|Publisher DOI:||10.1007/978-1-0716-0191-4_12||Title:||Estimation of process model parameters||Language:||English||Authors:||Deppe, Sahar
Hass, Volker C.
Hernández Rodríguez, Tanja
Kuchemüller, Kim Beatrice
|Keywords:||Model implementation;Modeling;Parameter estimation;Programming||Issue Date:||2020||Source:||Methods in Molecular Biology (2095): 213-234 (2020)||Journal:||Methods in molecular biology||Abstract (english):||
Cell culture technology has become a substantial domain of modern biotechnology, particularly in the pharmaceutical market. Today, products manufactured from cells itself dominate the biopharmaceutical industry. In addition, a limited number of products made of in vitro cultivated cells for regenerative medicine were launched to the market. Modeling of such processes is an important task since these systems are usually nonlinear and complex. In this chapter, a framework for the estimation of process model parameters and its implementation is shown. It is aimed to support the parameter estimation task, which increases the potential of implementation and improvement of mathematical process models into the novel and existing bioprocesses. Apart from the parameter estimation, evaluation of the estimated parameters plays an essential role in order to verify these parameters and subsequently the selected model. The workflow is outlined and shown specifically on the basis of a mathematical process model describing a mammalian cell culture batch process.
|URI:||http://hdl.handle.net/11420/4617||ISSN:||1064-3745||Institute:||Bioprozess- und Biosystemtechnik V-1||Document Type:||Chapter (Book)||Project:||IBÖM04:mDoE-Toolbox2-Neue mDoE Software-Toolbox zur modellgestützten Optimierung biotechnologischer Prozesse|
|Appears in Collections:||Publications without fulltext|
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