From left: Moderator Sean Rooney, a partner with PwC; Dr. Virginia Calega of Independence Blue Cross, Jonathan Hirsch of Syapse; Gaurav Singal of Foundation Medicine; and Yirong Wang of Mount Sinai Medical Center.
Precision medicine may be the key to revolutionizing cancer treatment, but for the excitable among us, a good (and necessary) bucket of cold water was splashed onto anyone dreaming of a medical metamorphosis in cancer care.
Significant hurdles in healthcare costs, training, and data collection must be cleared before precision medicine is able to transform treatment for cancer patients, according to participants in a panel discussion during the MedCity CONVERGE Conference in Philadelphia this week. The topic, in case you haven’t guessed already: What’s holding back precision medicine?
With the Rise of AI, What IP Disputes in Healthcare Are Likely to Emerge?
Munck Wilson Mandala Partner Greg Howison shared his perspective on some of the legal ramifications around AI, IP, connected devices and the data they generate, in response to emailed questions.
Being able to pull data from electronic medical records and thread it together in a workable, comprehensible way, for one.
“There’s a tremendous data liquidity issue in healthcare that’s exacerbated in this space,” said Jonathan Hirsch, founder and president of San Francisco-based Syapse, makers of a precision medicine data platform that allows for molecular profiling of patients. For precision medicine to make its mark, the “fundamental core infrastructure problem” of good data collection has to be solved, he added.
It’s a point that was echoed by Dr. Gaurav Singal, who serves as vice president of data strategy and product development at Foundation Medicine in Cambridge, Massachusetts.
“Messy data in the clinical world is still a problem to solve,” Singal said.
A Personalized Approach to Medication Nonadherence
At the Abarca Forward conference earlier this year, George Van Antwerp, managing director at Deloitte, discussed how social determinants of health and a personalized member experience can improve medication adherence and health outcomes.
Tailoring data to the individual — distilling it down from the population level, in other words — is what’s necessary for precision medicine in oncology care, but it’s still a challenge. More than three-quarters of cancer patients in the U.S. get their treatment at community practices, which often don’t have the same abilities as major academic medical centers to really target patients’ tumors’ unique genetic backgrounds. It’s a problem that John Quackenbush, director of the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute, also explored in a morning keynote at the CONVERGE conference.
Of course, having the data is one thing, while incorporating it into policies that insurance companies have is another. For insurance companies, data from precision medicine treatment in oncology needs to be translated into actual patient outcomes.
“We need real-world evidence that [precision medicine] really changes outcomes,” said Dr. Virginia Calega, the vice president of medical management and policy at Independence Blue Cross.
Toward the end of the panel discussion, Yirong Wang, director of production bioinformatics at the Icahn School of Medicine at Mount Sinai in New York, provided what might be the biggest challenge to overcome: proper training.
In bioinformatics, a realm Wang knows well, the workers of today are still in “research mode,” he said. What’s needed is a dual mentality, one that also takes into account that mindset of engineers and others who know how to pull precision medicine into the real-world.
“I still strongly believe that the training we have nowadays is not providing us the right talent to move faster,” he said.
