Teva Pharmaceutical Industries has announced a collaboration with Intel to develop a unique wearable device and machine learning platform for use in Huntington disease (HD). This platform will continuously monitor and analyze key symptoms that impact daily living, in an effort to better understand disease progression and improve treatment evaluation.
Teva, working in collaboration with Intel, will deploy this novel technology platform for the first time in a sub-study within the ongoing phase II Open-Pride HD Study. As part of this, patients will be asked to use a smartphone and wear a smartwatch equipped with sensing technology that will continuously measure their general functioning and movement. These data will be wirelessly streamed to a cloud-based platform specifically developed by Intel to analyze data from wearable devices. Proprietary algorithms will then translate these data, in near real-time, into objective scores of motor symptom severity. The study will start towards the end of the year and will take place in centers in the U.S. and Canada.
This collaboration will leverage Intel’s capabilities in analytics and algorithm development for movement detection, together with Teva’s deep knowledge and experience in HD treatment and research. HD is a devastating illness that is desperate for treatment options, requiring innovative ways to continuously and remotely assess and quantify symptoms in a way that can provide meaningful and actionable feedback to doctors, patients and caregivers.
“The aim of this important project is to provide continuous objective data on the impact of Huntington disease on the patient, and, by extension, a clear understanding of the impact of treatment on patients’ quality of life,” said Michael Hayden, president of Teva Global R&D and Chief Scientific Officer. “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. This unique technology could complement future trials in HD.”
“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, corporate vice president and general manager of the Datacenter Solutions Group at Intel. “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.”
This cloud-based solution for analyzing wearable device data is being developed using the open-source Intel Trusted Analytics Platform (TAP), a software platform optimized for performance and security to accelerate the creation of advanced analytics and machine learning solutions. Initial development was done in collaboration with The Michael J. Fox Foundation for use in Parkinson’s disease research.