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Oregon Health, Intel Partner on Genome Analysis Computing

Joe Gray (Oregon Health and Science University)

Joe Gray (Oregon Health and Science University)

Oregon Health and Science University in Portland and Intel Corporation are developing new computing technologies to increase the speed and precision of analyzing a patient’s genome, while reducing their time and cost. Financial aspects of the multi-year collaboration were not disclosed.

The agreement calls for engineers and scientists from Oregon Health and Intel to develop the equipment, software, and workflows to cope with the large volume of complex biomedical data generated by analyzing a human genome. That kind of large-scale analysis is needed to create individual genetic profiles that can advance peronalized medicine.

The partnership plans to harness Oregon Health’s experience in imaging and analyzing the molecular-level factors behind cancer and other conditions. That work from Oregon Health’s Knight Cancer Institute can produce a detailed map of cancer cells and their changes over time, as well as a higher-level view of the overall cellular system’s behavior.

By comparing an individual patient’s genome with the map of a healthy genome, scientists can study the patient’s genetic abnormalities to determine those linked to cancer. The computing power needed for this analysis, however, calls for clusters of supercomputers and customized algorithms to decode the complexity of human genetic variation.

Intel is expected to provide its expertise in entreme-level computing in a research data center equipped with an Intel supercomputing cluster that brings together computer scientists, biophysicists, geneticists, bioinformatics specialists, and biologists. The Oregon Health/Intel researchers aim to create informatics tools to handle the high volumes of data generated in the process, but performing those functions faster, more precisely and at lower cost than with current technology.

Joe Gray, who directs Oregon Health’s biomedical engineering department calls the task “an enormous analytical challenge that is beyond the capability of current technology.” Gray notes that the combinaion of “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.”

The team plans to begin with genetic profiling of patients’ tumors to look for patterns of disease progression and to connect this information to treatments for those tumors. This task aims to reduce the time and cost needed to analyze a single patient’s cancer profile, from weeks and many thousands of dollars to a matter of hours at a cost that is feasible for clinical applications.

Gray believes the team’s initial work will offer lessons for other conditions, adding, “along the way we expect that what we will learn in studying cancer will also provide insights into other complex diseases.”

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