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How Intel and Teva Are Tackling Huntington's Disease
September 16, 2016
2 Min Read
The two companies want a mobile health solution for continuously monitoring and analyzing key symptoms of the devastating neurological disease.
Teva Pharmaceutical Industries and Intel Corp. have announced a collaboration to create a wearable device and machine learning platform for better monitoring of Huntington's disease, in the hopes of better understanding the disease's progression.
In the process, the companies might be able to better evaluate treatments for the disease. The inherited disease results in the progressive breakdown of nerve cells in the brain, broadly impacting functional abilities and eventually leading to death. Researchers estimate that the disease affected four to 15 out of 100,000 people of European descent, according to Wikipedia.
To better understand Huntington's disease, Teva in collaboration with Intel will have people with the disease use a combo of a smartphone and a smartwatch with sensors able to continuously measure general functioning and movement. Data will be wirelessly streamed to the open-source Intel Trusted Analytics Platform (TAP), initially developed in collaboration with The Michael J. Fox Foundation for use in Parkinson's disease research.
Proprietary algorithms will crunch the Huntington's disease patient data in near real-time to produce motor symptom severity scores.
"Current measurement of symptoms is largely based on observation when the patient sees the doctor. This technology now provides us with an opportunity to have continuous monitoring," Michael Hayden, Teva's global R&D and chief scientific officer, said in a news release.
A machine learning platform could "help drive the pharmaceutical industry towards faster, better clinical trials, potentially leading to new treatments for patients," said Jason Waxman, corporate vice president and general manager of the Datacenter Solutions Group at Intel.
The study is expected to start near the end of 2016 in U.S. and Canadian centers.
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[Image by Frank Gaillard - Own work, CC BY-SA 3.0]
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