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Semi-automation of process analytics reduces operator effect

The aim of this study was to semi-automate process analytics for the quantification of common impurities in downstream processing such as host cell DNA, host cell proteins and endotoxins using a commercial liquid handling station. By semi-automation, the work load to fully analyze the elution peak o...

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Detalles Bibliográficos
Autores principales: Christler, A., Felföldi, E., Mosor, M., Sauer, D., Walch, N., Dürauer, A., Jungbauer, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125066/
https://www.ncbi.nlm.nih.gov/pubmed/31813007
http://dx.doi.org/10.1007/s00449-019-02254-y
Descripción
Sumario:The aim of this study was to semi-automate process analytics for the quantification of common impurities in downstream processing such as host cell DNA, host cell proteins and endotoxins using a commercial liquid handling station. By semi-automation, the work load to fully analyze the elution peak of a purification run was reduced by at least 2.41 h. The relative standard deviation of results among different operators over a time span of up to 6 months was at the best reduced by half, e.g. from 13.7 to 7.1% in dsDNA analysis. Automation did not improve the reproducibility of results produced by one operator but released time for data evaluation and interpretation or planning of experiments. Overall, semi-automation of process analytics reduced operator-specific influence on test results. Such robust and reproducible analytics is fundamental to establish process analytical technology and get downstream processing ready for Quality by Design approaches. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00449-019-02254-y) contains supplementary material, which is available to authorized users.