UCLA Health deploys Microsoft Azure to leverage big data

Healthcare system is adopting software giant’s cloud computing services to gain insights from vast clinical and genomic information.

Los Angeles-based UCLA Health is adopting Microsoft’s Azure cloud computing services to gain insights from its clinical and genomic information through the use of artificial intelligence and machine learning tools.

In particular, UCLA Health is adopting Microsoft Azure as a standard platform to analyze its big data— both structured and unstructured—using predictive analytics to enable precision medicine through personalized treatments tailored for patients as well as disease prevention.

“Analyzing large data sets to make scientific discoveries is a race against time,” says Mohammed Mahbouba, MD, chief data officer for UCLA Health Sciences. “Using machine learning to analyze a combination of clinical and genomics data can provide critical insights, but doing so with a traditional computing infrastructure can require significant processing time. Azure enables us to quickly deploy and scale high-performance computing environments that can reduce the required processing time—sometimes from months to days—to make discoveries.”

Also See: Microsoft launches Azure API for FHIR to share data in cloud

In addition, the cloud-based platform is meant to accelerate medical breakthroughs by enhancing collaboration among researchers, while protecting and securing sensitive patient data—which will not be shared with Microsoft as part of the agreement.

“Another advantage of cloud computing is the way it enables UCLA researchers to more efficiently and securely work with their peers,” says Paul Boutros, director of cancer data science at UCLA Jonsson Comprehensive Cancer Center. “Cloud computing will allow researchers from different fields and institutions to collaborate, joining data sets and software from different formats that could not previously be integrated in a simple way.”

“We’re bringing together new communities of experts—including computer scientists, engineers, material scientists and others—to solve the biggest healthcare questions,” adds Boutros. “This platform allows us to provide our research collaborators with secure access to important data in one place, without moving sensitive, private health information.”

In 2017, UCLA Health and the David Geffen School of Medicine created the UCLA Institute for Precision Health, whose mission is to support campus-wide research aimed at advancing the diagnosis and treatment of disease. As part of that effort, the institute has launched the ATLAS program to recruit and genotype 150,000 patients across UCLA Health, leveraging both clinical and genetic data as a resource for researchers to develop and validate prediction models for personalized medicine.

The goal is to generate a genetic map of UCLA patients, enabling researchers to discover new risk factors for diseases and to tailor the appropriate treatment to each individual patient.

“Our data capabilities with Microsoft Azure will bring more medical discoveries and effective therapies to patients faster,” says Michael Pfeffer, MD, assistant vice chancellor and CIO for UCLA Health Sciences. “The integration of information from structured data, like lab results and medication information, with unstructured data, like documentation, genomics and medical images, creates an incredibly powerful big-data learning platform for discovery.”

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