The EU project Real4Reg : unlocking real-world data with AI

Abstract

<p><b>Background</b><br>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.</p><p><b>Methods</b><br>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.</p><p><b>Discussion</b><br>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.</p><p><i>Trial registration</i> Real4Reg is registered in the HMA-EMA Catalogues of real-world data sources and studies (EU PAS number EUPAS105544).</p>