EMA Finalizes Quality Framework for RWD in Regulatory Submissions

New guidance outlines how real-world data quality should be assessed to support regulatory submissions, emphasizing fitness-for-use and transparency

On March 16, the European Medicines Agency (EMA) finalized guidance outlining how real-world data (RWD) should be evaluated for use in regulatory submissions, reinforcing expectations for real-world evidence (RWE) in marketing applications.

The document applies the European Medicines Regulatory Network (EMRN) Data Quality Framework (DQF) to RWD to support consistent and transparent evaluation of data used in regulatory decision making. EMA recommends using the framework as a companion reference when preparing submissions that include RWD.

What is the focus of EMA's new guidance? 

The framework emphasizes that RWD quality should be assessed in the context of a specific research question, rather than against fixed thresholds. It outlines a structured approach to determining whether data are fit-for-use, considering relevance, reliability, completeness, coherence, and timeliness.

The guidance applies to data collected in routine clinical practice, including administrative claims, electronic medical and health records, prescription data, and patient registries. It aligns with existing standards such as European Network of Centers for Pharmacoepidemiology & Pharmacovigilance methodological guidance and the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) M14 guideline.

Defined roles across the data lifecycle

EMA clarifies that responsibility for data quality is distributed across stakeholders. Data holders are expected to implement quality management systems, document data provenance, and provide metadata, while data users should assess fitness-for-use, validate datasets, and document data quality metrics. Regulators will then review validation approaches and interpret evidence in a regulatory context.

Addressing challenges in secondary use of RWD

The guidance highlights the challenges associated with secondary data use, including limited control over collection and constraints on assessing reliability at the source. As a result, the framework promotes identifying data gaps and supporting reliability assessments through documentation, metadata, and analytical methods.

EMA also underscores the importance of anonymization or pseudonymization and notes that retrospective informed consent may be needed when patient-level data are used for regulatory purposes.

Emphasis on systems, processes, and documentation

The guidance highlights that data quality depends not only on the dataset itself but also on the systems and processes used to collect, manage, and transform the data. RWD may be suitable for regulatory use when there is sufficient evidence that the data are reliable and have not been altered.

The framework also introduces maturity models and structured checklists to support consistent evaluation of data quality across use cases.

For stakeholders across the lifecycle, the guidance emphasizes scientific rigor, focusing on internal validity, assessment of bias and key determinants of the outcome, and interpretation of results within a pre-specified and transparent framework that supports reproducibility and auditability.