Vierte Helmholtz Munich Expert Hour im Deutschen Bundestag

Helmholtz Munich Expert Hour at the German Bundestag: The Future of Preventive Medicine

Events AI Diabetes IDF Computational Health IML

Science and politics came together once again at the German Bundestag: For the fourth time, Helmholtz Munich hosted the Helmholtz Munich Expert Hour on September 10, 2025. This dialogue format gives political decision-makers the opportunity to learn firsthand about current research findings and their relevance for health policy. This time, the event revolved around the guiding question: Future Prevention: How do we defeat Diseases with Screenings and AI? 

Helmholtz Munich pursues a clear goal: diseases should be detected before they even arise. To achieve this, researchers decode genetic predispositions, analyze the influences of lifestyle and environment, and use artificial intelligence to predict disease progression – for a healthier society. But how can this vision be translated into practice? 

Leading scientists and policymakers discussed this question at the Expert Hour in the Bundestag. After opening remarks by Stephan Albani, Member of the Bundestag and patron of the event, and Prof. Stephan Herzig, Research Director at Helmholtz Munich, two short keynotes offered concrete insights into current research approaches: 

Prof. Anette-Gabriele Ziegler, Director of the Institute of Diabetes Research, emphasized that despite significant progress in research, there remains a high need for early diagnosis and effective prevention of type 1 diabetes. Using the Fr1da health screening as an example, Ziegler demonstrated how early detection works: for the past ten years, children have been identified at an early, asymptomatic stage of the disease and closely monitored. The goal is to significantly improve care and prognosis. Early detection also provides access to therapies that can slow disease progression. The international platform GPPAD, led by Ziegler, goes even further: through newborn screening, researchers identify children with a genetic risk for type 1 diabetes, enabling the development of innovative preventive strategies. 

Prof. Julia Schnabel, Director of the Institute of Machine Learning in Biomedical Imaging, presented the potential of artificial intelligence for personalized prevention. By using specialized algorithms, characteristic features of healthy tissues can be detected automatically, allowing for faster and more precise analyses. This leads, for example, to shorter scan times while improving the quality of MRI imaging. This precision radiology opens new possibilities for early diagnosis, even before clinical symptoms appear, and enables a more efficient use of medical resources. 

The joint discussion between researchers and members of the German Bundestag focused on how modern preventive medicine can relieve the healthcare system and strengthen Germany as a hub of innovation. 

[Translate to German:]
Univ.-Prof. Dr. med. Anette-Gabriele Ziegler

Institute Director, Chair of Diabetes and Gestational Diabetes, Klinikum rechts der Isar and Technical University of Munich, Director of the Global Platform for the Prevention of Autoimmune Diabetes (GPPAD)

View profile
Juli Schnabel_Zuschnitt
Prof. Dr. Julia Anne Schnabel

Director, Institute of Machine Learning in Biomedical Imaging

View profile

Related news

Expert Hour Bayerischer Landtag

Events, AI, Computational Health, AIH, IML,

Helmholtz Munich Expert Hour at the State Parliament: Focus on AI Potential in Medicine

For the first time, the Helmholtz Munich Expert Hour – an established dialogue format between science and politics – took place at the Bavarian State Parliament. At the invitation of Member of Parliament Maximilian Böltl and the Young Group of the…

Expert Hour im Bundestag

Events, Public Engagement, Computational Health, AIH, IML,

First "Expert Hour" at the German Bundestag: Data as a driver of innovation

Helmholtz Munich organized its first "Expert Hour" in the German Bundestag. With this new event format, Helmholtz Munich will regularly provide information on politically relevant health and research topics in the future and support work in the…