Accelerating discovery in biomanufacturing
JFAB (JBEI Framework for AI-driven Bioautomation) is an integrated, end-to-end platform for predictive biology that links design, build, test, and learn cycles into a continuous, data-driven engine for discovery and scale-up.
By combining automated experimental infrastructure with a robust data integration system and sophisticated AI and machine learning tools, JFAB enables researchers to transition from a hypothesis to a validated biological function with unprecedented speed. Datasets resulting from these experiments are continuously reintegrated into AI models, creating a self-improving system where biological design becomes increasingly predictive — reducing development timelines, lowering costs, and enabling the transition to a scalable bioeconomy.
JFAB Goals
- Use AI and automation to solve the most pressing challenges in biomanufacturing and develop and deploy new solutions for the production of a wide range of bioproducts.
- Leverage automation and data integration strategies to generate the significant volume of data necessary for AI applications, with a focus on producing high-content, high-quality, deeply informative datasets.
- Establish seamless, end-to-end workflows that execute biological design, strain construction, screening, and data capture and management with minimal human intervention.
