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Teva, Intel partner on machine-learning tech for Huntington's Disease

Teva and Intel hope to spur the development of next-generation treatment options by better understanding the progression of the disease and how current treatments impact a patients' quality of life.
Written by Natalie Gagliordi, Contributor

Israeli pharmaceutical firm Teva is partnering with US chipmaker Intel to develop wearables and a machine-learning platform that can be used in the treatment of Huntington's Disease.

Huntington's is a genetic and typically fatal neurodegenerative disease that causes nerve cells in the brain to deteriorate. This leads to a host of behavioral and psychological problems, including involuntary writhing movements called chorea. Patients generally succumb to the disease within 15 to 25 years of the diagnosis.

There is no cure for Huntington's, but Teva and Intel hope to spur the development of next-generation treatment options by better understanding the progression of the disease and how current treatments impact a patients' quality of life.

The companies plan to accomplish this by combining Intel's capabilities in analytics and algorithms with Teva's work around Huntington's treatment and research.

Specifically, patients will wear a smartwatch outfitted with sensors that will continuously measure their general functioning and movement. The data will feed into a cloud-based, machine-learning platform developed by Intel for analysis.

The platform was first developed two years ago as part of a multi-phase partnership between Intel and The Michael J. Fox Foundation for use in Parkinson's disease research. In both cases, the aim is to detect patterns in participant data collected from wearables intended to monitor symptoms.

"Patients generate data based on their day-to-day experiences that can help in improving disease management -- even something as simple as wearing a smart watch can add useful insight," said Jason Waxman, VP and GM of Intel's the Datacenter Solutions Group. "The complexity of analyzing these data streams requires a platform for machine learning, to help drive the pharmaceutical industry towards faster, better clinical trials, potentially leading to new treatments for patients."

The study will start toward the end of the year and will take place in centers in the US and Canada.

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