Real-time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed-batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, namely, cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre-processed using moving average. Later, it was modeled through a nonlinear theoretical Cole-Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole-Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration. The Cole-Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real-time process decisions to achieve desired productivity and product quality.

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This study focuses on optimization of the substrate feeding profile for enhanced production of ranibizumab, a recombinant therapeutic protein, in Escherichia coli. An established process analyzer, dielectric spectroscopy, was deployed to monitor the production process and to estimate real-time biomass. A validated mechanistic model was employed to formulate a multiobjective optimization (MOO) problem. The substrate flow rate during the fed-batch phase (F) was taken as the decision variable for MOO. The Pareto front resulting from MOO revealed that for a minimum broth volume (V) of 1.96 L, a maximum of 58.8 g of total biomass (XV) could be generated. The total biomass obtained from the optimal substrate feeding profile was 20.6% higher than the experimentally achieved total biomass. Enhanced productivity was achieved by the proposed MOO formulation, which facilitates the choice of any operating point from the Pareto front based on downstream expenses of the therapeutic product.

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