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EMA Network Data Steering Group workplan 2025-2028: Leveraging Data and AI for Enhanced Medicine Regulation

In the evolving landscape of medicines regulation, data and artificial intelligence (AI) have become pivotal tools to enhance public and animal health. The European Medicines Agency (EMA), together with the Heads of Medicines Agencies (HMA), has established the Network Data Steering Group (NDSG) workplan 2025-2028 to strategically harness data interoperability, analytics, and AI across the European Medicines Regulatory Network (EMRN).


The NDSG is a strategic advisory body formed jointly by EMA and HMA to:

  • Maximise data interoperability and exchange across the EU medicines network.

  • Improve access to diverse data sources and enhance evidence generation.

  • Leverage Artificial Intelligence (AI) to support regulatory science for human and veterinary medicines.

  • Ensure data use complies with ethical frameworks and EU data protection legislation.


Their vision is clear: “Trusted medicines by unlocking the value of data.” This entails maximizing data interoperability, improving access to data, generating compelling evidence, and leveraging AI. The aim is to propel public and animal health within the EU, utilizing data-driven strategies.


Key Workstreams of the NDSG Workplan 2025-2028

The NDSG workplan is organized into six core workstreams, each addressing critical aspects of data and AI integration in medicines regulation:

1. Strategy and Governance

  • Develop and update the EMRN data strategy and data standardisation strategy to ensure high-quality, shareable data assets.

  • Support implementation of EU-wide initiatives like the European Health Data Space (EHDS) and new pharmaceutical legislation.

  • Coordinate governance frameworks to align with the Interoperable Europe Act and other legislative requirements.

2. Data Analytics

  • Review and integrate advanced methodologies such as biostatistics, modelling & simulation, and pharmacoepidemiology.

  • Expand use of diverse data types including real-world data (RWD), clinical study data, genomic data, synthetic data, digital twins, patient experience data, and social media data.

  • Support the DARWIN EU® network for real-world evidence generation and expand its capabilities.

3. Artificial Intelligence (AI)

  • Provide guidance and policy support for AI tools in regulatory contexts.

  • Foster collaboration and experimentation with AI technologies to enhance regulatory decision-making.

  • Support change management to embed AI effectively in regulatory workflows.

4. Data Interoperability

  • Catalogue and manage data assets and metadata.

  • Improve data quality and ensure semantic and organisational interoperability across the network.

  • Develop glossaries and best practices to support consistent data exchange.

5. Stakeholder Engagement and Change Management

  • Implement strategies for stakeholder communication and education.

  • Build network skills and knowledge to support data-driven transformation.

  • Manage change to ensure smooth adoption of new data and AI tools.

6. Guidance and International Initiatives

  • Develop and update guidance documents relevant to data use and AI in regulation.

  • Engage with international partners to harmonize approaches and share best practices.


Highlights of Planned Activities and Milestones

  • DARWIN EU® will continue onboarding new data partners and conducting studies to support regulatory and national health initiatives. A follow-on infrastructure, DARWIN EU® 2, is planned to start around 2027.

  • The CHMP clinical study data pilot will progress, refining access to individual patient data from trials to enhance regulatory assessments.

  • Improvements to EudraVigilance will introduce new signal detection and SUSAR screening capabilities, along with an enhanced public website for adverse drug reaction reports.

  • Proof of Concept studies on non-clinical raw data analysis and the implementation of the Standard for Exchange of Nonclinical Data (SEND) will be advanced.

  • Reviews of innovative methodologies such as AI analytics, modelling & simulation, and emerging data types like patient experience data and mobile health data will be conducted progressively through 2025-2028.


By embracing interoperability, advanced analytics, and AI, the European medicines network aims to deliver trusted, high-quality medicines for both humans and animals more efficiently and transparently.


For more detailed information, please refer to the EMA’s official documents:

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