Best Practices Framework for Real-World Data (RWD) in Regulatory Submissions
Author(s)
Shivani Aggarwal1, Barath Sukumar, MS2, David Goldfarb, PhD, MPH3.
1Landmark Science, Inc, Los Angeles, CA, USA, 2Landmark Science, Inc, San Diego, CA, USA, 3Landmark Science, Inc, New York, NY, USA.
1Landmark Science, Inc, Los Angeles, CA, USA, 2Landmark Science, Inc, San Diego, CA, USA, 3Landmark Science, Inc, New York, NY, USA.
OBJECTIVES: The use of RWE for regulatory bodies and HTA decision-making has grown over the past decade, with numerous guidelines from regulators and payors. Despite many best practice recommendations for RWE, there is a lack of a clear, operational framework to guide the preparation and transformation of RWD for regulatory use. We present a practical framework for the preparation and submission of RWD in regulatory and HTA decision-making.
METHODS: We reviewed EMA and FDA guidance documents on RWD/RWE and evaluated recent case studies of RWE submitted in drug marketing authorization applications (MAAs). Medicines were selected for case study analysis based on inclusion of RWD/RWE in MAA submissions among MAAs approved from January 2021-present. Publicly available documents were extracted and reviewed by two independent reviewers. Practices related to RWD preparation, transformation, and documentation were synthesized with regulatory guidance to develop an operational framework.
RESULTS: Data preparation for submitting RWD in regulatory and HTA applications follows a stepwise process. Raw data should be organized into standardized formats including CDISC standards SDTM for source datasets and ADaM for analytic datasets. Sponsors should generate supporting documents including data dictionaries that define variables, formats, and controlled terminologies, define.XML files which provide metadata, and Reviewer’s Guides that enumerate dataset structures and special considerations. While formal requirements for HTA submissions vary, similar principles apply which include traceability from raw data to final analyses, transparency in analytic methods, and clear documentation. Early alignment on data standards, documentation expectations, and submission processes was consistently identified as imperative to ensure readiness and reduce delays.
CONCLUSIONS: A structured framework for submitting RWD ensures transparency, traceability and alignment with regulatory and HTA expectations. Sponsors should ensure RWD are transformed into accepted formats, have clear documentation, and be audit-ready. Consistent application of these best-practices ensures data integrity and allows for effective use of RWE in regulatory decision-making.
METHODS: We reviewed EMA and FDA guidance documents on RWD/RWE and evaluated recent case studies of RWE submitted in drug marketing authorization applications (MAAs). Medicines were selected for case study analysis based on inclusion of RWD/RWE in MAA submissions among MAAs approved from January 2021-present. Publicly available documents were extracted and reviewed by two independent reviewers. Practices related to RWD preparation, transformation, and documentation were synthesized with regulatory guidance to develop an operational framework.
RESULTS: Data preparation for submitting RWD in regulatory and HTA applications follows a stepwise process. Raw data should be organized into standardized formats including CDISC standards SDTM for source datasets and ADaM for analytic datasets. Sponsors should generate supporting documents including data dictionaries that define variables, formats, and controlled terminologies, define.XML files which provide metadata, and Reviewer’s Guides that enumerate dataset structures and special considerations. While formal requirements for HTA submissions vary, similar principles apply which include traceability from raw data to final analyses, transparency in analytic methods, and clear documentation. Early alignment on data standards, documentation expectations, and submission processes was consistently identified as imperative to ensure readiness and reduce delays.
CONCLUSIONS: A structured framework for submitting RWD ensures transparency, traceability and alignment with regulatory and HTA expectations. Sponsors should ensure RWD are transformed into accepted formats, have clear documentation, and be audit-ready. Consistent application of these best-practices ensures data integrity and allows for effective use of RWE in regulatory decision-making.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
RWD25
Topic
Organizational Practices, Real World Data & Information Systems, Study Approaches
Topic Subcategory
Reproducibility & Replicability
Disease
No Additional Disease & Conditions/Specialized Treatment Areas