EU – EMA RWE Framework to Support Regulatory Decision Making

RWE 201 – EU – EMA RWE Framework to Support Regulatory Decision Making

 

EMA RWE Framework 2023: https://www.ema.europa.eu/en/documents/report/real-world-evidence-framework-support-eu-regulatory-decision-making-report-experience-gained_en.pdf

The European Medicine Agency (EMA) is actively working on creating a framework that will facilitate the use and establishes the value of RWE in decision-making throughout the entire drug lifecycle.

The current framework includes 3 evidence generation pathways: (1) In-house database e.g., The Health Improvement Network (THIN®), (2) DARWIN-EU, and (3) ‘Traditional’ primary data studies.

80% of the database studies, also referred to as ‘rapid data analytics’ , were delivered in less than 90 days.  Whereas delivery of the DARWIN-EU studies averaged 215 days. The majority of the studies focused on safety, rare diseases, and paediatrics. 

Key Learning

  1. Suitability of RWD Sources:

– RWD aids in enhancing evidence from clinical trials, aiding EU regulatory decisions.

– Most suitable studies addressed primary care scenarios due to available databases.

  1. Regulatory Context & Timelines:

– Comprehending regulatory nuances and evidence gaps is crucial for apt data selection and study design.

– In-house studies, given their speed, fit well with research questions having tight timelines.

  1. Building Capability & Capacity:

– Familiarity with RWD concepts, methodologies, and terms is essential for RWE acceptance.

  1. Usefulness for Decision-making:

– RWD studies bolster scientific evaluations in multiple regulatory situations.

– Understanding data source attributes aids in grasping study strengths, limitations, and RWE’s value.

  1. Other Process-related Aspects:

– Standardizing RWD study approaches, through agreed processes and templates, enhances RWE efficiency.

Recommendations

  1. RWD Source Expansion: Access more diverse data sources for better representation. Retain all three RWE pathways and collaborate with NCAs to maximize RWE generation.
  2. Enhance RWE Timeliness: Adopt proactive RWD study identification methods and increase RWE generation speed, possibly via tools like DARWIN EU.
  3. Boosting Capability & Capacity: Implement the Big Data Steering Group’s curriculum specifically for regulatory stakeholders.
  4. Improving Decision-making Utility: Detail strengths and limitations in future reports for improved interpretation.
  5. Process Refinement: Encourage reflections on RWE’s potential to bridge knowledge gaps and further unify processes.

Conclusions

Over the report’s timeframe, 27 regulator-led RWD studies were finalized, aiding various regulatory assessments like PRAC and SAWP. These studies spanned across safety, drug use, disease epidemiology, and more, primarily providing descriptive analyses. Some comparative analyses were also done. The range and design of these studies highlight the vast potential of the existing RWE resources and the Agency’s adaptability in addressing diverse research inquiries. However, further enhancements can be made to fully harness the EMA RWD study framework’s potential.

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