The Michael J Fox Foundation is using big data techniques in an attempt to cure Parkinson's disease, in collaboration with chip manufacturer Intel.
"Nearly 200 years after Parkinson's disease was first described by Dr James Parkinson in 1817, we are still subjectively measuring Parkinson's disease largely the same way doctors did then," said Todd Sherer, PhD, CEO of The Michael J Fox Foundation.
"Data science and wearable computing hold the potential to transform our ability to capture and objectively measure patients' actual experience of disease, with unprecedented implications for Parkinson's drug development, diagnosis and treatment," he added.
"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," she said.
The purpose of the research is to build up a better picture of the clinical progression of the disease, and to better understand its relationship to molecular changes in patients' bodies.
With wearable sensors providing experiential data in real time, 24/7, researchers will go from looking at a small number of data points, to analysing more than 300 readings per second from thousands of patients.
To analyse this large volume of data, Intel has developed a big data analytics platform that integrates a number of software components including CDH from its recent purchase of Cloudera – an open-source software platform that collects, stores, and manages data. This platform is deployed on a cloud infrastructure optimised on Intel architecture, which Intel claims will allow scientists to focus on research rather than the underlying technologies.
The platform supports an analytics application developed by Intel to process and detect changes in the data in real time. By detecting anomalies and changes in sensor data, the platform aims to provide researchers with a way to measure the progression of the disease objectively.
In future, the platform could store other types of data such as patient, genome and clinical trial data. In addition, Intel states that the platform could enable other techniques such as machine learning and graph analytics to deliver more accurate predictive models that researchers could use to detect change in disease symptoms. These advances could provide new insights into the nature of Parkinson's disease, helping scientists measure the efficacy of new drugs.