Potential Research Focus Includes Subarachnoid Hemorrhage and Diabetes
SOUTHBOROUGH, Mass., - October 30, 2019 - Virtusa Corporation (NASDAQ GS:VRTU), a global provider of digital strategy, digital engineering, and IT services and solutions that help clients change and disrupt markets through innovation engineering, today announced it is collaborating with The University of Texas Health Science Center at Houston (UTHealth), Cardinal Health, and Amazon Web Services (AWS) to use AI and machine learning techniques to advance medical research.
This research collaboration is led by UTHealth’s faculty member, Hulin Wu, PhD, and will initially focus on finding the best treatment and management strategies for subarachnoid hemorrhage (SAH) and diabetes based on health care data and computer simulations.
Virtusa and Cardinal Health will simulate a comprehensive dataset comprising Electronic Health Records (EHR) representing more than 30,000 patients. Using vLife®, Virtusa’s cloud-based platform consisting of a comprehensive HIPAA-compliant data lake with multiple data sources, pre-built APIs, AI, and machine learning models, researchers hope to uncover hidden trends that can lead to new treatment strategies and cures for a range of illnesses.
UTHealth will leverage the simulated data to train and evaluate machine learning models capable of predicting treatment outcomes for certain types of illnesses. The data provided through Cardinal Health’s Proxi patient population simulation requires minimum data cleaning and preparation and is ready for the application of machine learning models soon after synthesis.
For the project, more than 20 faculty and students in the Department of Biostatistics and Data Science at UTHealth School of Public Health will team with clinicians, epidemiologists, informaticians, and computer scientists.
“We are developing novel statistical methods and machine learning approaches to interrogate EHR databases to identify the best treatment strategies and risk factors for a variety of diseases using real-world evidence,” said Hulin Wu, PhD, the Betty Wheless Trotter Professor and chair of the department. “The EHR data simulated by Virtusa’s platform will help us test and validate our new predictive models and machine learning algorithms before applying to the real EHR data."
“Life science companies must address how to seize the upside of disruption in today’s transformation age,” said Anthony Lange, senior vice president, Life Sciences, Virtusa. “Future value in life science is driven by innovation that focuses on outcomes with a high degree of personalization and is fueled by unlocking the power of simulated data. At Virtusa, we recognize the critical importance of collaboration in advancing AI technologies to create intelligent solutions that make lives better and businesses more efficient. As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions. At Virtusa, we leverage our deep industry and technical expertise to define solutions that make it easier for organizations to benefit from AI. We are very excited to be taking such problems head-on along with UTHealth on our vLife® Platform.”
“Cardinal Health is excited to see another effective use for Proxi, our simulated EHR data platform,” said Jeff Graham, principal, Big Data Analytics, Cardinal Health. “Through the use of our technology, organizations like UTHealth can work with simulated clinical records to accelerate research, augment existing real-world-evidence, and save time by using clean, ready-to-use linked data.”
"The availability of Virtusa’s Machine Learning Model Packages for disease state classifications on AWS Marketplace will assist our health care data scientist customers to deploy and integrate machine learning models into their applications quickly,” said Ananth Balasubramanian, global lead of Healthcare and Life Sciences, AWS Marketplace, Amazon Web Services, Inc. "We are excited to have another set of great solutions added to the catalog to help our customers harness the power of AWS to build mission-critical applications."
“With all the hype associated with Big Data, it has been exceptionally satisfying to work in close collaboration with our partners at Virtusa, Cardinal Health, and now UTHealth to develop innovative, effective solutions in the AI technology space that has the potential to impact human health,” said Daniel H. Robertson, PhD, research fellow and vice president of digital technology, Indiana Biosciences Research Institute (IBRI). IBRI serves as a consultant to Virtusa on issues of molecular biology in engagements, including this one with UTHealth.
To learn more about Virtusa’s Life Sciences capabilities, please visit: virtusa.com/practice/life-sciences/
Virtusa Corporation is a global provider of digital business strategy, digital engineering, and information technology (IT) services and solutions that help clients change, disrupt, and unlock new value through innovative engineering. Virtusa serves Global 2000 companies in Banking, Financial Services, Insurance, Healthcare, Communications, Media, Entertainment, Travel, Manufacturing, and Technology industries.
Virtusa helps clients grow their business with innovative products and services that create operational efficiency using digital labor, future-proof operational and IT platforms, and rationalization and modernization of IT applications infrastructure. This is achieved through a unique approach blending deep contextual expertise, empowered agile teams, and measurably better engineering to create holistic solutions that drive the business forward at unparalleled velocity enabled by a culture of cooperative disruption.
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Virtusa Corporation (NASDAQ GS:VRTU), a global provider of digital strategy, digital engineering, and IT services and solutions that help clients change and disrupt markets through innovation engineering, today announced it is collaborating with The University of Texas Health Science Center at Houston (UTHealth), Cardinal Health, and Amazon Web Services (AWS) to use AI and machine learning techniques to advance medical research.