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Newsletter October 2025 | |||||||||
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Dear Subscriber, In this issue, we present an article entitled “Machine learning on sensitive data”, showing the potential of this field. Here you will be able to find an explanation about the topic, understand how confidentiality is maintained, explore how it is being used in Real4Reg and take a look at future developments. Also, we introduce our partner Finnish Centre for Scientific Computing (CSC). Furthermore, you’ll be able to find news about a new Metadata Catalogue section on our website, participation in scientific events in early October and information about upcoming events. | |||||||||
Machine learning on sensitive dataReal-world data with machine learning Unsupervised learning (UL) is an approach that can be used on measurements that either contain labels or not, and is dependent on the question to be answered. Should the measurements contain labels, or there is some inference about the possible number of categories, UL is used to estimate the cardinality and the "nature" of the measurement distributions. In the context of real-world data (RWD), that is, patient-level observational data collected from clinical care, ML may provide a flexible set of tools for conducting statistical analyses of data where the measurements may be a mixture of numerical and/or non-numerical types. Sections in this issue:
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Partner presentation: CSC - IT Center for ScienceCSC - IT Center for Science is Finland’s leading provider of high-performance computing (HPC) and data management services for research and innovation. Its expertise spans HPC resource management, distributed training for artificial intelligence (AI) and machine learning (ML), data handling pipelines, and secure, efficient access to computing power, enabling cutting-edge scientific and industrial applications. CSC operates LUMI, one of the world’s most powerful supercomputers, and the LUMI AI Factory, a pioneering service infrastructure that combines HPC, high-value data, and AI expertise to accelerate AI innovation. Aims A primary aim of CSC is to build digital solutions for data management, scientific computing, and education that help researchers, learners, and companies understand the world, in a user-friendly manner and with cutting-edge resources. CSC supports the digitalization of society and promotes the green transition with its customers, owners, and partners, always with integrity and in compliance with ethical requirements. CSC is a company entrusted with special state assignment and is
jointly owned by the state of Finland and Finnish higher education
institutions, showing commitment to research and innovation. The
customers of CSC include universities and universities of applied
sciences, research institutes and infrastructures, public
organizations and companies. Role in Real4Reg CSC contributes to topics related to data science, ML, and AI in the Real4Reg consortium, including data analysis tasks using the CSC Sensitive Data Desktop. CSC plays a crucial role in Work Package 3 – Methodology & Tools, whose main goal is to develop and implement data science algorithms which will later be integrated into a tool package available for the scientific community. Specifically, CSC is leading the development of a method to construct synthetic control arms using RWD and AI/ML algorithms to predict drug safety related issues.
CSC - IT Center for Science in media
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Metadata Catalogue – New Section on Our WebsiteWe’ve added a new section to our website for you to explore. Here
you’ll be able to find information about the different data sources
from Denmark, Germany, Finland and Portugal that are being used were
used in this project. This section reunites crucial details, for
example the years covered by the data source or the content
withdrawn from it.
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Participation in Scientific Events – Early OctoberOn previous days, Real4Reg members participated in multiple scientific events. The work of the project was presented and discussed at the GetReal Institute 2025 Annual Conference in Utrecht (Netherlands) through the presentation of two posters — “Feasibility of Supplementing Single-Arm Trials with External Control Arms: Evaluation of German Real-World Data” and “Insights from an EU-Wide Stakeholder Survey on Real World Evidence in the Regulatory Process” —, an oral communication — “Exploring the Role of Target Trial Emulation” —, and participation in a panel discussion — “From RWD to Decision-Grade RWE”. Real4Reg was also presented to the scientific community in the
remote workshop “Real-World Evidence for Post-Marketing Regulatory
Decisions”, organised by the Saudi Food and Drug Authority (SFDA).
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Upcoming Events9-12 November 2025, Glasgow, UK 13-14 November 2025, Jena, Germany 19-21 November, Uppsala, Sweden 5-7 December, San Diego, USA For more information on additional events in the realms of real-world data, artificial intelligence, and health, please consult our Events page. | |||||||||
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RealReg is a project funded by the European Union under the Horizon Europe programme –Project No. 101095353. The consortium of ten European institutions aims to promote the use of real-world data to support regulatory decisions about medicines. For media inquiries, please contact: real4reg@infarmed.pt Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them. | |||||||||
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ImprintFederal Institute for Drugs and Medical Devices
(BfArM) Headquarters Bonn: Headquarters Cologne: Phone: +49 (0)228 99 307-0 If you don't want to receive this mailing anymore, you can unsubscribe with your email adress here: unsubscribe link. |
