Model-based DoE for feed batch cultivation of a CHO cell line
© Möllerl et al. 2015
Published: 14 December 2015
Process optimization deals with various parameters and statistical methods to guarantee consistent cell grow than product quality. Even if high throughput systems can handle these parameter combinations in parallel experiments, the heuristic restriction of boundaries can result in stepwise iterations with many experiments. This can make the way from process development to process establishment even more troublesome, since academia or start-up research facilities might not have the possibility to perform these experiments. The optimization of complex biotechnological production processes with approved Design of Experiment (DoE) methods is therefore time-consuming and cost-intensive. The use of DoE tools in combination with an appropriate growth model might be a valuable tool to develop and to test fed-batch strategies in silico before experiments are carried out in the laboratory. To approve this concept, a two-step growth process with media exchange followed by a fed-batch with an optimized feeding profile was designed using DoE tools in silico.
Material and Methods
< 0.5 mM
< 0.1 mM
The process was optimized using a model based design instead of performing various experiments in the laboratory. Based on a few shaking flask experiments for kinetic parameter determination,the model was tested for data generation on common fed-batch strategies. Optimized conditions were selected by means of DoE strategies and tested experimentally. In this way, suitable fed-batch strategies for mammalian cell lines were evaluated in silico before bioreactor experiments had to be performed.This results in a significant reduction of required experiments and is therefore an inexpensive and time-saving alternative to entire statistical optimization methods.
The cell line CHO-XM-111 (CCOS-837) was obtained from the Culture Collection of Switzerland, Wädenswil.
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