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Enabling efficient cell engineering leaving gene-expression BURden OUT for cell therapies and biopharmaceutical industry

Project description

Novel software to expedite cell engineering for biopharmaceuticals and cell therapy

Mammalian cell engineering is boosting the development of cell-based therapies for challenging diseases including cancer and the production of critical biopharmaceuticals, such as monoclonal antibodies. However, the pipeline from design to commercialisation is long and expensive, particularly when multiple transgenes are involved. This complexity arises from the competition for limited intracellular resources, leading to unbalanced product expression that can diminish therapeutic effectiveness. Funded by the European Research Council, the BURnOUT project plans to develop innovative AI and machine learning software that should streamline this process by optimising gene sequences for mammalian cell engineering. The project will be validated in biopharmaceuticals and cell therapy contexts, aiming for broad application across life sciences, from AI and synthetic biology to drug technology.

Objective

Mammalian cell engineering has emerged as a new ground-breaking modality for the development of cell based therapies to treat several hard-to-cure diseases, including cancer (T cell-based immunotherapies) and to produce molecule with diagnostic and therapeutic applications such as monoclonal antibodies (mAbs), that are now a dominant product class in the biopharmaceutical industry. However, the pipeline for efficient design-test-commercialization of the product is long and expensive, even more so when cells must be engineered with two or more transgenes, an increasing need in T cell-based therapies or drug production (e.g. cells engineered to produce enzyme and co-enzymes, or antibody cocktails). At the core of the problem is the competition for a finite number of intracellular resources, transcriptional and translational, that cause an unbalanced expression of products thus hampering the therapeutic effect. BURnOUT is an Artificial Intelligence and Machine Learning based software that will provide, in an automated manner, paired gene sequence optimisation to accelerate the process of mammalian cell engineering. BURnOUT will be validated in two different settings: one for the biopharmaceutics (engineered CHO cell lines for antibodies production) and one for cell therapy (engineering T cells for multiple CARs expression). The successful validation of the technology will be of trans-and multi-disciplinary interest and will have the goal of targeting the amplest variety of markets in Life Science, from AI to synthetic biology for cell and gene therapies and global cell technologies for drug industry. We envision that BURnOUT will respond to current strategic societal needs and challenges such as reduced costs of biopharmaceutics, and more effective treatment for cancer.

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Host institution

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA
Net EU contribution
€ 150 000,00
Address
VIA MOREGO 30
16163 Genova
Italy

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Region
Nord-Ovest Liguria Genova
Activity type
Research Organisations
Links
Total cost
No data

Beneficiaries (1)