Summary
The success of phage therapies relies on correctly matching a therapeutic phage to bacterial strain. However calibration of therapy recipe may last for years. Presented solution enable to accelerate this by in silico simulations on AI platform for in vitro. It is able to find optimal phage that meets the phenotype imposed by the researcher, especially:
-predict given phage effectiveness against a specific bacteria strain,
-indicate mutations that increase phage effectiveness,
-generate explanations for predictions.
Currently, this process is performed by wet-lab employees (in vitro).
Replacing it with an in silico process will reduce the number 90 out of 100 experiments, significantly accelerating the process and improving phage therapy quality. At the same time, it’s the basis for modern probiotics (for microbiome modulation). At the same time, it will enable dynamically generate personalized therapies for specific patients. It is a novel endeavor in the area of molecular biology.
-predict given phage effectiveness against a specific bacteria strain,
-indicate mutations that increase phage effectiveness,
-generate explanations for predictions.
Currently, this process is performed by wet-lab employees (in vitro).
Replacing it with an in silico process will reduce the number 90 out of 100 experiments, significantly accelerating the process and improving phage therapy quality. At the same time, it’s the basis for modern probiotics (for microbiome modulation). At the same time, it will enable dynamically generate personalized therapies for specific patients. It is a novel endeavor in the area of molecular biology.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/190103838 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2024 |
| Total budget - Public funding: | 2 417 995,00 Euro - 1 692 596,00 Euro |
Cordis data
Original description
The success of phage therapies relies on correctly matching a therapeutic phage to bacterial strain. However calibration of therapy recipe may last for years. Presented solution enable to accelerate this by in silico simulations on AI platform for in vitro. It is able to find optimal phage that meets the phenotype imposed by the researcher, especially:-predict given phage effectiveness against a specific bacteria strain,
-indicate mutations that increase phage effectiveness,
-generate explanations for predictions.
Currently, this process is performed by wet-lab employees (in vitro).
Replacing it with an in silico process will reduce the number 90 out of 100 experiments, significantly accelerating the process and improving phage therapy quality. At the same time, it’s the basis for modern probiotics (for microbiome modulation). At the same time, it will enable dynamically generate personalized therapies for specific patients. It is a novel endeavor in the area of molecular biology.
Status
SIGNEDCall topic
HORIZON-EIC-2022-ACCELERATOROPEN-01Update Date
09-02-2023
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