SOURCE-LINKED INTELLIGENCE
Enabling efficient cell engineering leaving gene-expression BURden OUT for cell therapies and biopharmaceutical industry
he 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.
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 150000
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.