Projektbeschreibung
Nutzung biointelligenter Design-Bau-Test-Lern-Zyklen zur besseren Erprobung von Innovationen
Eine nachhaltige Kreislaufwirtschaft kann die Umwelt schützen und die Folgen des Klimawandels mildern, indem sie das Abfallaufkommen und die Treibhausgasemissionen reduziert. Innerhalb eines Ansatzes in Richtung der kreislauforientierten Bioökonomie werden nachhaltige Substrate in Bioprozessen verarbeitet, um ein ganzes Spektrum an Innovationen zu realisieren. Die Erprobung von Lösungen aus der synthetischen Biologie unter industriellen Bedingungen gestaltet sich jedoch immer noch schwierig, weshalb viele Innovationen nicht auf den Markt gelangen. Das EU-finanzierte Projekt BIOS wird diese Herausforderung annehmen und einen biointelligenten Design-Bau-Test-Lern-Zyklus für die Reifung neuer Innovationen in der synthetischen Biologie einführen. Dabei wird eine Mischung aus biologischen und mechanischen Technologien und Verfahren zum Einsatz kommen, um das Erreichen der Endphase effizienter und einfacher zu gestalten.
Ziel
The usage of fossil resources leading to increasing atmospheric CO2 levels and global climate change should be rapidly replaced by implementing a circular economy. Circular bioeconomy converting sustainable substrates in moderately operating bioprocesses offers a plenitude of solutions. While synthetic biology provides a multitude of tools for strain engineering, their rapid use in hosts for optimal performance under industrial conditions is still challenging. Promising innovations are often trapped in the ‘valley-of-death’ as strain engineering faces a too complex space of putative manipulations. Novel approaches are needed to increase speed and success rate of strain and bioprocess engineering.
The bio-intelligent approach, rigorously applied in BIOS, aims to accelerate and improve the conventional ‘design-build-test-learn’ (DBTL) cycle for strain and bioprocess engineering. Interdisciplinary collaboration will bridge microbiology, molecular biology, biochemical engineering with informatics, automation engineering, and mechanical engineering. Novel innovative metrics, biosensors, and bioactuators are developed for bi-directionally communication at biological-technical interfaces. Digital twins are created mimicking cellular and process levels. Integrating AI not only improves prediction quality but also enables hybrid learning, the key reason to increase speed and success rate in the novel bio-intelligent DBTL cycle (biDBTL). The power of biDBTL will be showcased by creating P. putida producer strains for terpenes, polyolefines, and methylacrylate. All are highly attractive products with a high potential for reducing anthropogenic greenhouse footprint. BIOS will open the door to a de-centralized, networked collaboration for strain and process engineering that efficiently links individual expertise for the sake of a symbiotic and rapid progress. BIOS also paves the way to de-centralized bio-manufacturing by implementing autonomous, self-controlled bioprocesses.
Wissenschaftliches Gebiet
Not validated
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- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsbiosensors
- engineering and technologychemical engineeringbiochemical engineering
- natural sciencesbiological sciencessynthetic biology
- engineering and technologymechanical engineering
- social scienceseconomics and businesseconomicssustainable economy
Schlüsselbegriffe
Programm/Programme
Thema/Themen
Aufforderung zur Vorschlagseinreichung
HORIZON-CL4-2021-DIGITAL-EMERGING-01
Andere Projekte für diesen Aufruf anzeigenFinanzierungsplan
HORIZON-RIA - HORIZON Research and Innovation ActionsKoordinator
70174 Stuttgart
Deutschland