Real-World Evidence for Regulatory Decision Making - Some Updates

This year, real-world data and real-world evidence is the theme in every conference in the clinical trial and drug development area. Just a couple of months ago, I had discussed "Generate Real-World Data (RWD) and Real-World Evidence (RWE) for Regulatory Purposes". Last month at the annual Regulatory-Industry Statistics Workshop, the real-world evidence was again the main topic. Below are some topics (with slides) that were discussed in the workshop.

• Keynote speaking by Jacqueline Corrigan-Curay, US FDA CDER Office of Medical Policy: FDA’s Real-World Evidence Program: An Update
• Real-World Data, Machine Learning, and Causal Inference: Presentation by Jie Chen, Merck Research Laboratories
• FDA Guidance on Meta-Analysis of Safety Evaluation: Presentation by Eugenio Andraca-Carrera, FDA/CDER/OTS/OB
• Continuum Safety Evidence in Decision-Making: From RCTs to RWE: Presentation by Ed Whalen, Pfizer Inc.
• The Use of Real-World Evidence in Regulatory Decision-Making for Medical Products: How We Get There from Here:  Presentation by Mark Levenson, FDA/CDER
• The Use of RWE for Label Expansion: Presentation by Weili He, AbbVie
• The Use of RWD/RWE to Inform Clinical Trial Design: Presentation by Martin Ho, FDA/CDRH
• Adjusting diagnostic test performance for numerous confounders: Presentation by Gene Anthony Pennello, FDA
• Approaches and Challenges in Accounting for Baseline and Post-Baseline Characteristics when Comparing Two Treatments in an Observational/Non-Randomized Setting: Presentation by Joe Massaro, Boston University

There is also an upcoming conference "Real-World Evidence Conference" this November 2019 in Cambridge, MA

Where is the real-world data coming from?
The real-world data will mainly come from the claim data, the EHR (electronic health records), registry, and maybe social media data. The data from a clinical trial using the real-world device (for example, using actigraphy/accelerometry to measure the patient's function in the real world) may also be considered as real-world data - different types and more acceptable real-world data.

Even though the real-world evidence is discussed everywhere, the application and the acceptability of the real-world data are still limited. It is unlikely to have real-world data or real-world evidence to replace the clinical trials, especially the gold standard of RCT (randomized, controlled trials).  In this DIA discussion between Ms. Kunz and Ms. Mahoney, "Advancing the Use of Real-World Evidence for Regulatory Decision-Making", the potential application of real-world evidence was mentioned to be for label expansion and for fulfilling the post-marketing requirement. I would say that real-world evidence may also be applied in the regulatory decision making for ultra-rare diseases.

For real-world data, data quality is always an issue and a concern. In a recent presentation by Dr. Bob Temple, "Leveraging Randomized Designs toGenerate RWE", he discussed the areas and examples that real-world evidence was used. He also had the following comments about data quality and precision.

In a most recent article, US FDA's Temple On Real-World Evidence: 'I Find The Whole Thing Very Frustrating'. and also this article: Real-World Evidence: Sponsors Look To US FDA Drug Reviews For Potential Pitfalls.

Officials from the European Medicines Agency (EMA) said in an article published recently in Clinical Pharmacology & Therapeutics that there will need to be adequate statistical methods to extract, analyze and interpret real-world evidence before they can translate into credible evidence.

Are novel, non‐randomised analytic methods fit for decision‐making? The need for prospective, controlled and transparent validation