Personalized Cancer

Pete Celano,  3 June 2015


These are times of great invention in Cancer, largely around the notion of “fingerprinting” an individual tumor.

Subha Madhavan, Ph.D., Director, Innovation Center for Biomedical Informatics, Georgetown University Medical Center (@subhamadhavan), wrote eloquently on this subject in May, saying:

Personalized Medicine (or the newer term Precision Medicine) promises to revolutionize healthcare. The rush of innovation enabled by big data has made possible precision medicine, or the tailoring of medical treatment to the individual characteristics of each patient. Near daily discoveries of biomarkers, molecular profiling techniques, and the other tools of precision medicine have stimulated innovative research and inform regulatory decision-making about genetic diagnostic tests or specific treatments for patients with cancer, cardiovascular diseases, neurological disorders and other conditions.

The facts about Tumor Profiling are these–

  1. The cost to the patient (co-pay) of genetically sequencing a solid tumor has fallen by 10x in less than three years, thanks to innovative companies such as Caris Life Sciences of Dallas, Texas.
  2. There’s increasing evidence that targeting medications at what are called “Actionable Gene Mutations” improves Patient outcomes.
  3. Big Pharma is racing to create more “precision” drugs, which likely helps explain Roche’s billion dollar investment in Caris’ primary competitor, Foundation Medicine, in January 2015.

 mdandersonSOURCE:  MD Anderson Cancer Center

You’ve heard, perhaps, of the Network Effect.  Consider, then, what I call the Database Effect— if 10,000 U.S. patients have contributed their tumor profiling data, treatment plan and ultimate outcome (on a de-identified basis, of course), some amount of research on this dataset will yield “x” study results, that advances the current state of efficacious cancer therapy.

Now get that to 100,000 patients (about 6% of the new cancer patients per year in America), and the net research result might be far greater given the more meaningful data volume, such as 50x.  Get to 1,000,000 patients– might it then be a 500x effect regarding cancer treatment discovery, given the ineffable “n” of Sample Sets?

The intersection of Big Data + Tumor Profiling in Cancer makes the current era extraordinarily promising in terms of Patients living longer post-diagnosis.

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