Historically, medical research data obtained from other sources outside of traditional clinical trials were viewed with a heavy dose of skepticism even before evaluation of the methodology. Although this real-world data (RWD) was widely used to satisfy safety monitoring and post-drug approval regulation requirements, many clinicians viewed RWD and the real-world evidence (RWE) it generated as unverified and unreliable data mining explorations with drug marketing objectives. RWD, by definition, is unstructured (compared to randomized controlled trials) and can be obtained with a variety of methods from multiple sources lending to its credibility problem of “real evidence.” Unfortunately, there are several examples of exploited and misused RWD with tailored methodologies that produced data to fill messaging gaps. This has fostered mistrust and misunderstanding of RWD in the medical community. Fortunately, there is substantial evidence of high-quality data from RWD, leading to essential observations. Still, the credibility issue caused by a few bad apples is difficult to undo, creating a barrier for RWD/RWE use in clinical research.
The unstructured and less precise nature of RWD that opens it up to misuse is what makes the data and evidence valuable as a reflection of the real world. Clinical trials are designed to be conducted under homogenous circumstances to minimize factors that could influence the outcome of the study. When obtained with correct methodologies and from credible sources, RWD provides the perfect complement to clinical trial data. RWD and the RWE it generates can be used to assess safety and efficacy in patient populations not represented in clinical trials, understand if a perceived drug risk is real, and to identify and understand gaps in research and areas of unmet needs in standard of care. It is also valuable in assessing the generalizability of clinical trial data, generating hypotheses for additional trials, and studies quality of life and changes in drug use patterns.
Over the past five years, RWE has increased in value to the research community thanks in part to the 21st Century Cures Act. The Cures Act put in place avenues to accelerate drug development, so life-saving therapies can quickly become available to patients who need them. One of these avenues is RWD/RWE to support drug approval applications, where it was once reserved to satisfy post-approval and safety surveillance regulatory requirements. In large part, this was driven by time-critical oncology research that was unable to wait for survival endpoint data of clinical trials. Oncology Phase 1 and 2 trials have begun integrating RWD extensions of as a part of the expedited approval process. In essence, RWD/RWE is critical in making life-extending therapies available to critically ill patients, helping put its previous credibility issues in the rearview.
To support RWD/RWE’s place as credible research, the Food and Drug Administration (FDA) has offered guidance on proper RWD study design and data gathering from quality sources, further solidifying RWD’s importance and place in the research paradigm. This guidance identifies the main challenges to quality RWD as 1) the methodologies used, 2) reliability and relevance of data, and 3) quality of data sources used.
To help navigate the RWD/RWE challenges, researchers should consider partnering with research companies experienced in long-term, real-world, observational studies. Such companies have the infrastructure to support a variety of study designs (e.g., large simple trials, hybrid or pragmatic designs, and long-term observational studies). In addition, a company specialized in gathering and verifying data through in-home patient visits, medical health record reviews, and longitudinal biometrics analysis would ensure quality RWE. Partnerships such as these can elevate the quantity and quality of RWD to support traditional RCTs and drug approval pipelines.
ABOUT THE AUTHOR:
Brian Neman serves as the Co-Founder and CEO of Sanguine Biosciences. Brian focuses on all items relating to commercialization and relationships with researchers; he is an adjunct professor of Digital Health at USC, and co-founded Sanguine in 2010 out of his graduate program in healthcare administration at USC. He is also on the boards and committees of various organizations including HD Care, BIOCOM Big Data Committee, and more.
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