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
Real4Reg WP1: Using Real-World Data to Improve Research on Breast Cancer and ALS
Read more: Real4Reg WP1: Using Real-World Data to Improve Research on Breast Cancer and ALSReal4Reg is working to improve how real-world health data (RWD) is used in decisions about medicines and medical technologies across Europe. The project focuses on developing and applying artificial intelligence (AI) to make data analysis more effective and reliable throughout the entire product lifecycle. The results will help shape training and good practice guidelines for…
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Latest News
Real4Reg Consortium Holds X Consortium Meeting in Lisbon
Read more: Real4Reg Consortium Holds X Consortium Meeting in LisbonThe Real4Reg European consortium held its annual in-person meeting on May 21–22, 2025, in Lisbon, in a hybrid format. The event brought together international experts, clinical specialists, and representatives from partner institutions to discuss recent developments and preliminary results of the project. A highlight of the meeting was an invited talk by Prof. Mads Nielsen…
Upcoming Events
22-26 August 2025 – Washington DC, USA: 41st Annual Meeting International Society for Pharmacoepidemiology
23-25 September – Münster, Germany: Annual conference of DGEpi “Changing the face of epidemiology”
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.