Precision Oncology Needs Data Sharing: Integrating Genomic and Clinical Data to Advance Patient Care

By Jonathan Hirsch, Founder & President, Syapse

In early 2015, a cancer patient I’ll call Mark was out of options. He was 55 years old, married with two children, and was being treated at a community medical center in the mountain states for metastatic colon cancer. In addition to failing multiple lines of standard cancer therapy, he also failed a new immunotherapy. A genomic test was performed on Mark’s tumor, and the results showed an odd signature of rare genomic changes in his tumor with no obvious matches to drugs for his tumor type.

Mark’s doctors had tried all of the standard treatments. Mark didn’t think he had any more options.

Breaking Down Silos

In oncology today, patient data is siloed and inaccessible. Within a healthcare system, critical information about a cancer patient’s family history, disease status, genomics, and treatments are locked inside difficult-to-access health IT systems, such as electronic medical records. Critical cancer data within these systems are often unstructured, or stored in formats that do not map to useful oncology standards. On top of that, cancer patient outcomes are rarely documented in any usable way. Healthcare systems are truly unprepared to deal with the enormous amount of cancer data they possess.

These challenges are made even worse when trying to share data across organizations. Different healthcare systems may adopt different data standards, or no standards at all, making it very difficult to harmonize information across healthcare systems. Even when healthcare systems want to share data with each other, the technology obstacles often seem insurmountable.

Because of this, oncologists are often left searching for information and answers.

It should not be this difficult for well-meaning people to do the right thing.

Patients like Mark remind me of why we started Syapse. A few years ago, when I was in graduate school at Stanford University, I saw many of these problems first hand. I saw critical patient data, such as genomic test results, being faxed from department to department within the hospital. And this was in the heart of Silicon Valley, where the world’s most innovative technologies were developed.

I couldn’t stand by and watch these antiquated systems deprive cancer patients of the best care, so I dropped out of graduate school to tackle these problems head on at Syapse.

Bringing Precision Medicine to Every Cancer Patient

Syapse is on a mission to bring precision medicine to every cancer patient throughout the country. We want every patient to benefit from treatment guided based on their full clinical and genomic profile, matching each patient to the right treatment at the right time based on robust evidence. This evidence should include the real-world information learned from the millions of cancer patients treated every year, information that currently is going unused.

It is only by learning from real-world patient data that we will make rapid progress in the fight against cancer.

To do so, we have to break down the data silos both within healthcare institutions and across them. Syapse has worked for years to develop our software, the Syapse Precision Medicine Platform, to accomplish this. Syapse software reaches into legacy systems and aggregates health history, medical records, cancer status, labs, radiology, pathology, molecular, genomic, and treatment data.

Using that fully integrated data, Syapse software provides clinical decision support personalized for each patient, notifying the oncologist and care team about treatment and clinical trials that might be applicable for the patient’s specific cancer. Our software also tracks the treatment decisions made, and what happens to the patient, including tracking patient outcomes and integrating those outcomes with the rest of the patient’s data to form a full, longitudinal understanding of the patient’s care journey.

Using a standards-based approach, we have created a foundational data model for capturing the entire cancer patient’s journey, and all of the health systems we work with have their data mapped into this model.

But what’s most important is that when patients receive their cancer care at a healthcare system that is partnered with Syapse, their doctors can use the data on past patients with similar cancers. They can see what worked and didn’t work in the past, and apply those results to the treatment of new patients. Even when a cancer is extremely rare, an oncologist may be able to match the patient’s tumor to a past case, enabling better, more targeted treatment.

This innovative treatment approach gave Mark new options. He was being treated at Intermountain Healthcare, a healthcare system that has worked with Syapse for 3 years on cancer precision medicine. That full 3 years of cancer genomics data was used to help Mark’s oncology care team pick the right therapy.

When Mark’s care team used Intermountain’s Syapse database to look at his specific tumor, they were able to find a set of patients whose tumors were genomically similar to his. Those patients had responded very well to an genomically-targeted ovarian cancer drug. The care team at Intermountain decided to put Mark on that drug, and this targeted therapy has stabilized Mark’s disease. This new treatment not only gave Mark options — it gave him the ability to gain precious time with his family. Mark has been able to watch his son graduate from high school, and watch his daughter get married. He is still doing well today.

Launching a Network

If data sharing within one health system could have such a profound impact on someone like Mark, what kind of progress can we make if all major health systems can access this kind of cancer data?

The only way to make faster progress in combatting cancer is to work across organizations to share data and learn together. Syapse is dedicated to working with many of the nation’s largest healthcare systems to make that a reality.

Intermountain Healthcare, Stanford Cancer Institute, Providence Health & Services, and Syapse have joined together to advance cancer care through data sharing and increase access to clinical trials. Last week, we officially announced the launch of OPeN, the Oncology Precision Network.

Responding to Vice President Joe Biden’s Cancer Moonshot Initiative, OPeN will share aggregated cancer genomics data through an advanced software platform, rapidly bringing the most promising treatment insights to cancer patients and physicians.

This unprecedented collaboration between two of the nation’s largest not-for-profit health systems, one of the country’s premier academic research centers, and Syapse, a leading precision medicine software company, aims to find breakthroughs in cancer care by leveraging previously untapped real-world cancer genomics data while preserving privacy, security, and data rights.

OPeN will provide access to precision medicine and clinical trials for previously underserved cancer patients. The vast majority of cancer patients are not treated by major cancer centers and don’t benefit from high volume based analytics. OPeN will help extend this knowledge to communities across the country.

When fully implemented, OPeN will impact 50,000 new cancer cases per year, representing three percent of the nation’s total; 200,000 total cancer patients per year; and have more than 1.5 million historical cancer cases. OPeN comprises data and physicians across 11 states, 79 hospitals and 800 clinics.

Not only that, but the OPeN database is live today!

OPeN has approximately 100,000 data sets in the OPeN database.

The purpose of OPeN, is to, well, be open! OPeN hopes to include other health systems later in the year, with the long-term goal of impacting cancer care across the United States.

With the launch of OPeN, we believe that cancer care will fundamentally change. No longer will technology get in the way of a physician or a medical system doing the right thing for their patients, which is to share data to improve care for all. And no longer will patients like Mark run out of options when traditional treatment fails.

Integrated clinical, genomic, and treatment data that oncologists can use to find the right treatment for their patient.
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