My father, Foster Hill, has stage III prostate cancer.

At 69 years old, he is a quiet man who was often told in his younger days that he resembled Muhammad Ali. He immigrated in his twenties to Canada from the small Caribbean nation of Antigua to look for opportunities beyond sugar cane and the tourism trade.

My father became a chemical technician for well-known oil refineries, while staying true to his real passion in life – playing organ music. Every Sunday, as he has since I can first remember, he plays the largest church organ in Sarnia, near Lake Huron, where he lives with my mother.

Like many men of his generation, he has always been wary for the medical system. For decades he avoided the test, known as PSA, that screens for prostate cancer. In September of this year, driven by pain he could no longer ignore, he went to his doctor who discovered a rock-hard prostate gland. The diagnosis, stage III prostate cancer, means that the cancer has already begun to spread, but is still potentially treatable.

Now retired, his long hours practicing the organ are punctuated with doctor visits to receive Lupron hormone therapy. The good news? The therapy is working. For now.

We don’t know what lies ahead. The first round of Lupron therapy is often effective, but a significant number of patients later develop a resistance to the drug.

The battle against my father’s cancer has only just begun.

This is where Big Data in healthcare can become a true lifesaver. Typically, in medicine, we know only what works for the majority of patients, not what will work for an individual. However, with enough data from enough people – we are talking hundreds of thousands, and sometimes, even millions of patients – we can apply analytics to build predictive models to discover which interventions will work. For the last twelve years, it has been my job to make that happen.

As CEO and founder of GNS Healthcare, I oversee a team of mathematicians, biologists, and data scientists as they crunch and decode healthcare data to unlock the mysteries of what treatment will work for specific patients.

My father’s cancer has given these efforts a new urgency and has raised a new question: Can I use Big Data to save my father’s life?

The stakes involved were made clear earlier this year when my cousin, T.D. Hill, fought stage IV cervical cancer and lost. My sharp-witted but reserved cousin, who had raised two boys while living with Multiple Sclerosis, passed away in March of this year. She was 43 years old.

It’s not too late for Big Data to help my father. One of my first steps was to arrange for a sample of his tumor to be genetically sequenced by the Cambridge, Mass.-based cancer diagnostics company, Foundation Medicine. The company delivered a report with treatment options based on the genetics of my father’s tumor and the most up-to-date science.

Our understanding of the biology disease has expanded greatly in recent years, and the new, targeted therapies are now available. We can no longer rely solely on a physician’s experience or a standard set of guidelines in making a decision about treatment. Instead, we need to identify the genetic markers that can be linked to drugs that have been known to respond to patients with those specific genetics.

Unfortunately, Foundation Medicine’s analysis found my father has a tumor with a genomic alteration identified as a TE2 truncation, which, according to their findings will not find a match for treatment in any of the currently approved therapies. But they did list two trial studies that may hold promise.

This type of analysis is limited by the data that is available today. In order to realize the goal of true personalized cancer treatments, much more data will have to be made available and paired with rich clinical information on the case histories of the patients from which the samples come. With more information and today’s cutting-edge analytics, we can not only create personalized cancer treatments, but also accelerate innovation, make treatments safer, and cut costs to fashion a more efficient medical system.

Building the kind of data set we need can’t be accomplished by any one company or government organization. It requires a unified effort to collect, store and make this data accessible. A central theme at the StrataRx conference, which I helped chair earlier this year, was how individuals – by collecting, owning and sharing their data – can help transform healthcare.

It’s time to band together in the name of Big Data in healthcare. My dad can’t afford to wait. None of us can.

Colin Hill is CEO of GNS Healthcare. This post was first published on Forbes.

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22 Responses for “Can Big Data Save My Dad From Cancer?”

  1. legacyflyer says:

    Hopefully, this experience will be a strong stimulus for you and your team to work hard on Prostate Cancer research.

    Good luck to you and your father. I wish you the best.

    Any thoughts on screening for Prostate Cancer using PSA? I know it is controversial topic right now.

  2. Congrats on your work at GNS — the type of analysis you’re doing will change the game in healthcare.

    Unfortunately, our publically funded research and clinical trial system (not even counting the privately funded pharma and device work) is holding back substantial amounts of real-world data that would accelerate the information we could utilize to make substantially better personalized treatment recommendations.

    Moves to open up this jealously guarded set of academic data are needed to accelerate the potential of big data in saving lives and reducing pain/ suffering.

  3. Rich says:

    Good luck on your research and hoping for the best with your dad. I think that with the more and more data collected we can find a way to beat this.

  4. lewesjoan says:

    Identifying a “druggable target” is only part of the equation. I think the big initial appliation for multigene assays like Foundation Medicine’s is using the information to develop enriched populations for clinical trials looking at how a particular agent works in a group of patients whose tumors are genetically likely to respond to a therapy that has either shown promise in preclinical testing or in a patient population with a tumor in a different site of origin but with the same genetic abnormality. Big Data may ultimately fill this gap, but I am not convinced that existing registry data is robust enough to support treatment decisions.

  5. pardeep rana says:

    Best PSA test for prostate cancer patients.

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