New opportunities and challenges for hybrid data and model driven bioprocess optimization and scale-up / 生物工程学报

Currently, biomanufacturing technology and industry are receiving worldwide attention. However, there are still great challenges on bioprocess optimization and scale-up, including: lacing the process detection methods, which makes it difficult to meet the requirement of monitoring of key indicators and parameters; poor understanding of cell metabolism, which arouses problems to rationally achieve process optimization and regulation; the reactor environment is very different across the scales, resulting in low efficiency of stepwise scale-up. Considering the above key issues that need to be resolved, here we summarize the key technological innovations of the whole chain of fermentation process, i.e., real-time detection-dynamic regulation-rational scale-up, through case analysis. In the future, bioprocess design will be guided by a full lifecycle in-silico model integrating cellular physiology (spatiotemporal multiscale metabolic models) and fluid dynamics (CFD models). This will promote computer-aided design and development, accelerate the realization of large-scale intelligent production and serve to open a new era of green biomanufacturing.

Progress in intelligent control of industrial bioprocess / 生物工程学报

Industrial bioprocess is a complex systematic process and bio-manufacturing can be realized on the basis of understanding the metabolism process of living cells. In this article, the multi-scale optimization principle and practice of industrial fermentation process are reviewed, including multi-scale optimizing theory and equipment, on-line sensing technology for cellular macroscopic metabolism, and correlated analysis of physiological parameters. Furthermore, intelligent control of industrial bioprocess is further addressed, in terms of new sensing technology for intracellular physiological metabolism, big database establishment and data depth calculation, intelligent decision.