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Artículo

Novel chemometric strategy based on the application of artificial neural networks to crossed mixture design for the improvement of recombinant protein production in continuous culture

Didier, Caroline; Forno, Angela GuillerminaIcon ; Etcheverrigaray, MarinaIcon ; Kratje, Ricardo BertoldoIcon ; Goicoechea, Hector CasimiroIcon
Fecha de publicación: 09/2009
Editorial: Elsevier Science
Revista: Analytica Chimica Acta
ISSN: 0003-2670
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Química Analítica

Resumen

The optimal blends of six compounds that should be present in culture media used in recombinant protein production were determined by means of artificial neural networks (ANN) coupled with crossed mixture experimental design. This combination constitutes a novel approach to develop a medium for cultivating genetically engineered mammalian cells. The compounds were collected in two mixtures of three elements each, and the experimental space was determined by a crossed mixture design. Empirical data from 51 experimental units were used in a multiresponse analysis to train artificial neural networks which satisfy different requirements, in order to define two new culture media (Medium 1 andMedium 2) to be used in a continuous biopharmaceutical production process. These media were tested in a bioreactor to produce a recombinant protein in CHO cells. Remarkably, for both predicted media all responses satisfied the predefined goals pursued during the analysis, except in the case of the specific growth rate (µ) observed for Medium 1. ANN analysis proved to be a suitable methodology to be used when dealing with complex experimental designs, as frequently occurs in the optimization of production processes in the biotechnology area. The present work is a new example of the use of ANN for the resolution of a complex, real life system, successfully employed in the context of a biopharmaceutical production process.
Palabras clave: Artificial neural networks , Crossed mixture experimental design , Culture medium formulation
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/103968
URL: http://www.sciencedirect.com/science?_ob=ArticleListURL&_method=list&_ArticleLis
DOI: http://dx.doi.org/10.1016/j.aca.2009.07.051
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Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Citación
Didier, Caroline; Forno, Angela Guillermina; Etcheverrigaray, Marina; Kratje, Ricardo Bertoldo; Goicoechea, Hector Casimiro; Novel chemometric strategy based on the application of artificial neural networks to crossed mixture design for the improvement of recombinant protein production in continuous culture; Elsevier Science; Analytica Chimica Acta; 650; 2; 9-2009; 167-174
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