Creating a Clear Path to Precision Oncology with Real-World Data

March 30, 2022
COTA Team

Real-world data (RWD) is the key to ensuring that all patients can access the right care for their individual needs. Combining human insight and advanced technology to extract insights from RWD will help us achieve the patient-centered goals of precision oncology.

In early March, the ViVE2022 conference brought thousands of clinicians, healthcare executives, and technology companies to sunny Miami Beach to discuss the latest best practices and data-driven breakthroughs from across the industry.

Precision care, and how to achieve it, was a major topic of conversation across the event. From chronic disease management to cutting-edge oncology, clinicians and entrepreneurs presented an array of striking ideas on how to become more precise in clinical care without losing focus on equity, accessibility, and the patient experiences.

On a panel of expert oncologists and technology innovators, COTA’s Chief Medical Officer, C.K. Wang, MD, stressed that the cancer care community must start their part of this journey with a better understanding of what “precision oncology” really is.

“The traditional view of precision oncology is finding a target in a cancer and using a drug against it,” he explained. “But it’s important to keep in mind that the majority of cancers do not have an actionable mutation, so that approach is only effective in and applicable to a small group of patients. We need to broaden our definition of precision oncology, because we believe all patients affected by cancer deserve a clear path to the right care.”

Real-world data (RWD) will be an essential part of building accessible, equitable avenues to high-quality cancer care so that cancer patients can achieve the best possible outcomes, he continued.

“Imagine if we could see a cancer patient in the clinic and tell them exactly how other patients like them fared with a specific treatment,” Wang said. “Imagine if we could quickly and effectively match that person to a clinical trial that’s right for their situation. RWD can help us get there – if we can aggregate, curate, and apply the right data in the right manner.”

To do so, industry stakeholders will need to take a hard look at how to improve the structure, completeness, and accuracy of clinical documentation produced at the point of care.  

“Physicians aren’t really taught to document in a structured way – we tend to learn by following previous examples,” Wang said, recalling a loose approach to documentation training when he was a new physician. “As a result, a lot of the clinical documentation is quite messy and unstructured at times, contradictory. That affects the way that we treat individual patients and the way we learn from patients in aggregate.”  

Technology alone won’t be able to solve the problem of messy source data, the panelists agreed.  Instead, data companies need to use trained human data abstractors in combination with emerging strategies in natural language processing, machine learning, and artificial intelligence.

“At COTA, we don’t believe technology can do everything,” said Wang. “We believe these tools can guide people through the data abstraction process to make it faster and more accurate, but we have to involve humans and their highly trained decision-making skills throughout the process.”

With expertly curated RWD available to investigators and clinical trial sponsors, researchers can begin to design more effective programs and find more patients with the appropriate clinical profiles to participate in promising research initiatives. 

“The percentage of participants in clinical trials hasn’t changed much for decades, which is a major concern,” he noted. “One of the most difficult things I did in clinical practice was educating patients to dispel some of the myths around clinical trials. We have to break down other barriers, too, such as traveling to trial centers and navigating strict and extensive protocol requirements.”  

“There are a lot of solutions out there, but it’s not one size fits all,” Wang concluded.  “It’s about first identifying the challenges and then sourcing the appropriate technology to help expedite solutions.”  

“The insights we generate from RWD can help solve those problems by improving clinical trial matching, informing treatment decisions, and leading everyone down that clear, accessible path to precision cancer care.”

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