Science & Tech

Big Data, Major Health Care Advances

How the Texas A&M Health Science Center leads the way in biomedical informatics.
By Christina Sumners, Texas A&M Health Science Center December 11, 2015

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A unified biomedical informatics program is essential for clinical research.

(Zedge)

All of the tweets and text messages sent every day. All of the data collected by the millions of wearable fitness trackers. The billions of base pair sequences that make up our genomes—and the genomes of the trillions of tiny creatures that live inside us.

Alone, all of this data might not mean much, but when it is analyzed into information, and that information into knowledge, discoveries can be made that improve health, both individually and in a population, whether it is finding a link between heartburn drugs and heart attacks, possible hereto-unknown drug interactions, or molecular similarity between a skin disease and Alzheimer’s.

Turning raw biomedical data, especially so-called “big data,” into information and eventually into knowledge is the interdisciplinary science of biomedical informatics. At its core, biomedical informatics is using systematic rigor to employ techniques that transform data into meaning and meaning into knowledge, as applied to problems of biomedical interest such as individual health, public health and biomedical research.

At the Texas A&M Health Science Center Biomedical Informatics Center, led by Jack Smith, M.D., Ph.D., researchers are examining these areas and more. A unified biomedical informatics program is essential for clinical research, according to David Huston, M.D., a practicing immunologist who leads the Texas A&M Clinical Science & Translational Research (CST*R) Institute, which is why the center is a key part of the CST*R Institute.

“Biomedical informatics is a discipline critical for enabling precision medicine and advancing clinical and translational research, which is increasingly data intensive, and requires collaboration across many communities, including health care, research and public health,” Huston said. “Translational research, or moving a new therapy from the laboratory to widespread clinical use, can greatly benefit from biomedical informatics.”

“What researchers like myself do is look at how information systems can help people make better decisions at each stage of the clinical trial process,” Smith said. “It’s always a combination of doing a better job of analyzing the data, and, increasingly, that involves integrating information in journal articles, online knowledge bases, and other materials that go beyond pure data.” Algorithms can be written to “scrape” much of this information automatically. This process can help detect potential problems with drugs or other interventions before they get any further in the clinical trials process. Smith wants to create generalizable solutions/tools to biomedical informatics problems in translational science.

Continue reading on Vital Record.

This article by Christina Sumners originally appeared in Vital Record.

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