Teva Uses IBM Watson for Healthcare Data Management

October 26, 2016 - IBM has partnered with Teva Pharmaceuticals to discover new treatment options and improve chronic disease management, both projects running on IBM Watson Health Cloud.

The duo are working together on an initiative that combines Teva's therapeutic technologies with IBM Watson's cognitive computing. Their initiative aims to enable patients, healthcare providers, and payers to better understand and control chronic conditions, and track treatments.

Teva will use IBM Watson technology to implement a systematic approach to assist their work in the emerging fields of drug repurposing. Using the data collected by Watson, Teva hopes to discover new uses for existing drugs to help better treat patients.

IBM and Teva’s collaboration also expands to chronic disease management, with their first target being respiratory and central nervous system diseases. Their chronic disease initiative also integrate data from the weather channel as an added dimension to the results.

"Teva envisions a future where we can empower patients and their families to better understand diseases, like asthma, and cope with health challenges in a more systematic, data-driven manner, with the ability to be proactive, rather than reactive," said Rob Koremans, MD, President and CEO of Teva Global Specialty Medicines. "In doing so, we aim to cut treatment costs by providing patients, payers, healthcare providers and caregivers with relatable data that can inform action and insights into a patient's total disease  management plan."

IBM Watson is a platform-as-a-service (PaaS) that uses language processing and machine learning to gather and reveal insights from large amounts of data. Watson is designed specifically for healthcare organizations to deliver precise and individualized results for a better understanding of what affects people’s health.  

"There is so much data out there that is currently underutilized, yet has the potential to significantly inform drug repurposing. Eighty percent of all health data is invisible to current technology systems because it's unstructured," said Ajay Royyuru, IBM Fellow and Director of Healthcare & Life Sciences for IBM Research. "Using cognitive technologies to mine this data could reveal novel therapies for diseases that desperately need tackling. By teaming up with Teva, our belief is we will gain insights that can lead pharmaceutical companies to develop new medicines that benefit patients worldwide."

Medical data processing and recording is one of the first technological tools to be generally accepted in the healthcare community beginning with electronic health records (EHRs). Research by Archives of Public Health found patients were dying or suffering more as a result of poor quality medical records. EHRs reduce errors, save time, and make it much easier to process medical data.

According to research conducted by Health Information Science and System, the volume of healthcare data is growing and without the proper management or processing solution enabled, the data that could help save lives is useless.

The unused data is valuable and the research points out that, “healthcare reimbursement models are changing; meaningful use and pay for performance are emerging as critical new factors in today’s healthcare environment. Although profit is not and should not be a primary motivator, it is vitally important for healthcare organizations to acquire the available tools, infrastructure, and techniques to leverage big data effectively or else risk losing potentially millions of dollars in revenue and profits.”

The research concluded that the benefits of analyzing this data include detecting diseases at earlier stages, managing specific individual and population health, detecting health care fraud more quickly and efficiently.

Partnerships similar to IMB and Teva’s are taking advantage of the massive amounts of healthcare data available and putting it to use. IBM and Teva plan to share their results to help the healthcare industry improve patient care.

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