A general artificial neural network for the modelization of culture kinetics of different CHO strains |
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Authors: | T. Marique M. Cherlet V. Hendrick F. Godia G. Kretzmer J. Wérenne |
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Affiliation: | (1) Animal Cell Biotechnology, Université Libre de Bruxelles, CP 160/17, avenue F. D. Roosevelt 50, 1050 Brussels, Belgium;(2) Animal Cell Biotechnology, Université Libre de Bruxelles, CP 160/17, avenue F. D. Roosevelt 50, 1050 Brussels, Belgium;(3) Departament Engenyeria de Quimica, Universitat Autonoma de Barcelona, Spain;(4) Institut für Technische Chemie, University of Hannover, Germany |
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Abstract: | Animal cell cultures are characterized by very complex nonlinear behaviors, difficult to simulate by analytical modeling. Artificial Neural Networks, while being black box models, possess learning and generalizing capacities that could lead to better results. We first trained a three-layer perceptron to simulate the kinetics of five important parameters (biomass, lactate, glucose, glutamine and ammonia concentrations) for a series of CHO K1(Chinese Hamster Ovary, type K1) batch cultures. We then tried to use the same trained model to simulate the behavior of recombinant CHO TF70R. This was achieved, but necessitated to synchronize the time-scales of the two cell lines to compensate for their different specific growth rates. This revised version was published online in July 2006 with corrections to the Cover Date. |
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Keywords: | animal cells artificial neural network CHO growth kinetics modelization |
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