Current Opportunities and Challenges in RWE and its Future with AI

FDA’s recent support and presentations at meetings on Regulatory Submissions with Real-World Evidence: Successes, Challenges, and Lessons Learned (RWE Meeting) and Artificial Intelligence in Drug & Biological Product Development (AI Meeting) provided updates on the current status of these initiatives at FDA, while also showing how the long-term benefits of Real World Evidence (RWE) and Artificial Intelligence (AI) may be linked.

The RWE Meeting included updates on PDUFA VII and MDUFA V commitments, along with case studies and a panel discussion.  Representatives from CDER discussed the Advancing RWE Program launched in 2022, which seeks to improve the quality and acceptability of RWE-based approaches, noting that of 26 requests, only five had been accepted, showing that there are still challenges to successful use of RWE, including concerns related to interpretability of data.  Representatives from CDRH discussed ongoing work with the use of Real World Data (RWD) to generate RWE across the total product life cycle, staff training, National Evaluation System for health Technology (NEST) program developments, and RWE guidance documents.

Case studies and panel discussions highlighted areas where RWE has been successful and obstacles to greater use.  Success was seen using RWE to collect natural history data to be used as a historical control.  This was especially useful in rare conditions.  In one example, the collection of natural history RWD was collected before a treatment was available to understand the progression of the condition  with standard of care.  Once there was a treatment available to study, the previously collected RWD was used as a control for comparison against patients receiving the treatment.  Success was also linked to early interaction with FDA, and where sponsors put in a lot of thought into ensuring data were fit for use and that bias was minimized in the study design stage. One challenge identified relates to data accessibility since patient level data are needed for CDER reviews and are hard to obtain from studies conducted outside of the United States.  For medical devices, one of the biggest challenges noted was being able to identify devices by manufacturer and model in RWD sources.  The successful device case study presented, for a spinal implant subject to medical device tracking (21 C.F.R. Part 821), was able to overcome this challenge by pairing its own tracking data with a CMS data set that included outcome measures.

To overcome challenges, several points were discussed.  Panelists suggested published consensus positions on the disease and data collection can help standardize data collection across studies and registries, which can in turn support future approvals.  Sharing additional case studies by FDA or industry in sessions like the RWE Meeting, both what works and does not work, was also noted as an opportunity to develop new solutions.

For the future, FDA noted that it wants to see RWD and RWE as a credible part of evidence to complement randomized controlled trials.  CDRH identified the use of Unique Device Identifiers (UDI) as a means to overcome the lack of device manufacturer and model information in RWD.  Several panelists brought up AI as a key opportunity for the future of RWE, noting that all data collection allows AI to be leveraged, but not all data are reliable for use.  It was also mentioned that AI can be used to annotate data, ultimately improving quality and fit for use.  The end of the RWE Meeting was the perfect transition to the AI Meeting, which will be covered in our next post.