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This funding call focuses on advancing the European bioeconomy by leveraging terrestrial natural products to develop bio-based solutions across industries. The initiative aligns with European policies such as the European Green Deal and bioeconomy strategy, aiming to enhance circular and bio-based value chains. The call emphasizes the integration of modern biodiscovery approaches with digital and biotechnological tools, targeting bioactive compounds for high-value applications in sectors like pharmaceuticals, cosmetics, and agriculture. Projects are expected to achieve Technology Readiness Levels (TRL) 6-7 by completion. Key focus areas include computational innovations, biodiversity preservation, and biotechnology-driven production methods. Collaboration, biodiversity conservation, and sustainability assessments are vital aspects of the projects.
Opening: 06-05-2025
Deadline(s): 17-09-2025
Data provided by Ghent University
This funding opportunity represents a pre-agreed draft that has not yet been officially approved by the European Commission. The final, approved version is expected to be published in the first quarter of 2025. This draft is provided for informational purposes and may be used to preliminarily form consortia and develop project ideas, but it is offered without any guarantees or warranties.
Expected Outcome
• Broadened range of sustainable bioactive natural products with market applications.
• Advances in computational tools and methods for biodiscovery.
• Increased commitment to biodiversity conservation through biotechnological production.
• Enhanced stakeholder engagement supporting biotechnology and bio-based innovation.
Scope
• Modern biodiscovery approaches integrating '-omics' and bioinformatic tools.
• Identification and upscaling of bioactive natural compounds for high-value applications.
• Safe and sustainable production of natural products, adhering to the 'Safe and Sustainable by Design' framework.
• Biodiversity preservation and avoidance of unsustainable harvesting.
• Digital optimization of biodiscovery processes using AI and computational methods.
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