Health Technologies

How Technology Integration Supports Precision Medicine

Precision Health Can Be Applied to All Disciplines

The University of California, Irvine, has integrated its technology to create targeted health and wellness strategies for patients. In February 2022, the university launched the Institute for Precision Health, an interdisciplinary campuswide initiative to develop solutions in precision medicine. A future brick-and-mortar home for IPH will let data scientists collaborate with clinicians to develop analytics tools.

“Precision health is truly an amalgamation of multiple critical pillars. Understanding the multidisciplinary nature of this work is really how IPH came about,” says Dr. Peter Chang, ­assistant professor in residence at UCI’s Department of Radiological Sciences. He formed IPH along with co-director Leslie Thompson, a professor in the school of medicine and the school of biological science.

IPH’s launch was driven by a need to make sense of health data. It linked EHRs, genomics and other medical data with ML’s analytic power, Chang says.

UCI has made various investments in precision health analytics, including recently replicating its EHR system in Syntropy, a data management and analytics platform hosted in the AWS cloud. “It essentially gives us the flexibility and power to look at all of our data using sophisticated analytics in a very efficient way,” he says.

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Other data computing environments on the UCI campus borrow architecture developed at major technology companies, such as the Kubernetes orchestration engine that originated at Google, Chang adds. Combined with containerization technology, Kubernetes allows Chang’s team to easily orchestrate AI software development on a flexible, hybrid, on-premises, cloud-based computing cluster. The system is able to automatically scale computing resources, including specialized NVIDIA GPUs that his team leverages to train algorithms on high-dimensional data such as images, waveforms and videos. “Taking advantage of a hardware and software stack optimized by major AI companies allows our team to maximize our investment in computing resources and focus on our goal of realizing precision medicine,” Chang says.

As a radiologist, Chang relies on predictive modeling and data analysis for personalized treatment and health maintenance. “Whether in a research or clinical environment, the same key technology, such as NVIDIA hardware or cloud-native services, is driving AI innovation,” he says.

Chang believes healthcare is still in the early stages of precision medicine and making sense of analyzing the data in a sophisticated way. But the future means linking multiple types of data and using ML to make sense of it, he says. 

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