Control of cultivation processes for recombinant protein production: a review

Abstract

The current state-of-the-art in control of cultivation processes for recombinant protein production is examined including the quantitative knowledge that can be activated for this purpose and the measurement techniques that can be employed for control at industrial manufacturing sites.

Soft sensor control of metabolic fluxes in a recombinant Escherichia coli fed-batch cultivation producing green fluorescence protein

“…Previous reports with E. coli producing recombinant proteins have also shown significant variability under identical or similar culture conditions. For example, in a study by Lübbert and coworkers [12] a batch-to-batch variability of protein expression of + 25% five hours after induction was shown. This is on the same level as in observed here.…”

“…Especially this latter soft sensor provided a useful sensor tool that supports the intention with the PAT initiative [12,23]. It shows that soft sensor based control is advantageous and can contribute to collect more data using on-line monitoring in combination with relatively uncomplicated mathematical modeling.…”

“…A variety of combinations of soft sensor is reported for process monitoring and control applications in industry [4][5][6][7]. During the past ten years, the soft sensors have also extensively been discussed in biotechnology, in particular for the monitoring and control of bioreactors [8][9][10][11][12][13][14]. Biomass growth, for example, has been estimated by soft sensors based on base titration [15,16], absorbance measurement [11], and exhaust gas analysis [12] using mechanistic models.…”

“…During the past ten years, the soft sensors have also extensively been discussed in biotechnology, in particular for the monitoring and control of bioreactors [8][9][10][11][12][13][14]. Biomass growth, for example, has been estimated by soft sensors based on base titration [15,16], absorbance measurement [11], and exhaust gas analysis [12] using mechanistic models. Other soft sensors have used regression models, multivariate models, and neural networks [17] in combination with on-line fluorimetry [18] and multisensor arrays [19].…”

“…production of antibiotics [10]. In microbial processes, examples include feedback control of specific growth rate from gas mass balance [11,12] and monitoring of oxygen and carbon dioxide gases for estimating biomass on-line [20][21][22]. In other studies the soft sensors have controlled the nutrient feeding to the fed-batch by monitoring key metabolites as acetate by on-line HPLC [11].…”