief Institute and the Indiana Bioscience Research Institute.
A leading scientific journal, Nature Medicine, has published a major study online on how real-world patient data can better predict diabetes-related kidney disease in patients with the chronic disease. A separate announcement from Roche Diabetes Care GmbH, the lead on this research study, explained that kidney disease, frequently a long-term complication of diabetes, is characterized by the progressive loss of kidney function, which often requires dialysis or renal transplant.
Authored by 13 scientists and researchers, the study, Predicting the Risk of Early Chronic Kidney Disease in Diabetes Patients Using Real-World Data, reveals that earlier recognition of patients likely to develop kidney disease, would provide information to slow progression of the disease, thereby improving health and reducing healthcare expense. The study is a collaboration of Roche Diabetes Care, IBM, Eli Lilly and Company, the Regenstrief Institute and the Indiana Bioscience Research Institute.
Using data originating from half a million people with diabetes, the Roche/IBM team developed a predictive algorithm to identify those who are at high risk for developing chronic kidney disease in the near future. In a direct comparison between the Roche/IBM predictive algorithm and similar, prior algorithms derived from clinical trials , the Roche/IBM algorithm outperformed all tested methods in a one-to-one comparison, as well as in cohort studies.
In an extension of the original collaboration, the IBRI, Eli Lilly and Indiana University School of Medicine through Regenstrief, provided Roche another independent real-world data set originating from 100,000 patients with diabetes obtained from the Indiana Network of Patient Care database, and the findings were confirmed.
“This is an example of one of the ways the IBRI is working in collaboration with scientists at other institutes and companies to gain access to the right data, such as that from the Regenstrief Institute to apply analytics and machine learning to work on major problems within life sciences,” said Dan Robertson, Ph.D., director of the IBRI’s Applied Data Sciences Center. “We are pleased to see the success of one of our early projects. We are continuing our work with our industrial partners to explore disease progression, patient stratification, digital diagnostics and eventually moving towards identifying new therapeutic targets to improve patient health.”
“Regenstrief, with its rich resource of one of the largest and most diverse sets of longitudinal, real-world medical data in existence, is proud to partner with other scientists, companies and research organizations as we use those data to advance science and improve health,” said Regenstrief Institute President and CEO Peter Embi, M.D. “This is a great example of how by working together, partnerships like these can empower breakthrough discoveries that ultimately will benefit patients and health care systems throughout the world.”
About the IBRI
The Indiana Biosciences Research Institute (IBRI) is a not-for-profit, independent applied research institute formed in 2013. The IBRI is focused on discovery and applied research to facilitate the development of technologies and innovations aimed at improving human and animal health, agriculture and the environment. Target areas are diabetes, metabolic disease and poor nutrition, and related applied data science and analytics. More at http://www.indianabiosciences.org
Founded in 1969 in Indianapolis, Ind., the Regenstrief Institute is a local, national and global leader dedicated to a world where better information empowers people to end disease and realize true health. The Regenstrief Institute and its researchers are responsible for a growing number of major health care innovations and studies. Examples range from the development of electronic health record innovations, global health solutions, and information technology standards that enable the use and interoperability—to improvements in patient-physician communications and the creation of models of care that inform practice and improve the lives of patients around the globe.