Cancer is one of life’s perpetual foe’s. For many of us the disease has either affected us personally or a member of our family. Within cancer treatment there is a lot of emphasis placed on catching the root of the problem quickly so that it doesn’t spread. Unfortunately for doctors, this early detection often requires the patient to be alert and ultimately aware of the ominous signs that cancer can bring. For patients, this is the real-life equivalent of walking a tight rope - but do analytics have the capacity to reshape the way we think about cancer prevention? According to Jennifer Quigley, Director, Registry & Bio Repository, they most certainly do and she is unequivocal in her assertion that cancer care and analytics can work in perfect unison together.
At the Big Data and Analytics for Pharma Summit in Boston, Jennifer gave us a heartfelt account of cancer care from both the perspective of a data enthusiast and someone who has been deeply affected by the damaging consequences of the disease. She expresses a desire “to put names to faces as people often get lost in science and data”. A pictorial montage was shown to the audience of Jennifer’s friends and family who had either passed away or suffered from cancer at some point. It’s clear to see why Jennifer is so passionate about the prevention of cancer and ends this part of the presentation by stating; “it’s [cancer] emotional tool is immeasurable and as an economic tool it’s staggering as well”
Jennifer objective is simple and it can be articulated in six words - to improve cancer care and medicine. It’s a simple concept, but one which is multilayered and surrounded in apprehension and confusion from the sufferers. For Jennifer, continually improving upon and developing cancer care should have data at its heart. She says; “it’s not a product or a program or even a study, it’s simply an idea - but it will require co-operation and collaboration across organisations”
In a nutshell, cancer can be described as an uncontrolled growth of cells, but that is a very sweeping definition - in reality every cancer case is unprecedented and unique to the individual. In order to counteract this uncertainty, Jennifer has put together a proposal which she feels will benefit cancer care greatly and she was more than willing to share it with us at the summit.
The principal of the project is to collect patient data from pre-treatment and pre-diagnosis to diagnosis to the end stage. By aggregating this data and coupling it with clinical and diagnostic data - predicting cancer in a patient can become more feasible. The reason why predictive analytics are so imperative for the improvement of cancer treatment is because no two cancers are alike - they may well be categorised as the same, but like humans every cancer is unique, but we have similarities that allow us to be categorised and understood. Jennifer states “no longer is stage 3 colon cancer the same in every individual”.h
In an interesting twist, Jennifer points her attention to Target, the U.S. retailer. She refers to an article written by Charles Duhig a Journalist at the New York Times who wrote about how by using extremely extensive data gathering techniques, the supermarket found out a girl was pregnant before she even knew herself. This story is often mentioned and heralded by Big Data pessimists as a step to far for our privacy, but whether you agree with Targets operations or not, if it were transferred to cancer prevention it could be a game changer. Imagine if data could predict when someone was most likely to be hit with cancer and the implications that would have for their health and continued cancer care.
The longitudinal data process that Target implements could be used for cancer care. Clearly it’s easier said than done, but the collection of patients characteristics, demographics, medical history, locational data, molecular and genetic data is already happening and could create predictive algorithms. As Jessica states; these predictions could be the catalyst for a discovery or a road map for successful studies and trials - but first the ground rules need to be laid. Data collaboration must include structure to normalise data and a way to match records and protect the patients PHI - this must also include health organisations labs, hospitals and clinics collaborating to make sure data is correct”
With the amount of data coming at us rising exponentially, the time is now to invest in healthcare analytics. As Jennifer states; “there has been an explosion of testing that is creating a lot of data - if we are to realise potential this has to be started today”. Perhaps Target have influenced one the major breakthroughs in cancer prevention, but whatever the outcome, Jennifer’s data-centric ideas are both refreshing and exciting for the people who are affected by cancer everyday.