Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better
Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scal...
Gespeichert in:
Veröffentlicht in: | Biotechnology progress 2015-09, Vol.31 (5), p.1370-1380 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1380 |
---|---|
container_issue | 5 |
container_start_page | 1370 |
container_title | Biotechnology progress |
container_volume | 31 |
creator | Ahuja, Sanjeev Jain, Shilpa Ram, Kripa |
description | Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scale model should be predictive of large scale. Typically, small‐scale bioreactors, which are considered superior to shake flasks in simulating large‐scale bioreactors, are used as the scale‐down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one‐sided pH control and their satellites (small‐scale runs conducted using the same post‐inoculation cultures and nutrient feeds) in 3‐L bioreactors and shake flasks indicated that shake flasks mimicked the large‐scale performance better than 3‐L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3‐L scale‐down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000‐L and shake flask runs, and differences between 15,000‐L and 3‐L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3‐L scale. By reducing the initial sparge rate in 3‐L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1370–1380, 2015 |
doi_str_mv | 10.1002/btpr.2134 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1732822817</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1727989097</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3764-dbdc1daca8a0b9026df8aa3e837289cab1313b90e4a8092b0db1decb3caa5daa3</originalsourceid><addsrcrecordid>eNqFkd2KFDEQhYMo7rh64QtIwBsFezc_093py3XRGWFQkVXBm1CdVLPZSf-YZBznkXxLM864oCBeVUF951CcQ8hjzs44Y-K8TVM4E1zO75AZLwUrKiblXTJTdVkVdSPVCXkQ4w1jTLFK3CcnomJNLaSYkR8X0-SdgeTGgY4d7Tc-uW8QHCSkMIDfRRfzYmkPMdIUYIgdBjoFNxg3eYy0GwMN2LkBexzS3gSoLFa0dWNAMCmfowGPhR23A-1Hi77YXuNA4zWskXYe4jrS3vXOUF6-yF_-IY60xZQwPCT3OvARHx3nKfn4-tXV5bJYvVu8ubxYFUbW1bywrTXcggEFrG2YqGynACQqWQvVGGi55DIfcA6KNaJltuUWTSsNQGkzeUqeHXynMH7dYEy6d9Gg9zDguIma11IoIVSe_0dF3agmZ53Rp3-hN-Mm5Hx_UVWdiylVpp4fKBPGGHOoOufcQ9hpzvS-ar2vWu-rzuyTo-Om7dHekr-7zcD5Adg6j7t_O-mXV-8_HC2Lg8LFhN9vFRDWuqplXerPbxe6nC-WX5afuF7Jn_OYxQY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1726780658</pqid></control><display><type>article</type><title>Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better</title><source>MEDLINE</source><source>Access via Wiley Online Library</source><creator>Ahuja, Sanjeev ; Jain, Shilpa ; Ram, Kripa</creator><creatorcontrib>Ahuja, Sanjeev ; Jain, Shilpa ; Ram, Kripa</creatorcontrib><description>Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scale model should be predictive of large scale. Typically, small‐scale bioreactors, which are considered superior to shake flasks in simulating large‐scale bioreactors, are used as the scale‐down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one‐sided pH control and their satellites (small‐scale runs conducted using the same post‐inoculation cultures and nutrient feeds) in 3‐L bioreactors and shake flasks indicated that shake flasks mimicked the large‐scale performance better than 3‐L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3‐L scale‐down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000‐L and shake flask runs, and differences between 15,000‐L and 3‐L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3‐L scale. By reducing the initial sparge rate in 3‐L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1370–1380, 2015</description><identifier>ISSN: 8756-7938</identifier><identifier>EISSN: 1520-6033</identifier><identifier>DOI: 10.1002/btpr.2134</identifier><identifier>PMID: 26097232</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Animals ; Bioreactors ; Cell Culture Techniques ; CHO Cells ; Cricetinae ; Cricetulus ; Hydrogen-Ion Concentration ; Least-Squares Analysis ; Linear Models ; mass transfer ; Models, Theoretical ; Multivariate Analysis ; OPLS-DA ; outlier analysis ; Pilot Projects ; Principal Component Analysis ; scale-down model</subject><ispartof>Biotechnology progress, 2015-09, Vol.31 (5), p.1370-1380</ispartof><rights>2015 American Institute of Chemical Engineers</rights><rights>2015 American Institute of Chemical Engineers.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3764-dbdc1daca8a0b9026df8aa3e837289cab1313b90e4a8092b0db1decb3caa5daa3</citedby><cites>FETCH-LOGICAL-c3764-dbdc1daca8a0b9026df8aa3e837289cab1313b90e4a8092b0db1decb3caa5daa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fbtpr.2134$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fbtpr.2134$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26097232$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ahuja, Sanjeev</creatorcontrib><creatorcontrib>Jain, Shilpa</creatorcontrib><creatorcontrib>Ram, Kripa</creatorcontrib><title>Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better</title><title>Biotechnology progress</title><addtitle>Biotechnol Progress</addtitle><description>Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scale model should be predictive of large scale. Typically, small‐scale bioreactors, which are considered superior to shake flasks in simulating large‐scale bioreactors, are used as the scale‐down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one‐sided pH control and their satellites (small‐scale runs conducted using the same post‐inoculation cultures and nutrient feeds) in 3‐L bioreactors and shake flasks indicated that shake flasks mimicked the large‐scale performance better than 3‐L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3‐L