Dynamic modelling and optimisation of a mammalian cells process using hybrid grey-box systems
In this work a model-based optimisation study of fed-batch BHK-21 cultures expressing the human fusion glycoprotein IgGl-IL2 was performed. Due to the complexity of the BHK metabolism it is rather difficult to develop an accurate kinetic model that could be used for optimisation studies. Many kinetic expressions and parameters are involved resulting in a complex identification problem. For this reason an alternative more cost-effective methodology was adopted, based on hybrid grey-box models. It was concluded that modulation particularities of BHK cultures were effectively captured by the hybrid model, this being of crucial importance for the successful optimisation of the process operation. From the optimisation study it was concluded that the glutamine and glucose concentrations should be maintained at low levels during the exponential growth phase and then glutamine feeding should be increased. In this way it is expected that both the cell density and final product titre can be considerably increased.
KeywordsFeedforward Neural Network Baby Hamster Kidney Glutamine Concentration Baby Hamster Kidney Cell Material Balance Equation
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