What I saw at DIA RWE 2023

I am just back from Baltimore, Maryland, where I had the joy of attending DIA’s Real-World Evidence (RWE) Conference for the second year in a row. This is one of my favorite conferences due to its focus on pressing RWE issues, its ability to host engaging policy and practical discussions, and its intimate size. Aetion had multiple speakers and presentations, including a fantastic presentation from Brian Conroy, Senior Director of Biostatistics, on objectivity guardrails for RWE studies and a thought-provoking introduction to synthetic data provided by Lucy Mosquera, Senior Director of Data Science at Replica Analytics, an Aetion company. I wanted to share some of the thoughts and takeaways that had left a strong impression over the two-day conference:

1. One oft-repeated idea from many conference attendees was the theme of moving from theory to practice. We have many regulatory guidances, a wealth of strong methods and best practice approaches, and the know-how to generate high-quality RWE. It is now time to generate practical examples and ensure we have a depth of use cases that allow us to fully leverage the opportunities real-world data (RWD) offer.
2. Understanding how RWE can support regulatory decision-making is still one of the most important goals in the evidence-generation space, but many companies are thinking about how to leverage RWE more upstream in the evidence-generation process. Presentations focused on using RWE to make go/no-go decisions on moving forward with a development program and using RWE for trial planning purposes. Integrated evidence generation is a key aspect of fully recognizing the power of RWE. The more we think of RWE as another tool in the evidence generation toolbox (as opposed to a band-aid for a faltering development program), the better results we will see.
3. RWE’s bleeding edge focuses on marrying the old with the new. New technology (such as natural language processing, generative AI, and synthetic data) should be combined with best-in-class approaches to maximize established methods (objectivity guardrails, pre-specification, audit trails) and generate best-in-class evidence.
4. There’s still a lot more in the works:
   1. FDA stated it has two additional RWE-related guidances focusing on non-interventional studies and RCTs in clinical practice settings in the works. The agency will also soon release a definitions paper that clearly outlines a taxonomy for classifying RWE in a product approval.
   2. The Big Data Steering Group believes the use of RWE in the EMA context will be enabled and its value established by 2025. EMA is planning to release a deep-dive chapter on RWE as part of its Data Quality Framework in the coming months. 

Aetion is always thrilled to lead and participate in new developments across the RWE industry and is poised to support sponsors in moving from RWE theory to practice, establishing an overarching integrated evidence generation strategy to optimize the use of their RWD, and merging new technologies with established methods.

If you are interested in learning more about how RWD, RWE, synthetic data and generative AI, and Aetion’s platform applications can help accelerate your business and bring medicines to patients faster, please connect with us here.