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Fast Facts on Precision Medicine: Using Genomic Information to Boost Cancer Care

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People with cancer undergo various types of testing during their diagnosis and treatment. It’s common, for example, for tumor tissue that was removed during a biopsy or surgery to be sent for genomic analysis — a study of the tumor’s genetic makeup. Oncologists then use that information to help guide choices for therapy in accordance with national treatment guidelines. But what if experts could do even more with this type of data?

Precision Medicine at Work

“One of the major goals of Johns Hopkins’ inHealth Precision Medicine program is to study how we can harness data collected during routine clinical care, analyze it, feed our learnings back into the health care system and improve patient care,” explains Srinivasan Yegnasubramanian, M.D., Ph.D., director of Johns Hopkins inHealth Precision Medicine and co-associate director of precision oncology at the Johns Hopkins Kimmel Cancer Center.

“Genomic data is already being collected in clinical practice for patients with cancer and some other conditions,” he says. “By coupling that genomic data with other clinical, pathological and radiological data, we can better understand how we can guide our approaches to give the right therapy at the right time for the right person.”

Johns Hopkins clinicians use a number of platforms for genomic testing, including the JHGenomics Molecular Diagnostics Laboratory, that collect information on all relevant genetic mutations and variants found in patients’ tumors. A priority for the inHealth program has been to create a central data repository for analysis. Precision medicine researchers are working to take it a step further, to integrate these data with other deidentified clinical information from patients’ electronic health records. They are also working to incorporate pathology and radiology imaging data in the near future. 
The inHealth Precision Medicine program plans to engage expertise from across schools, centers and institutes at Johns Hopkins to use artificial intelligence, natural language processing and other advanced analytical approaches to help clinicians guide treatments, including:

  •  Providing patients with treatment and clinical trials options that match their clinical condition.
  • Analyzing mutations that might predispose certain people to particular cancer types.
  • Estimating treatment response based on a patient’s genomics and other health status.

The project will move forward in various stages, Yegnasubramanian says, with the first stage — a compilation of genomic data from over 15,000 patients who have undergone clinical genomic testing at Johns Hopkins — to be made available through the inHealth Precision Medicine Analytics Platform for research. Initially, it will be most relevant for cancer research because most genomic testing is happening in that field. “But the platform will ultimately serve all of the health system, because there’s going to be increased importance for this type of genomic data in all spheres of medicine,” he says.

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