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Mathematical model of biotechnology process to produce a recombin | 18619
Journal of Chemical Engineering & Process Technology

Journal of Chemical Engineering & Process Technology
Open Access

ISSN: 2157-7048

+44-20-4587-4809

Mathematical model of biotechnology process to produce a recombinant protein


3rd International Conference on Chemical Engineering

October 02-04, 2017 Chicago, USA

Grazia Leonzio

University of L'Aquila, Italy

Posters & Accepted Abstracts: J Chem Eng Process Technol

Abstract :

The aim of this research is to develop a mathematical model to describe the production of human antibody fragments of small size as ScFv, Fab, F(abâ�?�?), through fermentation of Escherichia coli BW25113 (ara). The fermentations are conducted in a fermenter (Chemap Ag) with a mechanical agitation. The entire phase of fermentation is monitored on-line using a data acquisition system MFCS/WIN. A kinetic and stochiometric models are developed. The stochiometric model describes the biological process of biomass growth. The kinetic analysis of experimental data about fermentation of E. coli is carried out for batch and fed-batch phase for the production process. The batch analysis is described by material balances of substrate and biomass with Monod and Pirt equations. The fed-batch phase is modeled using the material balances on biomass, substrate and product and analyzing the variation on volume during the time. Runge and Kutta algorithm is used to resolve the system equations. Result show that the equation that describe the growth of biomass is: C6H12O6+3.56O2+0.52ONH3â�?�?2.13CH1,92O0,3N0,24+3,87CO2+4,74H2O. For the Monod and Pirt law the following parameters are found by regression of experimental data during the batch phase: �?¼max is 0.55 h-1, Ks is 0.10 g/L, Yx/s is 0.35. The kinetics parameters that describe the fed-batch phase are the following: �?¼max is 0.24 h-1, Ks is 1.5 g/L, Yx/s is 0.34, m is 0.02, �?± is 0.00043, �?² is 0.00007, Yp/s is 0.00084. A sensitivity analysis is carried out to verify the efficiency of the mathematical model, varying the values of parameters about �?±10%: Evident variations are not present so the model is robust and stable. The realized mathematical models can be used to optimize the pilot plant and for the planning of the laboratory tests.

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