Cancer therapies based on a highly sophisticated understanding of individual genetic profiles have long been the promise of precision cancer care. Thanks to rapid technological innovation, the tireless efforts of researchers, and selfless participation from those diagnosed with cancer, precision medicines that dramatically improve treatment outcomes and quality of life have become a reality for countless cancer patients around the globe. However, we’ve only just begun to realize the full benefits of personalized medicine.
There are numerous technological, structural, and legislative obstacles to overcome in the effort to improve precision medicine and make it the standard of cancer care. However, perhaps the most immediate and pressing challenge is in addressing disparities in how data is aggregated, standardized, shared, and analyzed. Big data enabled by technological innovation holds the key to better understanding cancer and driving discovery. Making the best use of this data will require leaders in bioinformatics to establish novel paradigms and rethink how data can be applied on a large scale to address healthcare’s most important mysteries.
As an oncology-focused health informatics solutions company, M2GEN is playing a critical role in advancing precision medicine. Our mission is simple: to facilitate the development of revolutionary cancer therapies. We are achieving this mission by partnering with the Oncology Research Information Exchange Network®, an alliance of the nation’s top cancer centers. Our role is to provide researchers with the bioinformatics tools, data, and molecular pipeline analytics services they need to drive greater scientific collaboration, accelerate discovery, and expedite the time to market for life-saving therapies.
Q&A With M2GEN’s Chief Data and Analytics Officer
Dr. Daniel Elgort, PhD, recently joined M2GEN as Chief Data and Analytics Officer, arriving with a depth of unique experience that will be indispensable in advancing M2GEN’s mission of making better use of data in oncology research.
Following his academic studies, Dr. Elgort began his career in corporate research, focusing on the development of novel diagnostic technologies with Philips. He saw exciting opportunities for innovation in big data analytics as the field began to take shape in the early 21st century. After transitioning into a new role, he soon became the Global Lead for Healthcare Data Analytics Research, where he worked with large healthcare systems around the world to better understand critical aspects of patient care, including treatment outcomes and resource management.
Having worked at Philips for 11 years, he pursued new challenges and transitioned to a role as Chief Data Science Officer with Covera Health. Working in partnership with a coalition of radiology providers, Covera Health sought to leverage data sharing, aggregation, and analytics to better gauge, and ultimately improve, quality of care for patients.
Dr. Elgort’s six years of experience building relationships with healthcare providers to work toward a shared vision of using data to improve patient care was an excellent foundation for his work with M2GEN.
“It was important to see what can be achieved by aggregating data that speaks to the care that patients are receiving and the outcomes they’re experiencing,” Dr. Elgort said.
“Working in partnerships to better aggregate and standardize data at scale across large patient populations allows researchers to perform powerful analytics and gain deep insights that aren’t possible for individual healthcare providers to achieve on their own.”
Dr. Elgort recently took the time to speak about how M2GEN is positioned to help researchers unlock the full potential of oncology data as well as his vision for the future of the company.
Q: What makes M2GEN a leader in bioinformatics today?
A: Two important factors that I think make M2GEN stand out are its partnerships with research-oriented cancer centers and the way the company explicitly engages with patients at those cancer centers. By building partnerships with cancer centers that focus on oncology research, we are well positioned to not only generate, aggregate, and standardize critical data but also better understand which data elements need to be prioritized for inclusion in an integrated, longitudinal clinical and genomic dataset.
This is useful in creating datasets that can be made available commercially to pharmaceutical companies for important work, such as drug discovery. But just as importantly, it creates a centralized, standardized store of data that our network of cancer centers can leverage for both for academic research and for supporting patient care.
As the operational engine of ORIEN, M2GEN plays a central role in facilitating the collaboration and data sharing critical to discovery. As Dr. Elgort says:
Without M2GEN, the coalition of cancer centers don’t have an effective way of collaborating and sharing data with each other. It’s a very difficult technical and administrative process, especially when you consider that data is being shared among dozens of institutions, all of which have their own way of generating and recording data …
Dr. Elgort goes on to say that the benefits of partnering with M2GEN extend beyond access to a rich source of standardized oncology data.
