European Medicines Regulatory Network launches first data strategy to enhance governance, quality, and interoperability of health data

The European Medicines Regulatory Network (EMRN) – a regional regulatory system between the European Medicines Agencies (EMA), the European Commission, and the national competent authorities of EU and EEA Member States – has released its first network data strategy, setting a shared vision for how authorities across the EU will manage, govern, and use data to strengthen decisions and protect public and animal health.

The strategy was adopted by the Network Data Steering Group on June 27, 2025, endorsed by the Heads of Medicines Agencies (HMA) on September 12, 2025, and approved by the EMA Management Board on October 2, 2025. Peter Arlett, Head of the Data Analytics and Methods Task Force at the EMA, described the publication as:

“A major step accelerating EU regulatory agencies’ use of data for impactful decisions and improved patient and animal health.”

He added that six objectives will be delivered “through concrete actions ensuring the regulatory network’s data assets are well governed, meet high standards and quality, and deliver benefits for stakeholders.”

The strategy sets out the EMRN’s vision, principles, and goals to maximize the value of data across regulatory processes. It operates within the broader EU legal framework on data protection, sharing, and interoperability, including the GDPR, EU Data Act, and Interoperable Europe Act, and is closely aligned with initiatives such as the European Health Data Space (EHDS) and the EMA Network Strategy to 2028. The strategy highlights that its success will depend on “effective collaboration with a diverse ecosystem of stakeholders,” including patients, healthcare professionals, industry, academia, health technology assessment (HTA) bodies, and policymakers.

The document identifies several barriers to achieving data-driven regulation, including fragmented systems, differing technical capabilities, and inconsistent adoption of standards. It highlights “varying levels of organizational maturity, skills, and technical readiness,” alongside “financial limitations,” “lack of interoperability,” and the “slow adoption of new data standards such as ISO IDMP.” Privacy and security concerns in cross-border data sharing are also noted. Overcoming these challenges is seen as crucial to enabling greater use of advanced analytics and AI in regulatory assessments.

The strategy is built on six core data principles – data are: 

1. Considered assets
2. Accessible
3. Shared
4. Actively managed with defined roles
5. Described using common vocabularies and definitions
6. Safe and secure

Data are “expected to be FAIR (findable, accessible, interoperable, and reusable) and machine-readable,” reflecting the growing need for computational analysis at scale. The strategy also reinforces that ethical data use is key, emphasizing “confidentiality and privacy,” “purpose limitation,” “fairness,” and “AI and trustworthiness,” alongside transparency about how data are collected, generated, and shared.

Building on these principles, the strategy defines six strategic goals to translate them into practice across the network:

1. Data governance: Establishing common policies, roles, and quality standards to ensure reliable and consistent data management across the EMRN, while supporting appropriate data access for stakeholders within and outside the network. As the document notes, this framework “enables standardization and harmonization in a data-driven network,” ensuring practices support both legal and security requirements.
2. Data quality management: Implementing the Data Quality Framework for EU Medicines Regulation to strengthen reliability, trustworthiness, and automation in regulatory processes. The strategy also supports harmonized use of master data within the network and promotes international collaboration to align data quality methodologies. As the EMRN highlights, “data quality should be a fundamental consideration from the start of data collection and generation processes,” with quality management integrated into all system proposals and improvements.
3. Interoperability: Strengthening coordination on data standardization across the EMRN through active contributions to international standards such as ICH, ISO, and HL7, and by creating consistent engagement processes within standards development organizations. The strategy highlights the goal of building “a seamless data ecosystem that supports the network’s mission in medicines regulation,” with semantic interoperability and master data management at its core. It also aims to enable trusted data exchange across the network and with external partners by updating its standardization approach and implementing the European Interoperability Framework for regulatory data flows. Interoperability will be embedded into all IT and data projects, promoting API-first architectures and the use of FHIR-based structured data exchange.
4. Data cataloguing and metadata management: Developing a centralized, comprehensive catalogue with clear metadata schemas to improve the discovery, understanding, and reuse of data across the EMRN. This includes maintaining the EMRN/HMA catalogue of real-world data (RWD) and aligning metadata frameworks with EU approaches such as Health DCAT-AP and the EHDS. The strategy notes that this approach will “ensure that data can be easily located, understood, and appropriately used in regulatory decision-making processes,” supporting efficient discovery and reuse across the network.
5. Knowledge and change management: Promoting a data-driven culture across the network through coordinated capacity building, training, and knowledge sharing. The EMRN will establish network-wide capacity-building programs guided by an assessment of training needs to strengthen data and analytical skills. It commits to “developing tailored training programs, providing ongoing guidance, and facilitating knowledge sharing among network members” to ensure that all stakeholders can effectively leverage data assets and analytics in support of regulatory decision-making.
6. Value through analytics and tools: Deploying modern, self-service analytics and advanced methods, including AI and predictive modeling, to enhance data use across the network. The EMRN will agree and implement a network-wide data analytics strategy that supports dashboards, visualizations, and advanced analytical tools, while also enabling the extraction of value from unstructured sources such as dossiers and documents. The strategy envisions business intelligence solutions that “integrate data silos into an interconnected and interoperable data network,” empowering stakeholders to independently analyze data and drive informed public health decisions.

Successful implementation of the EMRN data strategy depends on collaboration across the regulatory network and with external partners. As the EMA notes, stakeholders “both contribute to and benefit from the regulatory network’s data,” helping to advance public and animal health and foster innovation in medicines regulation. Delivery will be coordinated through the Network Data Steering Group, with a dedicated implementation plan defining roles, responsibilities, and timelines.

The EMRN’s data vision:

“Trusted medicines by unlocking the value of data,”

frames data as a strategic asset that enhances efficiency, scientific assessment, and transparency. By strengthening governance, improving quality, and advancing interoperability and analytics, the strategy aims to enable faster, better-informed decisions while maintaining strong ethical and security standards. As the document concludes, the goal is to “build trust from stakeholders by making trusted data accessible for review and analysis” and to “share and use data for innovation and improved access to and availability of medicines and veterinary medicinal products.”