FIP is the abbreviation of fermentation intelligent platform which is a technical platform that enables the development of an efficient and speedy fermentation process. The platform combines metabolic models, computational fluid models and AI algorithms to digitalise the fermentation process. Thanks to the fast simulation ability, the platform can quickly figure out the best feeding and upscaling strategy.

Simply speaking, it saves research time and cost while guaranteeing much higher production efficiency. The fermentation process is extremely complicated. Most industrial players are not willing to spend the effort to understand such a “black box”, but rather rely on “expert’s experience” to optimise the process through trial and error. However, this old-fashioned way of process optimisation is time-consuming and costly. The big gap between laboratory and mass production often results in a long development time through trial-and-error testing. On the contrary, the FIP provides the best feeding strategy based on the actual metabolic activities of microbes and the growing environment, avoiding endless trial-and-error testing.

Both. The FIP models are over different scales, from lab-scale, pilot-scale, and production-scale. Due to the geometry variation of bioreactors, we adjust computational fluid models of R&D and production stages to realise a more realistic metabolite distribution prediction. On the lab scale, FIP can calculate the best media composition, while on the pilot-scale and production scale, FIP can also provide the best feeding strategy. Moreover, FIP can compare the key parameters obtained through real-time monitoring with established digital models so that corresponding measures can be quickly taken to improve the fermentation process if any anomalies occur.

Biomass, enzymes, chemicals, materials and a lot of pharmaceutical products. FIP covers metabolic models of various cell types from yeasts, fungi and bacteria. Therefore, it can be applied in realising an efficient production of most fermentation-based bioproducts.