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Think Tank

Real World Evidence (RWE) in Regulatory Decision Making: Establishing Study Credibility and Totality of Evidence

I was pleased to be a part of the Duke-Margolis webinar on January 15, 2020 entitled, “Bolstering RWE Study Credibility and Its Role in a Totality of Evidence Approach,” and thought it important to share some of the learnings from the session.

While the 2016 21st Century Cures Act “requires that FDA establish a framework for implementing a program to evaluate the potential use of RWE to help support the approval of a new indication for a drug approved under the Federal Food, Drug, and Cosmetic Act and help support or satisfy postapproval study requirements,” it is well established that the FDA has been using RWD and RWE for decades to help assess medication use and to satisfy post-marketing requirements for safety issues. What is novel is the potential to use RWE for drug approvals and/or label expansions, and the FDA has already made several approvals based on RWE such as Ibrance® (palbociclib) for male breast cancer, Blincyto® (blinatumomab) for acute lymphoblastic leukemia and others.

However, RWD is, by definition, uncontrolled, and often collected for purposes outside of research, e.g., secondary data such as billing claims or electronic medical records. As a result, there are a number of aspects that must be addressed to help increase the rigor and confidence in RWE to make it acceptable for regulatory decision making.  Institutions such as Duke-Margolis are collaborating with the FDA to address a number of these important issues.

The webinar was designed to summarize 2 new whitepapers that were just released. The first, “Demonstrating the Credibility of Non-Interventional Studies Using Secondary Data,”  described when and why a non-interventional study (NIS) is the preferred, only, or complementary option compared to interventional studies such as randomized controlled trials (RCTs). It also covered some of the key regulatory definitions and highlighted some of the common methodologic considerations (e.g., assessing the direction and magnitude of bias).

Bottom Line: Non-interventional studies (NIS) using secondary data can be used in many circumstances to make valid causal inferences; however, we lack a single gold standard for evaluation of NIS quality, although useful frameworks do exist. As such, it is currently up to researchers and regulators to develop a study-by-study consensus on the definition of “credible evidence”. After two decades performing and overseeing “regulatory grade” safety studies (primarily), my view is that a consensus on the framework will eventually evolve with more experience, but we’ll need to be patient while we gather that experience and be prepared that ultimately each study and situation is unique to define “high quality RWE”.

The second whitepaper entitled,Adding Real-World Evidence to a Totality of Evidence Approach for Evaluating Marketed Product Effectivenessoutlined what drives the Totality of Evidence considerations when using RWE:

o  Prior and new evidence
o  Timing since approval (older drugs have more evidence and experience)
o  Robustness of prior evidence
o  Clinical context (e.g., high unmet need)
o  Regulatory context (e.g., is the new indication’s population clinically very similar to the already approved population)
o  Weighting of RWE vs RCT

Bottom Line: Ultimately, the role of RWE in the total data package is highly situation-dependent and certainly evolves over time, but RWE can unquestionably provide an important contribution to the understanding of a medication’s use, population, or other factors.

Importantly both whitepapers make the case that from an evidentiary standard, an evidence package can include studies other than RCTs and still support an effectiveness claim, as long as we carefully consider the data, methods, and context.

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Connect with Dr. Sobel to discuss UBC’s expansive RWD/RWE experience and learn more by visiting ubc.com.

With 15+ years in evidence generation, UBC is poised to address the challenges of this emerging landscape and accelerate the time to generate meaningful and clinically rich evidence.