Purpose
The Challenge Programme aims to contribute substantially to the development of Danish and European research ecosystems within research areas of strategic priority to the Novo Nordisk Foundation. The goal is to develop innovative solutions to major scientific challenges, supporting leading researchers to form a consortium united by a clear vision and mission.
The Programme provides funding to enable scientific depth and focus and facilitate synergy between the research partners.
The grants awarded within the Challenge Programme will broadly fit within the Novo Nordisk Foundation Strategy.
A webinar covering the Challenge Programme and theme will be held on 12 June 2025.
The Novo Nordisk Foundation will hold an interactive hybrid workshop on 28 August 2025 to support networking and knowledge sharing around the theme.
Research Theme 2026
The Challenge theme uncovers the mechanisms driving development, function and self-organisation of biological systems under non-equilibrium conditions.
Supported research will centre around establishing new or improved theoretical frameworks, this in combination with using state-of-the-art experimental techniques and recent advancements in computational methods. The research must be an interdisciplinary collaboration between fields such as biology, physics, chemistry, engineering or computer science.
The results from this Challenge may improve our understanding and prediction of complex systems under physiological conditions from single biomolecules to the organism level, with the potential to accelerate drug development, tissue engineering, regenerative medicine, or sustainable biotechnology.
Supported research may include but is not limited to:
- Mechanisms of self-organisation driving order and specialised function under non-equilibrium conditions.
- The drivers of self-assembled biological structures under non-equilibrium conditions.
- Complex biological behaviour driven by active processes involving protein interactions, molecular machines, cellular metabolism and signalling.
- Fundamental physical models for predicting dynamics of non-equilibrium biological systems.
- Novel experimental and AI-based methods to observe and quantify non-equilibrium biological processes in real-time