Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 505810
Title 3D-liquid chromatography as a complex mixture characterization tool for knowledge-based downstream process development.
Author(s) Hanke, A.T.; Tsintavi, E.; Pilar Ramirez Vazquez, M. Del; Wielen, L.A.M. van der; Verhaert, P.D.E.M.; Sandt, E.J.A.X. van de; Eppink, M.H.M.; Ottens, M.
Source Biotechnology Progress 32 (2016)5. - ISSN 8756-7938 - p. 1283 - 1291.
Department(s) Bioprocess Engineering
Publication type Refereed Article in a scientific journal
Publication year 2016
Abstract Knowledge-based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three-dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behaviour of each component. Matching of the peaks across the different separation dimensions and against a high-resolution reference chromatogram allows to assign the determined parameters to pseudo-components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high-throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%. This article is protected by copyright. All rights reserved.
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