dc.contributor |
Chotteau, Veronique |
dc.contributor.author |
Aliaga Navarro, Antonio |
dc.date |
2010-02-06 |
dc.identifier.uri |
http://hdl.handle.net/2099.1/9879 |
dc.language.iso |
eng |
dc.publisher |
Universitat Politècnica de Catalunya |
dc.rights |
Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject |
Àrees temàtiques de la UPC::Enginyeria química::Biotecnologia |
dc.subject |
Cell culture -- Computer simulation |
dc.subject |
Cultius cel·lulars -- Simulació per ordinador |
dc.title |
Metabolic reaction network approach for CHO modelling culture |
dc.type |
info:eu-repo/semantics/bachelorThesis |
dc.description.abstract |
Projecte realitzat en col.laboració amb Kungliga Tekniska Högskolan. Bioprocess Department |
dc.description.abstract |
Animal cell culture has provided several beneficial improvements in the field of biotechnology. Nowadays, the engineers have focused their work in the optimization of cell cultures techniques. One important tool used is the simulation by computer since it is inexpensive, requires less time than other methods and it is a simple way of understanding the behaviour of the cells in a culture.
This Thesis worked in the design of one simulator that describe the evolution over time of the extracellular metabolites and cell growth of CHO culture. A model that was designed using the concept of metabolic reaction network and the assumption of pseudo-steady state was checked and validated using diverse set of experimental data. In order to trigger different metabolic routes in the cells, these experiments were carried out varying amino acid composition in the medium.
The metabolic reaction network was simplified and consisted in 38 reactions. The set of experimental data was simulated using a graphical interface design in the present Thesis. The model succeeded since the results were very satisfactory. The error was, in general, small and it was checked that the system could also detect the different metabolic pathways that the cells follow when the initial conditions are modified in many metabolites. The model can also be applied without the information of all the essential amino acids, obtaining highly satisfying results as well. |