Real4Reg – Unlocking Real-World Data with AI
Real4Reg is a consortium of ten European institutions which aims to promote the use of real-world data (national healthcare registers and claims data) to support the regulatory decisions about medicines. Real4Reg will take advantage of ground-breaking technologies such as artificial intelligence and machine learning.
The structure and approach of our project aim to facilitate the implementation of the effective use of real-world data in regulatory decision-making and health technology assessment.
Data & Methods
Real4Reg will use data sources from four European countries (Denmark, Finland, Germany, and Portugal) and will develop solutions to address the data analytical needs of regulatory agencies.
From a methodological point of view, the project is aligned with the decision-making process in regulatory agencies, which can be broadly broken down into the pre-authorisation, evaluation, and post-authorisation phases of the product lifecycle.
Use Cases
Description of Study population: breast cancer, ALS
Real4Reg will assess the value of real-world data from national healthcare registers and claims data in generating high-quality, accessible, population-based information on breast cancer and amyotrophic lateral sclerosis (considering the diagnosis, treatment, and outcomes).
Historical controls and synthetic data: breast cancer, ALS
Real4Reg will demonstrate how the real-world data can contribute to questions that are not typically answered by clinical trials, due to ethical or practical issues. These questions need to be answered for regulatory evaluation and health technology assessment, in the improvement of external validity and statistical power and precision.
Safety: Fluoroquinolones
The overall objective of this use case is to prepare a good practice example for safety analyses of real-world data for the post-authorisation stage and to improve methods for risk estimation in observational data. Real4Reg will also evaluate the impact of regulatory warnings on the use of broad-spectrum antibiotics.
Effectiveness and drug repurposing: SGLT2 Inhibitors
Real4Reg will prepare a good practice example for drug effectiveness and drug repurposing analyses of real-world data for the drug post-authorisation stage. The case of Sodium-glucose Cotransporter-2 (SGLT2) inhibitors will be analysed. These antidiabetic medicines have shown beneficial effects on cardiovascular outcomes in recent years.
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Latest News
Supportive frameworks for generation of real-world evidence from real-world data
Read more: Supportive frameworks for generation of real-world evidence from real-world dataThe importance of real-world evidence (RWE) derived from different real-world data (RWD) has been increasingly recognised, including its use in regulatory decision-making. Electronic health records, national registers and claims data are commonly utilised data sources, providing excellent opportunities for capturing the routine delivery of healthcare together with medication use and associated outcomes in representative real-life…
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Latest News
Successful Multi-Stakeholder Workshop on RWD in Regulatory and HTA Decision-Making
Read more: Successful Multi-Stakeholder Workshop on RWD in Regulatory and HTA Decision-MakingOn Thursday, 6 February 2025, the Multi-Stakeholder Workshop on Real-World Data (RWD) in regulatory and Health Technology Assessment (HTA) decision-making took place at BfArM, in Bonn, Germany.
Who we are
Our consortium assembles ten partners from six different European countries with experience in the field of RWD analyses, including experts from regulatory agencies and health technology assessment bodies, academia, and patient organisations.
A project for the Patients
Real4Reg integrates two patient organisations to incorporate the patients’ perspectives and expectations along its work.