H2020
Europeo
ExpectedOutcome:In line with the European Green Deal and other European initiatives such as the circular economy action plan, the industrial strategy, the bioeconomy strategy and the biodiversity strategy, the successful proposal should support the uptake of bio-based innovation, to improve European industrial[1] sustainability, competitiveness and resource independence. They should develop innovative bio-based products using the full benefits of artificial intelligence and other digital technology innovation. They should engage all stakeholders and improve their knowledge and understanding of science, notably biotechnology-based value chains, and improve benefits for consumers.
Project results tshould contribute to all of the following outcomes:
Use the full potential of artificial intelligence applications for prospecting, understanding and sustainably using biological resources within safe planetary boundaries.Digital tools, sensors and methods for improved efficiency, climate change adaptation and sustainability of industrial processes in the bio-based sectors considering the needs of stakeholders are integrated in innovative engineering solutions.Enha...
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ExpectedOutcome:In line with the European Green Deal and other European initiatives such as the circular economy action plan, the industrial strategy, the bioeconomy strategy and the biodiversity strategy, the successful proposal should support the uptake of bio-based innovation, to improve European industrial[1] sustainability, competitiveness and resource independence. They should develop innovative bio-based products using the full benefits of artificial intelligence and other digital technology innovation. They should engage all stakeholders and improve their knowledge and understanding of science, notably biotechnology-based value chains, and improve benefits for consumers.
Project results tshould contribute to all of the following outcomes:
Use the full potential of artificial intelligence applications for prospecting, understanding and sustainably using biological resources within safe planetary boundaries.Digital tools, sensors and methods for improved efficiency, climate change adaptation and sustainability of industrial processes in the bio-based sectors considering the needs of stakeholders are integrated in innovative engineering solutions.Enhanced monitoring, reporting and management of natural resources using artificial intelligence and other digital technology applications.
Scope:Engineering biology applications have grown beyond chemical production to include the generation of biosensor organisms for the lab, animal, and field, modification of agricultural organisms for nutrition and pest/environmental resilience, production of organisms for bioremediation, and live cell and gene/viral therapies. The rapid expansion of the field has resulted in new tools and new approaches. However, we are still challenged by the need for novel and more robust and interoperable computational tools and models for engineering biology. For example, improved models of synthetic systems (synthetic biology) and of their interaction with their host organisms could help enable more successful engineering.
This information infrastructure for biological design is at an early stage compared to engineering disciplines such as mechanical and electrical engineering, as the biomanufacturing field has emerged only recently. A critical bottleneck is a lack of established “design rules,” core aspects of biological and biomolecular function that apply to diverse systems and applications. Furthermore, technologies for the utilization, manufacture, and deployment of innovative bio-based systems are still under development. These roadblocks have hampered the development of standard computational frameworks to represent, process and store information on biological components, predict system behaviour, and diagnose failures. Therefore, widespread automation in the bio-based sectors remains out of reach.
A mature computational infrastructure for biodesign requires powerful access to information on biological parts and systems, their environments, their manufacturing processes, and their operations in and beyond the laboratory in which they are created. This in turn requires findable, accessible, interoperable, and reusable data that enable effective aggregation information on bio-based systems, their environments, and their processes of manufacture, and the establishment of standard models of data processing and analysis, including bioinformatics, biosensors, bioindicators, ‘-omics’ technologies that allow open-development and scalable execution in the bio-based sectors.
The topic aims to prevent pollution and sustainably manage and use natural resources within safe planetary boundaries, including in the deployment of the bioeconomy and the bio-based sectors. The topic focuses on bioinformatics, “cheminformatics” and artificial intelligence as approaches and tools to transform available information into biologically or biotechnologically applicable knowledge. It also aims to efficiently integrate digital technologies into bio-based operations to optimise value chains from a technical, economic, social and environmental point of view.
Proposals should:
Enable prospecting, understanding and sustainable use of biological resources based on their convergence with digital technologies that lead to optimised and more efficient bio-based operations.Identify and characterise advanced technologies, including artificial intelligence, and their benefits for the utilisation, manufacture, and deployment of innovative bio-based systems.Develop integrated biological designs and data models for improved prospecting, understanding and deployment of higher efficiency and sustainability of biological resources and industrial bio-based operations (e.g. bioinformatics, biosensors, bioindicators, data analysis, ‘-omics’ technologies).Improve the economic and environmental sustainability of bio-based operations.Focus on the integration of -omics and machine learning techniques such as active learning for the design-build-test-learn (DBTL) cycle.Develop improved models and model standards of synthetic systems (synthetic biology) and of their interaction with their host organisms to facilitate more successful engineering and broader application in the bio-based sectors.Establish bio computer-aided design (BioCAD) tools and design-of-experiment (DoE) approaches.Reinforce and maintain scientific infrastructures to integrate existing biodiversity information (species, habitats and environmental processes).Consider contributing data and results to the European Commission’s Knowledge Centre for Bioeconomy hosted by the JRC. For this topic, it is not mandatory to integrate the gender dimension (sex and gender analysis) into research and innovation.
Specific Topic Conditions:Activities are expected to achieve TRL 4-5 by the end of the project – see General Annex B.
Cross-cutting Priorities:Digital AgendaArtificial Intelligence
[1]In synergy with European partnerships under Cluster 6, in particular Circular Bio-based Europe (CBE).
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