SOURCE: Ayasdi


October 16, 2014 11:00 ET

Bayes Impact Uses Ayasdi's Advanced Analytics to Discover New Breakthroughs in Parkinson's Disease

Ayasdi Cure Precisely Stratifies Patients to Improve Outcomes, Using Data From Smartphones and Clinical Research

MENLO PARK, CA--(Marketwired - Oct 16, 2014) - Ayasdi ( today announced that it is teaming up with Bayes Impact to discover insights that will lead to improved outcomes for people with Parkinson's disease. The Michael J. Fox Foundation for Parkinson's Research (MJFF) is providing data from Parkinson's disease patients, Bayes Impact data scientists are performing the analysis, and Ayasdi is using its advanced analytics software, Ayasdi Cure™, to accurately stratify patients and advance precision medicine.

Ayasdi Previously Identified New Patient Sub-Groups Based on Data Collected from Smartphones
Today, two-thirds of U.S. consumers carry smartphones throughout the day. Increasingly, smartphones track many aspects of our lives including where we go, what we buy and what we search. Health care companies and foundations are beginning to use smartphones as a way to track patient health in real-time. In early 2013, The Michael J. Fox Foundation launched a Parkinson's Data Challenge, making available accelerometer and gyroscope data from smartphones of people with Parkinson's and of healthy control volunteers.

Ayasdi applied its deep analytics and machine learning software to this dataset and proved that data collected from smartphones can be used to differentiate subjects with Parkinson's disease from healthy controls. In addition, preliminary results revealed two subpopulations of Parkinson's patients, as defined by the data collected from the smartphones.

"Years from now, I would expect that smartphone data from Parkinson's patients would stream directly to physicians so that they can see the severity of the disease in real-time and if new medications are ineffective or efficacious," said Damir Herman, Principal Data Scientist for Life Sciences at Ayasdi. "Instead of waiting a month for a patient to visit a doctor's office, a physician would know right away if the current course of therapy is working or if it's necessary to change treatment protocols. This is really the future of medicine, and I'm thrilled that Ayasdi is teaming with Bayes Impact to lead the way."

Bayes Impact Now Exploring More Precise Stratification of Parkinson's Patients to Improve Outcomes
Bayes Impact data scientists are applying Ayasdi's advanced topological analysis software to the Parkinson's Progression Markers Initiative (PPMI) dataset, with the goal of further stratifying Parkinson's disease patients to identify biomarkers. Ayasdi Cure helps identify patient subgroups with distinct traits, which may point to different pathological mechanisms and thereby treatment options.

PPMI is a longitudinal study taking place at 32 clinical sites around the world with a goal of validating biological markers of disease risk, onset or progression. The initial cohort enrolled 400 people with Parkinson's and 200 controls, and the study has since expanded to recruit people with Parkinson's risk factors: loss of sense of smell, REM behavior disorder and genetic mutations. MJFF sponsors the study and makes de-identified data from volunteers available for open access to qualified researchers.

"When we first engaged with Ayasdi, we weren't sure what we would find, but the results were immediately apparent," said Ken Kubota, Director of Data Science at The Michael J. Fox Foundation. "We are now including MJFF-sponsored PPMI data for Bayes Impact and Ayasdi to discover even richer insights that can potentially lead to real breakthroughs in the management and treatment of Parkinson's disease."

"The PPMI dataset is ideally suited for computational exploration because of its diverse set of tests and the large number of subjects enrolled," said Eric Liu, Chief Program Officer, Bayes Impact. "Topological data analysis from Ayasdi has proven to be an incredible way of discovering new insights from complex data."

About Ayasdi
Ayasdi is transforming how the world uses data to solve complex problems by automatically discovering and operationalizing insights from complex datasets. Founded in 2008 after a decade of DARPA and NSF funded research at Stanford, Ayasdi's has been named as one of the most innovative companies in big data by Fortune, Fast Company and others. The company's advanced analytics solution combines machine learning with Topological Data Analysis (TDA), enabling users to extract subtle, often hidden insights from their data. Funded by Khosla Ventures, Institutional Venture Partners, GE Ventures, Citi Ventures, and FLOODGATE, Ayasdi's customers include General Electric, Citigroup, Anadarko, Boehringer Ingelheim, the University of California San Francisco (UCSF), Mercy, and Mount Sinai Hospital. To learn more, visit or follow us @ayasdi.

Ayasdi helps the world's biggest and most sophisticated organizations discover breakthroughs that change how we all live and work. People who share this passion can view Ayasdi career opportunities here.

About Bayes Impact
Bayes Impact is a Y Combinator-backed nonprofit on a mission to bring the data revolution to the social sector. We deploy data science teams to develop solutions to social impact challenges, partnering with civic and nonprofit organizations. Our data scientists come from leading technology companies and academic institutions, including Google, Facebook, Cloudera, Genentech, Harvard, Stanford, and UC Berkeley. We are leveraging data science to positively impact our community and foster a new model of sustainable progress. To learn more, visit our website at

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