"We need data shared securely in a way that accelerates our ability to do analytics and get treatments to patients," he adds. "We need a future where this becomes much more commonplace. Imagine where we'll be in 2020. Instead of two percent of patients getting sequenced, it will be 10 percent, 20 percent, maybe even 100 percent. All in one day."
Intel and the Knight Cancer Institute will launch the Collaborative Cancer Cloud and expect two new institutions to come on board by 2016.
"And from there, we can open up this federated, secure Collaborative Cancer Cloud network to dozens of other institutions — or let them create their own — to accelerate the science and the precision treatment options for clinicians and their patients," Dishman says. "They can also apply it to advance personalized research in other diseases that are known to have a genetic component, including Alzheimer's, diabetes, autism and more."
Each partner will maintain control of its patients' data, Dishman explains. But the federation will allow the shareable cancer treatment knowledgebase to grow in availability. Essentially, rather than transporting massive volumes of data, the Collaborative Cancer Cloud will allow clinicians to run analytics on all of the data where it resides.
The power of data
"We want to help harness the power of that data in a way that benefits clinicians, researchers and patients with a better knowledgebase and preserves security and privacy," Dishman says. "By securely sharing clinical research data amongst many institutions while maintaining patient privacy, the entire research community can benefit from insights revealed in large data cohorts."
As a complement, Intel plans to deliver open source code contributions to ensure the broadest developer base possible is working on delivering interoperable solutions. Dishman says open sourcing the code will drive both interoperability across different clouds and allow analytics across a broader set of data.
"That to me is the real power of academics working with Intel," Druker says. "The analytics clearly have to be improved and sped up. As cancer biologists, we know what we have to learn from the data. Intel computer scientists can help us optimize the code and get to more efficient analyses."
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