ENP Newswire -
Release date- 14082014 -
The collaboration includes a multiphase research study using a new big data analytics platform that detects patterns in participant data collected from wearable technologies used to monitor symptoms. This effort is an important step in enabling researchers and physicians to measure progression of the disease and to speed progress toward breakthroughs in drug development.
'Nearly 200 years after Parkinson's disease was first described by Dr.
'The variability in Parkinson's symptoms creates unique challenges in monitoring progression of the disease,' said
Tracking an Invisible Enemy
For nearly two decades, researchers have been refining advanced genomics and proteomics techniques to create increasingly sophisticated cellular profiles of Parkinson's disease pathology. 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 potential to collect and analyze data from thousands of individuals on measurable features of Parkinson's, such as slowness of movement, tremor and sleep quality, could enable researchers to assemble a better picture of the clinical progression of Parkinson's and track its relationship to molecular changes.
Wearables can unobtrusively gather and transmit objective, experiential data in real time, 24 hours a day, seven days a week. With this approach, researchers could go from looking at a very small number of data points and burdensome pencil-and-paper patient diaries collected sporadically to analyzing hundreds of readings per second from thousands of patients and attaining a critical mass of data to detect patterns and make new discoveries.
Later this year,
Collecting, Storing and Analyzing the Data
To analyze the volume of data, more than 300 observations per second from each patient,
The platform supports an analytics application developed by
In the near future, the platform could store other types of data such as patient, genome and clinical trial data. In addition, the platform could enable other advanced 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 unprecedented insights into the nature of Parkinson's disease, helping scientists measure the efficacy of new drugs and assisting physicians with prognostic decisions.
Shared Commitment to Open-Access Data
The Foundation has previously made de-identified data and bio-samples from its sponsored studies available to qualified researchers, including from individuals with a Parkinson's-implicated mutation in their LRRK2 gene. MJFF has also opened access to resources from its landmark biomarker study the Parkinson's Progression Markers Initiative (PPMI) since it launched in 2010. Parkinson's scientists around the world have downloaded PPMI data more than 235,000 times to date.
As the world's largest nonprofit funder of Parkinson's research,
In addition to funding more than
Operating at the hub of worldwide Parkinson's research, the Foundation forges groundbreaking collaborations with industry leaders, academic scientists and government research funders; increases the flow of participants into Parkinson's disease clinical trials with its online tool, Fox Trial Finder; promotes Parkinson's awareness through high-profile advocacy, events and outreach and coordinates the grassroots involvement of thousands of Team Fox members around the world.
Tel: (408) 765-8080
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