Cancer comes in many forms, including hematologic malignancies that originate in blood-forming tissues or in the cells of the immune system, and solid tumors that form as abnormal masses of tissue and are named for the type of cells and classified by the organ or biologic structure from which they originate.
Hematologic cancers, such as leukemia, lymphoma, and myeloma, are relatively rare compared to solid tumors, which comprise the vast majority of cancers. These include some of the most common cancer types, such as breast, lung, prostate, colorectal, ovarian, and skin.
While there are some similarities between these two main cancer categories, there are also significant differences in how and why they develop – and how to best treat them. That means there are also notable differences in the data we generate, collect, curate, and analyze to design more effective therapies and apply best practices to care.
At COTA’s inception, we knew that it wouldn’t be easy to build the infrastructure and data science techniques to curate high-value real-world data (RWD) in this area, but it was that very challenge that attracted us to it. We saw the direct line from better RWD to better outcomes for patients, and knew we had to do something to strengthen the industry’s ability to connect those dots.
After more than 14 years of working closely with life science companies, clinical researchers, regulators, and oncologists, we have successfully leveraged our experience with complicated liquid tumor data to solve many of the hardest problems around how to work with highly variable real-world datasets on uncommon diseases.
We understand the importance of bringing together data from multiple provider sources, such as oncologists, surgeons, and specialist physicians, to create a comprehensive, longitudinal record of care. We are intimately familiar with how RWD can and should be used to support regulatory decision-making. And we know that quality, completeness, and reliability are non-negotiable features of a fit-for-purpose dataset.
Now, we’re setting our sights on solid tumors to bring even more clarity and understanding to the cancer community. Our datasets now include longitudinal treatment and outcomes data for a broad array of solid tumors, including:
- Breast cancer
- Colon cancer
- Rectal cancer
- Gastric cancer
- Lung cancer
- Melanoma
- Ovarian cancer
- Pancreatic cancer
- Prostate cancer
- Uterine
These are conditions that touch millions of patients and their families every year, and generate huge amounts of data that can be used to better understand critical genetic, clinical, and socioeconomic patterns in disease development, progression, treatment, and outcomes.
After taking on so many tough problems in the unique liquid tumor space, we are ready and eager to bring that deep expertise to the wide world of solid tumor data. We’re excited about the possibilities of applying these well-honed strategies to ever larger and more diverse datasets to assist with the precision medicine approaches of the future.
With so many patient records and so many rich data elements available to us in the solid tumor environment, our data teams will be able to further assist researchers and life science companies with developing highly detailed and specific patient cohorts to support faster, more efficient, and more effective investigations.
It’s the natural next step toward a world where every person with cancer gets the tailored, informed, and effective care they need to have the best possible outcome.
