In their recent publication, Learnings from a registry-based cohort study for spinal muscular atrophy disease, Carla Jonker (CMG/EMA) et al. reflect on what enables registry data to support regulatory decision-making and where challenges remain. Especially for rare diseases, it is extremely important to gather high quality data in independent disease registries to maximize the usability of information derived from a limited number of patients. Leveraging these data facilitates timelier and more robust regulatory and reimbursement assessments, ultimately improving patient access to innovative therapies. However, not all existing data registries meet regulatory standards. The recent paper of Carla Jonker and colleagues addresses the requirements registries must fulfil to be considered fit for regulatory purposes.  

 

The key lessons from the EMA’s registry experience were: 

1. Feasibility assessments matter: Registries must be assessed upfront for data quality, completeness, and relevance to clearly defined regulatory questions. Early feasibility assessments help identify limitations and avoid bias later in analysis. 
2. Standardisation and data quality are essential: Inconsistent definitions, limited standardisation, and missing data, particularly for key clinical variables, reduce the regulatory value of registry data. Harmonised data elements, clear variable definitions, and quality controls are crucial.  
3. Completeness of untreated patient data: Especially for orphan and rare diseases, capturing robust data on non-treated patients are critical for unbiased comparisons and informative regulatory evidence.  
4. Linkage and enrichment strengthen evidence: Registries become more informative when data can be linked to other sources (e.g. pharmacy or clinical systems), helping to address missingness and improve interpretability. 
5. Collaboration and governance: Close collaboration between registry holders, clinicians, patients, and regulators is necessary for registry data to meaningfully inform regulatory decisions. 

 

An example from our network: the MLD Initiative (MLDi)  

The MLD initiative (MLDi) is a harmonised, international multi-stakeholder registry for metachromatic leukodystrophy, with a strong focus on data quality, standardisation and regulatory relevance.  

 

Standardised data elements and endpoints 

The MLDi collects a clearly defined set of core data elements and endpoints that capture disease characteristics, functional status, treatment exposure, and outcomes across the full disease spectrum. These data elements were selected to be clinically meaningful, comparable across centres, and suitable for longitudinal and regulatory analyses, addressing the EMA’s emphasis on fit-for-purpose data. 

To ensure consistency, the dataset was developed using a modified e-Delphi consensus process involving international experts. This ensures that variables are clearly defined, uniformly interpreted, and consistently collected across participating centres. In doing so, it directly addresses  the concerns identified by EMA regarding heterogeneity and limited standardisation in registry data. 

 

Harmonised clinical standards 

In addition to defining what data are collected, MLDi supports how data are generated through shared clinical standards and protocols. These frameworks promote harmonised assessments and follow-up, reducing variability between centres and improving data reliability.  

 

Comprehensive and unbiased data capture 

MLDi captures data from both treated and untreated patients, enabling unbiased comparisons over time. The EMA has highlighted this aspect as essential for regulatory decision-making in rare and orphan diseases. 

 

Governance, collaboration and data ownership 

MLDi operates under strong governance with close collaboration between clinicians, researchers, and patient representatives, which aligns with the EMA’s call for early and sustained engagement. While coordinated by a central research management team, each participating centre retains ownership of its own data, ensuring transparency and compliance with local and legal requirements. 

 

Built for long-term and evolving regulatory needs 

The registry supports long-term follow-up and future data linkage, allowing MLDi to evolve alongside advances such as newborn screening, new outcome measures, and emerging therapies. 

In summary, the EMA’s published learnings and guidance show that registry data can be used to support regulatory decisions, but only when data are high quality, fit-for-purpose, standardised, and well governed. We hope the MLDi’s design and practices will reflect these criteria in practice, positioning it as a strong source of real-world evidence that meets regulatory requirements.  

 

Are you setting up a new disease registry or do you want to know more about making a registry multi-purpose? Please reach out!