Expanding Data Sharing is Imperative to Expanding Access to Quality Cancer Care


By Jonathan Hirsch


It’s common to hear that cancer care is in the midst of historic change. It is true: in 50 years, when books are written about the progress against cancer, we’ll look back on this period as a historic time of rapid and accelerated progress. We are changing the way cancer patients are diagnosed and treated. Patients now have access to comprehensive molecular profiling, illuminating what makes each patient’s tumor unique. Patients can now receive new therapies, targeted based on their molecular profile, and harnessing the body’s own immune system. These therapies are rapidly coming to market thanks, in part, to efforts to learn from the “real world data” about prior cancer patients’ experience.

This new type of care — precision medicine — has provided better outcomes for tens of thousands of patients. Yet precision medicine is still only reaching a fraction of the patients who could benefit from this approach.

Our current healthcare system is not set up to treat each cancer patient based on the unique characteristics of their disease — we are not set up to fully scale precision medicine. This access problem can and should be addressed now, and we at Syapse plan on addressing it through data sharing.

Bringing precision medicine cancer care into the community

At its core, precision medicine segments patients into smaller and smaller populations, seeking to match the right treatment to the right population of patients based on their clinical and molecular profile. 

In pursuit of practicing precision medicine, oncologists are increasingly ordering molecular testing for their patients. When the results come back, the oncologist is left with the seemingly herculean task of sorting through the complexity of the molecular results, putting those results into the context of the patient’s clinical profile, and attempting to make the best treatment recommendation for the patient. 

This is where the key challenge of precision medicine arises: as we uncover the molecular and clinical variations between patients, we are trying to match patients to therapies that were studied in clinical trial populations that no longer resemble the patient we are trying to treat. This is no surprise — with the massive variability in the tumor genome, it is not going to be possible to run randomized controlled trials on all combinations of molecular and clinical profiles. 

In this complex environment, how is an oncologist able to determine which treatment may work for their patient, and which treatments may not work? 

In tertiary, specialized academic cancer centers, sub-specialist oncologists have the benefit of seeing enough of a volume of rare cases, and significant time to engage in research in their sub-specialty. This allows the academic oncologist to build up knowledge to pattern match: when they see a patient in their sub-specialty, they rely on their extensive knowledge built up through their academic pursuits to be able to put forth an educated hypothesis about the treatment that may work. 

This is where the access issues arise. Academic cancer centers see only 15% of cancer patients in the US. The rest are treated in community settings, primarily non-academic health systems. 

So, how do we go about empowering non-academic oncologists to perform this same pattern matching on the treatments that may work and may not work for patients based on their clinical and molecular profile? The answer is in building a large data set of the real-world experience of cancer patients, shared across health systems. 

The data exist to do this, but are often siloed and often inaccessible to the oncologists who can use it. The good news: this challenge is solvable. We’ve been working on it for several years, alongside some of the brightest minds in cancer care.

Why data sharing is key to expanding access to precision medicine

To unlock data-driven precision medicine, an oncologist needs to be able to find patients who are similar, clinically and molecularly, to the patient they are treating today, and understand the treatments and outcomes for those similar patients. By learning from the experiences of all prior patients, oncologists will be able to make better recommendations today. The key challenge to realizing this elusive vision of a “learning health system” in precision medicine has been that the relevant population within a single health system is almost always too small to be used to inform a patient’s treatment, and may not serve patients from underrepresented communities.

Sharing data addresses this problem by expanding the data pool and breaking down the geographic barriers that many community health systems face when implementing precision medicine. A smaller community healthcare provider in Wisconsin, for example, may not have any records of what treatments worked for a 35-year-old female Asian nonsmoker with lung cancer and a specific EGFR mutation. However, if they could consult a larger pool of patients from health systems around the globe, they might find a number of matches, and use those insights to make better treatment decisions.

At the original 2016 White House Cancer Moonshot Summit, Syapse announced a national data sharing network to give health systems, for the first time, a platform to share real-world evidence at the point of care. With the Syapse Learning Health Network, an oncologist at one health system can receive — directly into her or his clinical workflow — insights into how similar patients at other health systems performed on different treatments, enabling better treatment decisions and better outcomes.

This would not have been possible without our health system partners, including Aurora Health Care, Catholic Health Initiatives, Dignity Health, Henry Ford Health System, and Providence St. Joseph Health, who answered the call of the Cancer Moonshot to share data.

Fortunately, as the use and awareness of precision medicine has rapidly grown, so has the willingness of the healthcare ecosystem to collaborate. We’ve seen proof of this in the tremendous growth of Syapse’s network in just two years. Since the 2016 Cancer Moonshot Summit, we’ve fulfilled our Cancer Moonshot pledge to onboard at least five new health systems within 12 months to our Learning Health Network.

Expanding data sharing with new health system partners

Among those working to find solutions is former vice president Joe Biden, who led the White House Cancer Moonshot in 2016. He has continued his leadership with the Biden Cancer Initiative and is convening the Biden Cancer Summit in Washington, DC, September 21, as a national call-to-action to take on cancer.

Data sharing has been a key focus of the Biden Cancer Initiative — as more providers share data and have more data to pull from, more people will have access to the best possible treatments.

Today we are delighted to announce that six new health systems have committed to sharing data upon joining the Syapse Learning Health Network — Ascension, Banner Health, Inova Health, LSU Health, OhioHealth, and Seoul National University Hospital. This expansion means that hundreds of thousands of new cancer patients each year will have better access to the best precision treatments, because their oncologists will have the data they need to make more informed decisions. The Syapse Learning Health Network is now bringing together data and physicians from 412 hospitals, and will impact 215,000 new cancer cases annually.

This expansion also means that the Syapse Learning Health Network is now international, serving patients and their physicians in both the U.S. and South Korea.

In addition, we’re announcing a commitment to data sharing with the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program, which will bring high-quality registry data to oncologists in Syapse’s network and enhance cancer surveillance efforts by providing data that is difficult to capture through traditional methods.

Vice President Joe Biden said: “We are at an inflection point in the understanding and treatment of cancer and are starting to break down barriers and change the culture in ways that are needed to deliver what patients deserve — a cancer research and care system that puts saving lives above all else. The commitments we have received, including the Syapse Learning Health Network, bring us closer to developing the right systems, the right culture to get us there.”

The next 12 months: Expanding the Syapse Learning Health Network

Over the next 12 months, we are committing to working with our new health system partners, along with the Network’s existing members, to make data sharing a reality in more communities and hospitals across the country, and internationally.

We will not stop there. In June, Syapse launched the Syapse Precision Medicine Council to give health systems a way to share not only data, but strategies and best practices for growing precision medicine programs in the community setting and demonstrating the value of precision medicine.

Members of the Precision Medicine Council represent a wide range of communities from around the world with diverse care needs. The inaugural members include some of the nation’s most advanced precision medicine programs: Aurora Health Care, Catholic Health Initiatives and Dignity Health (the Precision Medicine Alliance), Henry Ford Health System, Hoag Health Network, Providence St. Joseph Health, and Seoul National University Hospital. Syapse will host the inaugural event October 18-19 in San Francisco.

We are so close to treating more people with the treatments that are best for them, but more widespread data and information sharing is vital to truly expanding access to these therapies. I’m excited about the progress our health system partners have made, and I look forward to continuing our work with them to bring the best care to local communities.