A New Hippocratic Oath – Do More Good (With Data)
It’s a sad fact that nearly everyone has known someone who has had cancer, or has had it themselves. Anyone who has watched a friend or loved one battle this relentless disease knows how scary and difficult it can be to find the right treatment. With 1 in 2 men and 1 in 3 women in the United States developing cancer at some point during their life, according to the National Cancer Institute, inventing new cancer treatments is appropriately a top priority in the medical and pharmaceutical research fields. While there are a lot of moving pieces in this research, one indispensable part is patient data.
Almost a year ago, my dear friend Chris Battle lost his fight against kidney cancer, which is a particularly vicious and difficult-to-treat form of the disease. I saw Chris, along with his wife Dena and their families, search year after year for a drug treatment that could do anything to slow the growth of the cancer inside him. It was a search that they shared with complete humility, candor and more often than not, side-splitting laughter on their blog, the Kidney Cancer Chronicles. When treatments on the market did nothing, he moved on to clinical trials, where new drugs are tested. Some drugs were able to at least hamper the march of cancer through his body but just long enough to raise everyone’s hopes that finally Chris had found something that worked. Ultimately, he did not.
I’m not alone in saying that Chris did more in his four decades than most people could do in two lifetimes. His humor, his writing and the steps of his life still echo for those of us privileged and honored to call him our friend. While he is physically no longer with us, there are many ways we see Chris’ life continuing – most notably in his two beautiful daughters, Kate and Josie. There are other ways his contributions to the world live on, and one less obvious legacy is his data – the way his body reacted to the various treatments he tried. While the clinical trial drugs did not help him survive his fight the way we all wanted, he helped the clinical trials, adding his own data points to the larger picture of which drugs worked and why. Even now, this information is telling researchers something about how cancer interacts with specific pharmaceutical compounds. With more data, researchers can extrapolate new findings, refine treatments, and ideally, evidence that a drug is ready for market and its life-saving purpose.
Since data leads to better treatments, and better treatments save lives, more and better data means more and better life. Clinical trials in particular demand data, but as drugs become more targeted, researchers are increasingly challenged to find a sufficient number of people to take part in the studies. Some 15% to 20% of clinical trials never enroll a single patient, and more than 80% fail to meet enrollment deadlines, which dramatically delays testing and development. This challenge of finding patients is in part due to the limited number of potential participants: just 4% of cancer patients ever join a clinical trial.
There is also a cost consideration for clinical trials. While there is no price on human life, there is a massive price tag on taking a treatment from concept to market. If it fails in clinical trials for want of patients and data, a $100 million drug research project can come to a grinding halt. This means money and time wasted, to say nothing of the fact that the treatment might actually work, if but only researchers could generate enough data to statistically prove it.
As in so many other industries around the world, data-driven research and innovation is helping improve clinical trials, and by consequence, human life. Numerous companies have formed to answer some of healthcare’s most pressing challenges with data (in no small part because of the massive economic potential in healthcare analytics, expected to grow $10.8 billion by 2017). For clinical trials, there are several ways Big Data are helping evaluate potentially life-saving treatments.
Recognizing the need to find and increase the number of clinical trial participants, PatientPoint Outcomes Research Solutions uses data to quickly and efficiently search through patient records.
"[Traditional] recruitment methods typically include clinic staff poring through paper clinical charts page by page to identify patients that may meet the trial eligibility criteria,” said PatientPoint President Lisa Griffin Vincent. “Access to big data can transform and accelerate the clinical trials process if leveraged in the right ways."
This is a boon to researchers as well as patients. Watching Chris and his family hunt for kidney cancer treatments, it was evident just how much work was done on the patient side simply to find a relevant study. Big Data can make it easier to match new treatments with the people who need them and when that happens, even more good can happen.
Aggregating Trial Data
Even after searching patient lists, in some cases, there simply are not enough people available to test a highly targeted and complex treatment. Yet, there is already so much data from previous studies that, when aggregated, may hold insights relevant to a separate study. The data company M2Gen collects clinical data and feeds it into a searchable database that can be used to advance research and expand pools of patient information. Mark Hulse, CIO of M2Gen parent company Moffet Cancer Center, said:
“There aren’t a sufficient number of patients in total. You need to combine data from many institutions… If we can mine the data in the right way, it’s good on the patient side because it can get drugs to the market much faster, and it’s good on the business side because it saves the pharmaceutical companies money.”
Data can also help save money by advancing clinical trials and by refining how the trials are conducted. A recent Tufts study found that up to a quarter of all clinical trial tests and procedures are unnecessary, wasting between $3 billion and $5 billion every year. Tufts researchers mined the company Medidata Solutions’ clinical trial cost database to determine how much was spent on “non-core” procedures (i.e., those that are not relevant to the specific goals of a clinical trial). It is these kinds of data-driven insights that can help researchers improve clinical trials and through that, save or improve more lives.
Finding New Correlations
Discovering a new treatment does not always mean inventing a new drug. Sometimes medicine that is already on the market is found to have benefits for treating other diseases. For example, it was genomic and medical data that suggested to researchers that a 50-year-old antidepressant (desipramine) could have an impact on small cell lung cancer. This led to a currently ongoing clinical trial in which the data-based hypothesis is being tested. A big benefit of this so-called “drug repositioning” is that treatment has already passed safety testing, which accelerates trials on the road to patient treatment and to the marketplace.
In these ways, data is contributing to better and faster drug development, which can mean the difference between life and death for people fighting today and those who will fight in the future.
It’s not even debatable that medicine has come a long way since the origin of the Hippocratic oath (i.e., “do no harm”). Today, a new oath may be: “do more good.” Data makes this possible, and in many ways, we have people like my friend Chris and millions of others to thank for all this information and new possibilities, which might someday save a life. That life could be someone you know and love or even be your own. Regardless of whose it is, it’s one more reason to say another “thank you” to a man I and many others miss and were honored to have as part of our lives. His name is Chris Battle and his life is making a difference today so that our tomorrows are better and brighter.
That’s a helluva legacy to be proud of but if you knew Chris Battle, you’d know his contributions have no end and will always make a positive difference to the world.