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Newsletter September 2024 | |||||
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Deep dive: The challenge of causal inference in RWD analysisCausal machine learning (ML) is an evolving field that aims to model and infer cause-and-effect relationships in data. Unlike traditional ML, which focuses primarily on making predictions based on associations in data, causal ML seeks to answer questions about the effects of an intervention, e.g. via a drug, from data that may have been collected under real-world conditions (real-world data - RWD). The challenge arising in this context is, however, that unlike the situation in a randomised controlled trial (RCT), patients taking a specific drug might demonstrate systematic differences to patients who were not treated with that drug, because the treatment is a consequence of an informed decision by a doctor. Thus, the naive comparison of treated and untreated patients could be affected by statistical confounders and thus lead to wrong conclusions about the effectiveness and safety of a drug under real-world conditions. The fundamental problem in this regard is that one can only observe the factual outcome of a given treatment assignment for an individual, but not the opposite.
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Partner Presentation: Fraunhofer SocietyThe Fraunhofer Society is a non-profit,
translational research organisation with 76 institutes spread
throughout Germany, each focusing on different fields of applied
science. With around 30.000 employees and an annual research budget
of about €2.9 billion it is the biggest organization for applied
research in Europe. Although base funding comes from the German
government, more than 70% is earned through contract work, either
for government-sponsored projects or from industry. Aims The AI & Data Science team at Fraunhofer
SCAI is composed of around 20 individuals at different career stages
with a background in computational sciences (computer science, life
science informatics, bioinformatics, biomedical engineering) and
headed by Prof. Dr. Holger Fröhlich. Role in Real4Reg In Real4Reg, the AI & Data Science team is responsible for leading Work Package 3. The goal of Work Package 3 is to develop a programming library designed to support data scientists in regulatory agencies. By the end of the project, this library is expected to offer a wide range of functionalities, including:
To achieve these objectives, Work Package 3 collaborates closely with Work Packages 1 and 2, which focus on defining and implementing specific medical use cases.
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Real4Reg 2024 workshops on October 14On October 14, Real4Reg will host two dedicated workshops. The first, "Insights into Stakeholder Needs", is a specialized session designed to showcase the Real4Reg survey results, and to explore how these insights can shape effective training programs. Later in the day, a workshop specifically tailored for patients and the lay public, "Demystifying Real-World Data - Insights for Patients", will aim to clarify the complexities of real-world data (RWD) and its impact on healthcare.
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Presentation of Real4Reg survey results in Dresden, GermanyIn early September, Dresden was the venue of a joint conference of five German medical associations, enabling cross-sectional knowledge sharing across a range of scientific expertise. This was the first time the five societies German Society for Medical Informatics, Biometry and Epidemiology (GMDS), German Society for Social Medicine and Prevention (DGSMP), German Society for Epidemiology (DGEpi), German Society for Medical Sociology (DGMS), German Society for Public Health (DGPH) came together to exchange ideas and learnings in their respective fields. Almost 2000 scientists attended the conference and discussed topics such as discussed topics related to epidemiology, health technology assessment and public health such as gender, planetary/environmental health, artificial intelligence, and patient involvement.
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Real4Reg Consortium meetingsOn June 26-27, the Real4Reg Consortium held a hybrid consortium meeting at CSC – IT Center for Science in Helsinki, Finland. The opportunity to gather partners face-to-face strengthened bonds within the Consortium and facilitated the effective exchange of ideas. This month, on September 19, the third Real4Reg Consortium Meeting in 2024 took place online, and focused on analysis topics.
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Upcoming Events14 October 2024, online - Real4Reg Workshop:
Real4Reg - Insights into Stakeholder Needs 14 October 2024, online - Real4Reg
Workshop: Demystifying Real-World Data - Insights for Patients 18-20 November 2024, Copenhagen, Denmark -
NorPEN 16th Annual meeting 20 November 2024, Lisbon,
Portugal - Annual Conference of INFARMED (Portuguese
National Authority of Medicines and Health Products) 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 |
