Genomic Medicine Goes from Hype to Reality

Technology can play a major role in helping more patients receive breakthrough diagnostics and therapies for cancer and other maladies.

Consider the tumor. Once viewed as a uniform wad of deadly malignancy, it’s now known as a collection of diverse cell types, driven by a wide range of genetic mutations and cooperating in a complicated ecosystem.  

"There can be tremendous genetic diversity within a single tumor."

- Bryce Olson
Global Marketing Director for
Health and Life Sciences, Intel

"When more points of care have both genomic sequencing and data analytics at their fingertips, and a team skilled in the application of genomic methods in a clinical setting, more people will receive these new treatments.“

- Jennifer Esposito
Worldwide General Manager,
Health and Life Sciences, Intel

Stopping the “Cycle of Inaction”
First, providers and healthcare organizations can focus their efforts on areas with the biggest impact on care and where reimbursement is most likely. For now, that means primarily oncology, pediatrics, reproductive health, and pharmacogenomics, all of which have a larger known genetic component. Some EHRs have tools that can tell physicians which genetic tests are reimbursed and which require out-of-pocket payments from patients. As researchers continue to learn more about the genetics of other conditions, the list of high-impact areas will grow.

Organizations will also need to incorporate precision medicine into their governance bodies if they haven’t already done so. Making precision medicine a reality requires investment and likely major changes across the organization, including stronger collaboration among clinicians, pathologists, and medical tumor boards. Cross-functional executive support at all stages is critical to successfully implementing these changes.

With that executive-sponsored cross-functional team, the next step is determining the right approach and engaging the necessary partners, from sequencing to bioinformatics to clinical decision support, and deciding how much to do internally.

For example, smaller hospitals might work with a commercial diagnostic test company that handles all the sequencing, analytics, and clinical decision support tools to bring actionable data to doctors. A larger hospital may find it more cost-effective to have its own lab for genetic testing, with annotated test results delivered to physicians at the point of care. Given the size of that investment—including personnel trained in DNA extraction, sequencer operation, bioinformatics, genomic data analysis, and related aspects—that course may only make sense for larger organizations.

Ultimately, providers will expect infrastructure and tools that enable their EHRs to include a real-time interface with genetic databanks, as well as designated fields for genetic variant information to ensure genomic data isn’t relegated to easily overlooked text or comment fields. May organizations will also need more sophisticated algorithms and analytics to manage patients at the individual level.

"The size of genomic datasets doubles about every eight months."

- Erik Banks
Director of the Data Sciences
and Data Engineering group
at the Broad Institute

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