May 2, 2016

OICR joins the Collaborative Cancer Cloud

A connected cloud - decorative.

On March 31, Intel Corporation and the Knight Cancer Institute at Oregon Health and Sciences University announced two new leading cancer centres have joined the Collaborative Cancer Cloud (CCC): Dana Farber Cancer Institute and OICR.

The CCC is a distributed precision medicine analytics platform that allows institutions to securely share and analyze large amounts of data while also preserving patient privacy and security. The CCC will make it easier, faster and more affordable to determine how genes interact to cause disease in individual patients.

The long-term goal of the project is to reduce barriers to big data and make precision medicine more widely available to patients.

The CCC is unique in that it combines the benefits of cloud computing, such as scalability and security, with the advantages of local control of data. This ensures each institution is able to maintain proper custody of its datasets and protect patient privacy and any institutional intellectual property that may result.

Dr. Paul Boutros

Dr. Paul Boutros

“To understand the causes of cancer and to develop more effective methods of prevention, detection and treatment, cancer researchers need access to rich molecular and clinical data sets,” Dr. Lincoln Stein, Director of the Informatics and Bio-computing Program for OICR, said in a statement. “However the information is often siloed and unmanageably large, rendering it effectively inaccessible. Projects like the Collaborative Cancer Cloud overcome the barriers to working with these data sets by allowing multiple institutions to pool their data and to provide researchers with the computer power needed to work on the data remotely.”

Dr. Paul Boutros is the OICR lead for the CCC project.

OICR will initially work with Intel and the two other cancer institutions to develop genomic pilot projects based on industry-standard tools and will identify novel analytics approaches using machine learning techniques against a collective set of molecular and imaging data. This will be done to support big data analytics in a federated, aligned environment. But eventually the goal is to have dozens of institutes involved in the project increasing its scale and, by extension, its potential benefit to patients.