%0 Journal Article
%A Peltner, Jonas
%A Becker, Cornelia
%A Wicherski, Julia
%A Wortberg, Silja
%A Aborageh, Mohamed
%A Costa, Inês
%A Ehrenstein, Vera
%A Fernandes, Joana
%A Heß, Steffen
%A Horváth-Puhó, Erzsébet
%A Korcinska Handest, Monika Roberta
%A Lentzen, Manuel
%A Maguire, Peggy
%A Meedom, Niels Henrik
%A Moore, Rebecca
%A Moore, Vanessa
%A Nagy, Dávid
%A McNamara, Hillary
%A Paakinaho, Anne
%A Pfeifer, Kerstin
%A Pylkkänen, Liisa
%A Rajamaki, Blair
%A Reviers, Evy
%A Röthlein, Christoph
%A Russek, Martin
%A Silva, Célia
%A De Valck, Dirk
%A Vo, Thuan
%A Bräuner, Elvira
%A Fröhlich, Holger
%A Furtado, Cláudia
%A Hartikainen, Sirpa
%A Kallio, Aleksi
%A Tolppanen, Anna-Maija
%A Haenisch, Britta
%T The EU project Real4Reg: unlocking real-world data with AI.
%J Health research policy and systems
%V 23
%N 1
%@ 1478-4505
%C London
%I BioMed Central
%M DZNE-2025-00395
%P 27
%D 2025
%X The use of real-world data is established in post-authorization regulatory processes such as pharmacovigilance of drugs and medical devices, but is still frequently challenged in the pre-authorization phase of medicinal products. In addition, the use of real-world data, even in post-authorization steps, is constrained by the availability and heterogeneity of real-world data and by challenges in analysing data from different settings and sources. Moreover, there are emerging opportunities in the use of artificial intelligence in healthcare research, but also a lack of knowledge on its appropriate application to heterogeneous real-world data sources to increase evidentiary value in the regulatory decision-making and health technology assessment context.The Real4Reg project aims to enable the use of real-world data by developing user-friendly solutions for the data analytical needs of health regulatory and health technology assessment bodies across the European Union. These include artificial intelligence algorithms for the effective analysis of real-world data in regulatory decision-making and health technology assessment. The project aims to investigate the value of real-world data from different sources to generate high-quality, accessible, population-based information relevant along the product life cycle. A total of four use cases are used to provide good practice examples for analyses of real-world data for the evaluation and pre-authorization stage, the improvement of methods for external validity in observational data, for post-authorization safety studies and comparative effectiveness using real-world data. This position paper introduces the objectives and structure of the Real4Reg project and discusses its important role in the context of existing European projects focussing on real-world data.Real4Reg focusses on the identification and description of benefits and risks of new and optimized methods in real-world data analysis including aspects of safety, effectiveness, interoperability, appropriateness, accessibility, comparative value creation and sustainability. The project's results will support better decision-making about medicines and benefit patients' health. Trial registration Real4Reg is registered in the HMA-EMA Catalogues of real-world data sources and studies (EU PAS number EUPAS105544).
%K Artificial Intelligence
%K European Union
%K Humans
%K Technology Assessment, Biomedical
%K Pharmacovigilance
%K Decision Making
%K Algorithms
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:40016823
%2 pmc:PMC11869640
%R 10.1186/s12961-025-01287-y
%U https://pub.dzne.de/record/277334