Imagine if you could test a new biological recipe in a computer simulation before ever touching a lab beaker. This project builds a digital 'mirror' of biological production, using AI to predict how microbes will behave. It's like having a flight simulator for bio-factories, reducing the guesswork and expensive trial-and-error.
Biotechnology R&D is currently too slow and expensive due to trial-and-error methods. Companies lack the high-quality, interoperable data needed to automate production and predict bioreaction outcomes.
A data fabric and compute environment for digital twins, and a standardized template for multiscale microbial datasets uploaded to the Yoda platform.
If you are a bio-based chemical producer dealing with slow R&D timelines—this project developed digital twins that shorten the time it takes to move from lab to market. This allows for more reliable and autonomous production systems.
If you are a bioprocess engineering firm dealing with unstable bioreactions—this project developed real-time monitoring and decision support systems. These tools enable online control to ensure consistent product quality.
If you are a circular bioeconomy startup dealing with unpredictable microbial behavior in waste valorization—this project developed a data fabric to organize microbial biodiversity data. This helps in selecting the best microbes for efficient waste conversion.
Based on available project data, specific pricing is not mentioned as the project focuses on creating services delivered by European research infrastructures.
Yes, the project specifically targets 'smart biomanufacturing' to drive distributed, autonomous, and highly adaptable production systems for the bioeconomy.
Based on available project data, the project emphasizes FAIR open science-compatible metadata and trusted data networks, but specific licensing terms are not provided.
The project is running from 2023 to 2026, with early prototypes of the data fabric and compute environment already in development.
It uses Process Analytical Technology (PAT) and real-time streaming to provide online monitoring and control of bioreactions.
The project is backed by a diverse group of 25 partners across 10 countries, showing strong European coordination. With a 24% industry ratio, including 6 SMEs and one global company, there is a clear bridge between academic research (18 university/research partners) and commercial application, ensuring the tools are built for real-world industrial needs.
Contact INRAE (France) for details on RI service access.
Contact SciTransfer to identify the specific AI models or digital twin prototypes available for your bioprocess.
