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Machine learning for integrated multi-parametric enzyme and bioprocess design

Sector: Water Supply and Storage • Location: Denmark, Italy, Spain, Austria, Netherlands, Croatia, Czechia, Germany, France

Source: EU Funding & Tenders Portal

Project
Forthcoming

Currently, our world is facing several global challenges like climate change, water pollution, land erosion, resource depletion and unsustainable manufacturing. Biotechnology can provide many solutions to these problems. One example is the development of sustainable bioprocesses, which is at the heart of the EU’s green deal. Enzymes are nature’s catalysts at the core of such transformation since t

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The project “Machine learning for integrated multi-parametric enzyme and bioprocess design” is an infrastructure initiative in the Water Supply and Storage sector, located in Denmark, Italy, Spain, Austria, Netherlands, Croatia, Czechia, Germany, France. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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forthcoming

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Description

Description

Currently, our world is facing several global challenges like climate change, water pollution, land erosion, resource depletion and unsustainable manufacturing. Biotechnology can provide many solutions to these problems. One example is the development of sustainable bioprocesses, which is at the heart of the EU’s green deal. Enzymes are nature’s catalysts at the core of such transformation since they can catalyse complex biocatalytic reactions. Biocatalysis has been slowly but gradually displacing traditional organic chemistry in several processes by virtue of its better efficacy, with the added value of being less wasteful as evidenced by the cornucopia of EPA Green Chemistry Awards conferred to enzymatic processes. Thanks to protein directed evolution (Nobel Prize 2018), enzyme function can be tailored to new-to-nature industrial conditions within bioreactors. However, there are still many challenges limiting bioprocess scalability, owing to a lack of deep understanding of enzyme function and of efficient strategies to overcome the complex multi-factorial optimisation problem of both enzymes and bioprocesses. To address this gap, also known as the valley of death (i.e., a large investment gap between fundamental and applied research), ELEGANCE will offer a unique educational program combining state-of-the-art experimental and computational approaches including data science and artificial intelligence to design better enzymes and bioprocesses faster. The main goal is to train a new generation of specialists with essential hard and soft skills for transforming biocatalysis into a data-driven discipline to accelerate bioprocess development, thereby anticipating potential challenges arising in the valley of death. ELEGANCE will focus on enzymes catalysing highly selective oxyfunctionalisation reactions, unattainable through existing chemical technology, with ecological and economic attractiveness to enable the transition to a circular bioeconomy in many industries.

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High

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100%

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