One of the key benefits that cancer centers derive from partnership with M2GEN is having an established forum that allows for inter-institution collaboration. We help facilitate and manage research interest groups, annual scientific conferences, and a number of other forums that encourage interaction and help researchers identify collaborators …
Ultimately, all research initiatives share a common goal: to improve care and outcomes for cancer patients. Dr. Elgort elaborates on how M2GEN facilitates the shared interests of researchers and patients:
As a core part of our process, we ensure that we get informed consent from each patient whose data we intend to include in research datasets. This gives us more flexibility with the kind of information we’re able to capture and allows us to implement protocols to follow patients throughout their cancer journey, collecting valuable data, such as genetic sequencing information, at multiple points.
We also have the opportunity for more substantial engagement with patients, so they have the potential to benefit from the research they are participating in. For example, we can connect patients to clinical trials.
Q: What advancements can we expect to see in the field of oncology focused bioinformatics?
A: Technology will continue to advance. In the case of Next-Generation Sequencing, I think we have every reason to expect to continue seeing higher throughput and higher data quality as well as lower costs that allow it to be used even more in the context of clinical care and oncology research applications.
There’s also a proliferation and expansion in the kinds of information we can generate using these technologies. In addition to looking at the genome, we are producing additional data about protein expression, genetic pathways and metabolism patterns, and a myriad of other ways in which cancer tissue is different from healthy tissue. We can also better understand what’s happening in the local environment around the cancer tissue, beyond just the cancer cells. Especially in the case of solid tumors, we are beginning to generate critical data revealing the extent to which patients’ immune systems are infiltrating the cancer in the tumor’s microenvironment …
Of course, gaining deeper insights into cancer will require more than generating novel data. Researchers will also need new ways to discern which data warrants inclusion in clinico-genomic datasets and aggregate, standardize, and analyze this information. Dr. Elgort goes on to say:
Advancements in cloud-based advanced analytics infrastructure and analysis methodologies are enabling evermore powerful insights to be generated from this increasingly rich data about cancer. This is the kind of trend that enables new paradigms of analysis. These insights will enable researchers and doctors to differentiate between cancer patients in much more sophisticated ways than has been previously possible. This will in turn accelerate the drug discovery and development processes and enable oncologists to more effectively identify which therapies are going to be successful for a given patient.
Q: What challenges need to be overcome in bioinformatics to advance the cause of precision medicine?
A: A critical step in the path to get from where we are now to the future, with more effective cancer therapies available and improved ability to identify the therapies that are going to work for a given patient, is the actual creation of high-quality, large-scale, longitudinal clinico-genomic oncology datasets.
It is complex and difficult work to extract the required longitudinal data from a large population of cancer patients. It not only requires interacting with a large number of diverse healthcare providers, each with their own administrative procedures and electronic medical record systems, but also engaging with patients to get permission to use their medical data. Generating the linked clinical and genetic data is similarly challenging, requiring novel processes to be developed that enable aggregation and standardization of clinical and genetic testing results as well as new dedicated processes that bring cancer patients’ tissue specimens through custom Next-Generation Sequencing and analytics pipelines …
Developing leading-edge clinico-genomic datasets means identifying novel information that has not been available for analysis to this point. Working in uncharted territory presents its own challenges. As Dr. Elgort states:
There is no established consensus on what types of data are most relevant to the problems we’re trying to solve. We need to determine what data warrants inclusion in clinico-genomic datasets and then include them in a way that allows this information to be effectively leveraged for analysis. Especially for nascent datatypes, it can be particularly difficult to standardize this data for accurate analysis across large populations …
Dr. Elgort emphasized that such challenges are to be expected with promising new trends in cancer research and bioinformatics, and that overcoming them will be well worth the effort.
We’re broadening the number and types of cancer biomarkers, enabling us to create increasingly meaningful classifications for a given patient’s cancer type. That’s important for the drug discovery and development process because it helps us identify more detailed, cohesive patient cohorts and make appropriate comparisons.
Supporting Meaningful Research That Will Shape the Future of Cancer Care
Today, M2GEN’s groundbreaking data platform, ORIEN Avatar, is redefining how data can be used in the fight against cancer. Under Dr. Elgort’s leadership, M2GEN will continue to make strides in creating robust longitudinal clinical and genomic datasets while improving the ways in which such data is collected, shared, and analyzed.
Contact us today to request a demonstration and learn more about our custom bioinformatics solutions.