scale‐down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000‐L and shake flask runs, and differences between 15,000‐L and 3‐L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3‐L scale. By reducing the initial sparge rate in 3‐L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1370–1380, 2015</description><subject>Animals</subject><subject>Bioreactors</subject><subject>Cell Culture Techniques</subject><subject>CHO Cells</subject><subject>Cricetinae</subject><subject>Cricetulus</subject><subject>Hydrogen-Ion Concentration</subject><subject>Least-Squares Analysis</subject><subject>Linear Models</subject><subject>mass transfer</subject><subject>Models, Theoretical</subject><subject>Multivariate Analysis</subject><subject>OPLS-DA</subject><subject>outlier analysis</subject><subject>Pilot Projects</subject><subject>Principal Component Analysis</subject><subject>scale-down model</subject><issn>8756-7938</issn><issn>1520-6033</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkd2KFDEQhYMo7rh64QtIwBsFezc_093py3XRGWFQkVXBm1CdVLPZSf-YZBznkXxLM864oCBeVUF951CcQ8hjzs44Y-K8TVM4E1zO75AZLwUrKiblXTJTdVkVdSPVCXkQ4w1jTLFK3CcnomJNLaSYkR8X0-SdgeTGgY4d7Tc-uW8QHCSkMIDfRRfzYmkPMdIUYIgdBjoFNxg3eYy0GwMN2LkBexzS3gSoLFa0dWNAMCmfowGPhR23A-1Hi77YXuNA4zWskXYe4jrS3vXOUF6-yF_-IY60xZQwPCT3OvARHx3nKfn4-tXV5bJYvVu8ubxYFUbW1bywrTXcggEFrG2YqGynACQqWQvVGGi55DIfcA6KNaJltuUWTSsNQGkzeUqeHXynMH7dYEy6d9Gg9zDguIma11IoIVSe_0dF3agmZ53Rp3-hN-Mm5Hx_UVWdiylVpp4fKBPGGHOoOufcQ9hpzvS-ar2vWu-rzuyTo-Om7dHekr-7zcD5Adg6j7t_O-mXV-8_HC2Lg8LFhN9vFRDWuqplXerPbxe6nC-WX5afuF7Jn_OYxQY</recordid><startdate>201509</startdate><enddate>201509</enddate><creator>Ahuja, Sanjeev</creator><creator>Jain, Shilpa</creator><creator>Ram, Kripa</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201509</creationdate><title>Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better</title><author>Ahuja, Sanjeev ; Jain, Shilpa ; Ram, Kripa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3764-dbdc1daca8a0b9026df8aa3e837289cab1313b90e4a8092b0db1decb3caa5daa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Animals</topic><topic>Bioreactors</topic><topic>Cell Culture Techniques</topic><topic>CHO Cells</topic><topic>Cricetinae</topic><topic>Cricetulus</topic><topic>Hydrogen-Ion Concentration</topic><topic>Least-Squares Analysis</topic><topic>Linear Models</topic><topic>mass transfer</topic><topic>Models, Theoretical</topic><topic>Multivariate Analysis</topic><topic>OPLS-DA</topic><topic>outlier analysis</topic><topic>Pilot Projects</topic><topic>Principal Component Analysis</topic><topic>scale-down model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ahuja, Sanjeev</creatorcontrib><creatorcontrib>Jain, Shilpa</creatorcontrib><creatorcontrib>Ram, Kripa</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Biotechnology progress</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ahuja, Sanjeev</au><au>Jain, Shilpa</au><au>Ram, Kripa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better</atitle><jtitle>Biotechnology progress</jtitle><addtitle>Biotechnol Progress</addtitle><date>2015-09</date><risdate>2015</risdate><volume>31</volume><issue>5</issue><spage>1370</spage><epage>1380</epage><pages>1370-1380</pages><issn>8756-7938</issn><eissn>1520-6033</eissn><abstract>Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scale model should be predictive of large scale. Typically, small‐scale bioreactors, which are considered superior to shake flasks in simulating large‐scale bioreactors, are used as the scale‐down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one‐sided pH control and their satellites (small‐scale runs conducted using the same post‐inoculation cultures and nutrient feeds) in 3‐L bioreactors and shake flasks indicated that shake flasks mimicked the large‐scale performance better than 3‐L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3‐L scale‐down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000‐L and shake flask runs, and differences between 15,000‐L and 3‐L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3‐L scale. By reducing the initial sparge rate in 3‐L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1370–1380, 2015</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>26097232</pmid><doi>10.1002/btpr.2134</doi><tpages>11</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 8756-7938 |
ispartof | Biotechnology progress, 2015-09, Vol.31 (5), p.1370-1380 |
issn | 8756-7938 1520-6033 |
language | eng |
recordid | cdi_proquest_miscellaneous_1732822817 |
source | MEDLINE; Access via Wiley Online Library |
subjects | Animals Bioreactors Cell Culture Techniques CHO Cells Cricetinae Cricetulus Hydrogen-Ion Concentration Least-Squares Analysis Linear Models mass transfer Models, Theoretical Multivariate Analysis OPLS-DA outlier analysis Pilot Projects Principal Component Analysis scale-down model |
title | Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model-when shake flasks mimic 15,000-L bioreactors better |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T17%3A26%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Application%20of%20multivariate%20analysis%20and%20mass%20transfer%20principles%20for%20refinement%20of%20a%203-L%20bioreactor%20scale-down%20model-when%20shake%20flasks%20mimic%2015,000-L%20bioreactors%20better&rft.jtitle=Biotechnology%20progress&rft.au=Ahuja,%20Sanjeev&rft.date=2015-09&rft.volume=31&rft.issue=5&rft.spage=1370&rft.epage=1380&rft.pages=1370-1380&rft.issn=8756-7938&rft.eissn=1520-6033&rft_id=info:doi/10.1002/btpr.2134&rft_dat=%3Cproquest_cross%3E1727989097%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1726780658&rft_id=info:pmid/26097232&rfr_iscdi=true |