Abstract

Bioreactor optimization is a common engineering problem difficult to be solved due to the large number of influential variables of high variability. Production of monoclonal antibody is a well-known method to synthesize a large number of identical antibodies (that is of uniform characteristics, also called monoclonal antibodies, mAb). Due to such reasons intense efforts have been invested to maximize the production of mAb by using hybridoma cell culture. Based on an adequate kinetic model from literature (experimentally checked) this paper focus on pointing-out the major role of the net evolution of the viable biomass (growth, and decay) in the location of the optimal operating setpoint (SP) of a three-phase mechanically agitated batch bioreactor (TPMAB) with immobilized hybridoma culture. This in-silico analysis opens the possibility I) to optimize the bioreactor performances by placing the SP in the most favourable location, by adjusting the substrate and biomass initial load in the bioreactor according to the preliminary determined characteristics of a modified / improved biomass; ii) to optimize the batch-to-batch operation mode (not approached here) according to the time-varying characteristics of the biomass culture, or iii) to determine the optimal operation of the bioreactor in a fed-batch operating mode (not approached here).

Highlights

  • Over the last decades, there is a continuous trend to develop more and more effective bioreactors[1,2] to implement various biosyntheses for producing finechemicals or organic compounds in the food, pharmaceutical, or detergent industry, by using freesuspended or immobilized cell cultures in batch, semibatch, continuously operated fixed-bed, or continuously three-phase fluidized-bed reactors, aiming to replace complex chemical processes, energetically intensive and generating toxic wastes [3,4]

  • One application of tremendous importance in medicine is the industrial production of monoclonal antibodies, by the so-called Hybridoma technology, [8,9,10] by using antibody-secreting hybridoma cell cultures

  • Most important, as remarked by Dorka[12]; Li et al.[20], the large-scale production of monoclonal antibodies by mammalian cells in batch and fedbatch culture systems is limited by the unwanted decline in cell viability and reduced productivity that may result from changes in culture conditions

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Summary

TYPICAL VALUES FOR THE BIOMASS MAXIMUM

SPECIFIC GROWTH RATE (kg) AND OF THE MAXIMUM SPECIFIC DEATH/ DECAY RATE (kd) IN THE EQN.(3). Several values of the net this biomass evolution study, according troatteheknelit t=eraktgu-rekdinwfoilrlmbaetitoesnt.eTdhine biomass enhanced evolution might be explained by lot of operating variables not included in the common dynamic models of eq(2) form. Such variables could include [9,36]: the biomass [9,26,27,39]. Because not all the mentioned control variables are included in the adopted bioprocess dynamic model [24], the present paper will be focus on determining the following three control variables under certain operating alternatives: I) substrates initial concentrations, [GLC](0), [GLN](0); ii) inoculum inoculum size (that is initial cell preparation reasons, the tdoetanlsiintyit,iaXlνb,0i(ot)m; adsusewtioll be considered equal to the In mathematical terms, tvhiaeboleptoimneiz, aXtνi,o0(n=pXrto,0)b.lem can be formulated as following:. When significant inconsistecies between predicted optimal operating policy vs. experimental evidence are reported, such checks will lead to the process lumped model updating/completions, and re-estimation of some of their parameters for correcting its adequacy in order to perform futures bioreactor analyses, and to eventually correct its optimal operating policy

Bioreactor optimization results Formulation of the optimization problem
Results
Conclusions
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