OHSU, Intel Team on Personalized Medicine Initiative
Oregon Health & Science University (OHSU), a research university in Portland, Ore., has announced a new partnership with Intel to develop computing technologies that will aim to advance the field of personalized medicine. The technology will look to increase “the speed, precision, and cost-effectiveness” of analyzing a patient’s genetic profile, as engineers and scientists from both institutions will work together on the multi-year project.
Specifically, according to the OHSU press release, the collaboration will use Intel’s capabilities in data computing with OHSU’s imaging analysis of drivers of cancer and other diseases, which details how cells change over time at the molecular level. With this combination, the two hope to create information tools that can handle the amount of data generated in this process to gain a better understand genetic origins of illnesses like cancer. Ultimately, it hopes to discover a way to make “precision medicine a more routine model of patient care.”
“To make a real difference for cancer patients, we need to know more about how the disease functions over time and within the body’s multitude of systems. That represents an enormous analytical challenge that is beyond the capability of current technology,” stated Joe Gray, Ph.D., associate director for translational research at OHSU’s Knight Cancer Institute.
“By combining Intel’s computing expertise with what we know about how to analyze genomes and to create images of how cells change over time, we believe we have the capability to develop the right tools to make significant progress in making the promise of personalized cancer medicine a reality for more patients.”
Personalized medicine ventures of this ilk have begun to pop up across the country. Recently, the Mount Sinai Medical Center, the New York City-based 1,171 bed tertiary- and quaternary-care teaching facility, announced it's creating a new data management and analysis platform to give doctors real-time therapeutic and diagnostic guidance based on the patient’s genetic profile.
