As digital technologies evolve, healthcare regulators face increasing demands to integrate real-world data into regulatory decision-making processes. This is a critical undertaking as it promises to enhance the accuracy and relevancy of regulatory outcomes. On July 17, 2025, the HMA-EMA joint Network Data Steering Group met virtually, co-chaired by Karl Broich and Peter Arlett, to deliberate on significant advancements and strategies in managing real-world evidence (RWE), clinical study data pilots, and AI change management strategies. The discussions underscored the necessity of improved data quality, engagement with stakeholders, and innovation in data management methodologies.
Advancing Real-World Evidence Initiatives
The meeting revealed progress in RWE initiatives, particularly emphasizing the role of DARWIN EU, a prominent platform to generate actionable evidence from real-world data. The publication of the third RWE experience report laid out the pathway for future improvements, focusing on streamlining regulatory processes through efficient data utilization. The meeting stressed that committed stakeholder engagement and communication are paramount for these efforts to thrive. Therefore, the RWE change management strategy aims to optimize engagement with committees, working parties, and assessors to amplify the positive impact of real-world data on regulatory decisions.
Clinical Study Data and AI Change Management
The clinical study data pilot, which started in 2022, moves into its second phase, exploring more sophisticated data analysis methodologies. The pilot aims to present compelling evidence of the benefits of voluntary data submissions for scientific and regulatory assessments. Moreover, AI is becoming a cornerstone in these efforts, with strategic plans targeting literacy and training across the network. The collective aim is better collaboration, training, and software selection tailored to enhance data interpretation and decision-making processes. The EMA hopes to broaden the participation of member states in these initiatives to consolidate and leverage shared expertise.
– Enhance the efficiency of DARWIN EU by training assessors on drafting precise data queries.
– Encourage cross-stakeholder collaboration to realign processes with modern AI solutions.
– Utilize the AI tool being developed by Sweden’s Medicines Agency to streamline data analysis.
In the coming years, agencies such as the EMA will be pivotal in orchestrating the seamless integration of data-driven insights into the regulatory framework. Understanding these processes will empower researchers, pharmaceutical companies, and regulatory groups to enhance decision-making. Moreover, emphasis on training and education cannot be understated. Such initiatives prepare stakeholders for a data-centric regulatory environment, ultimately fostering trust, transparency, and efficiency in developing new medical therapies. The future focus will be on ensuring sustained dialogue and collaboration across the network, drawing more stakeholders to actively participate in these transformative endeavors.
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