Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25382
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dc.contributor.authorMaschke, Rüdiger-
dc.contributor.authorPretzner, Barbara-
dc.contributor.authorJohn, Gernot T.-
dc.contributor.authorHerwig, Christoph-
dc.contributor.authorEibl, Dieter-
dc.date.accessioned2022-08-05T09:35:25Z-
dc.date.available2022-08-05T09:35:25Z-
dc.date.issued2022-07-25-
dc.identifier.issn2306-5354de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/25382-
dc.description.abstractShake flasks remain one of the most widely used cultivation systems in biotechnology, especially for process development (cell line and parameter screening). This can be justified by their ease of use as well as their low investment and running costs. A disadvantage, however, is that cultivations in shake flasks are black box processes with reduced possibilities for recording online data, resulting in a lack of control and time-consuming, manual data analysis. Although different measurement methods have been developed for shake flasks, they lack comparability, especially when changing production organisms. In this study, the use of online backscattered light, dissolved oxygen, and pH data for characterization of animal, plant, and microbial cell culture processes in shake flasks are evaluated and compared. The application of these different online measurement techniques allows key performance indicators (KPIs) to be determined based on online data. This paper evaluates a novel data science workflow to automatically determine KPIs using online data from early development stages without human bias. This enables standardized and cost-effective process-oriented cell line characterization of shake flask cultivations to be performed in accordance with the process analytical technology (PAT) initiative. The comparison showed very good agreement between KPIs determined using offline data, manual techniques, and automatic calculations based on multiple signals of varying strengths with respect to the selected measurement signal.de_CH
dc.language.isoende_CH
dc.publisherMDPIde_CH
dc.relation.ispartofBioengineeringde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectGrowth rate estimationde_CH
dc.subjectKey performance indicatorde_CH
dc.subjectMammalian cell culturesde_CH
dc.subjectMicrobial cultivationde_CH
dc.subjectOnline-analyticsde_CH
dc.subjectOptrodede_CH
dc.subjectPlant suspension culturesde_CH
dc.subjectShake flaskde_CH
dc.subjectSpecific oxygen consumptionde_CH
dc.subjectStrain characterizationde_CH
dc.subject.ddc660.6: Biotechnologiede_CH
dc.titleImproved time resolved KPI and strain characterization of multiple hosts in shake flasks using advanced online analytics and data sciencede_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Chemie und Biotechnologie (ICBT)de_CH
dc.identifier.doi10.3390/bioengineering9080339de_CH
dc.identifier.doi10.21256/zhaw-25382-
dc.identifier.pmid35892752de_CH
zhaw.funding.euNot specifiedde_CH
zhaw.issue8de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start339de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume9de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.funding.zhawIntellishakerde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Life Sciences und Facility Management

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