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Ohio State, Cancer Center Partner on Research Database

Doctor with tablet

(HealthIT.gov)

28 May 2014. Moffitt Cancer Center in Tampa and Ohio State University’s Comprehensive Cancer Center in Columbus are launching a repository of patient data and tumor samples to speed development of therapies and better match patients to clinical trials. Financial details of the Oncology Research Information Exchange Network or Orien created by the collaboration were not disclosed.

Under the deal, de-identified clinical data from cancer patients will be combined with samples of tumors and bodily fluids not needed for care from the two institutions, and stored using Moffitt’s protocols. Ohio State will provide its expertise in translating molecular and genetic discoveries into better cancer prevention, detection, and treatments.

“Cancer is a highly complex disease, and potential breakthroughs have been stalled because we’ve lacked an efficient way to share incremental insights,” says Alan List, president of Moffitt, in a joint statement. “Even more frustrating, until today we’ve had no system to quickly match cancer patients from anywhere in the country with ongoing clinical research with the most potential to help them.”

Orien already has records on some 100,000 patients who gave their consent to be part of the database. The collection is expected to help cancer researchers identify new drug targets and candidates. Moffitt and Ohio State are seeking partners for further collaborations.

A key benefit of Orien, say the founding partners, is improved matching of cancer patients with clinical trials. The database is expected to provide clinicians with therapeutic opportunities, including clinical trial options, that better fit the patient’s genetic and molecular profile, leading to better outcomes and fewer adverse effects.

The matching of patients to clinical trials will be done by M2Gen, a for-profit subsidiary of Moffitt providing data management and informatics services. M2Gen identifies patients in the databases using its own algorithms for matching patients’ clinical and molecular profiles against a trial’s clinical and molecular eligibility criteria.

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