title: Estimation of biomass concentrations in fermentation processes for recombinant protein production.
abstract: Online biomass estimation for bioprocess supervision and control purposes is addressed. As the biomass concentration cannot be measured online during the production to sufficient accuracy, indirect measurement techniques are required. Here we compare several possibilities for the concrete case of recombinant protein production with genetically modified Escherichia coli bacteria and perform a ranking. At normal process operation, the best estimates can be obtained with artificial neural networks (ANNs). When they cannot be employed, statistical correlation techniques can be used such as multivariate regression techniques. Simple model-based techniques, e.g., those based on the Luedeking/Piret-type are not as accurate as the ANN approach; however, they are very robust. Techniques based on principal component analysis can be used to recognize abnormal cultivation behavior. For the cases investigated, a complete ranking list of the methods is given in terms of the root-mean-square error of the estimates. All techniques examined are in line with the recommendations expressed in the process analytical technology (PAT)-initiative of the FDA.
authors.affiliation: Institute of Bioengineering, Martin-Luther-University Halle-Wittenberg, 06120, Halle/Saale, Germany.
authors.forename: Marco
authors.initials: M
authors.lastname: Jenzsch
authors.forename: Rimvydas
authors.initials: R
authors.lastname: Simutis
authors.forename: Günter
authors.initials: G
authors.lastname: Eisbrenner
authors.forename: Ingolf
authors.initials: I
authors.lastname: Stückrath
authors.forename: Andreas
authors.initials: A
authors.lastname: Lübbert
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D049109:Cell Proliferation; D015169:Colony Count, Microbial / Q000379:methods*; D003198:Computer Simulation; D004926:Escherichia coli / Q000166:cytology / Q000235:genetics / Q000254:growth & development* / Q000378:metabolism*; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism*; D005285:Fermentation / Q000502:physiology; D008954:Models, Biological; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods; D015202:Protein Engineering / Q000379:methods; D011994:Recombinant Proteins / Q000096:biosynthesis*
chemical_list: D029968:Escherichia coli Proteins; D011994:Recombinant Proteins