Intel and MJFF Collaborate to Address Parkinson's disease through Big Data Analytics

By CIOReview | Monday, August 18, 2014

NEW YORK and SANTA CLARA, CA: Intel and Michael J. Fox Foundation for Parkinson's Research (MJFF) have partnered for advanced research and better treatment of Parkinson’s disease – a neurodegenerative brain disease. Technology advances in data collection and analysis now provide the opportunity to expand the value of this wealth of molecular data by correlating it with objective clinical characterization of the disease for use in drug development.

"The variability in Parkinson's symptoms creates unique challenges in monitoring progression of the disease," said Diane Bryant, Senior Vice President and General Manager of Intel's Data Center Group. "Emerging technologies can not only create a new paradigm for measurement of Parkinson's, but as more data is made available to the medical community, it may also point to currently unidentified features of the disease that could lead to new areas of research."

The data related to Parkinson’s features such as slowness of movement, tremor and sleep quality can be collected and analyzed from thousands of individuals. This data could help researchers in building a clinical progression of Parkinson’s and track its relationship to molecular changes.

Wearables can record and store data automatically at all the time without human intervention. This data is taken as an input for research and analysis. Insights generated from the huge amount of data can help in better tackling this disease.

Intel has developed a Big Data analytics platform to analyze the massive volumes of data collected through various means from the patients. This cloud-based platform enables researchers to track the anomalies and changes in sensor data. The finding and measuring of anomalies helps in tracking the progression of the disease objectively.

In the coming time, the platform can also be expected to be able to store data such as patient, genome, and clinical trial data. Advanced techniques such as machine learning, and graph analytics could also be enabled helping to build predictive models for researchers to detect change in disease symptoms.

Intel data scientists are gauging the devices’ accuracy by correlating the data collected to clinical observations and patient diaries.  Algorithms are also being developed to measure symptoms and disease progression.

MJFF and Intel are also expected to launch a new mobile application for reporting patients’ intake of medication as well as health status update.