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In Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production

2015-06Journal article Restricted access
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dc.contributor.authorSales, Kevin C.
dc.contributor.authorRosa, Filipa
dc.contributor.authorSampaio, Pedro N.
dc.contributor.authorFonseca, LuÍs P.
dc.contributor.authorB. Lopes, Marta
dc.contributor.authorCalado, Cecília
dc.date.accessioned2016-04-20T11:22:20Z
dc.date.available2016-04-20T11:22:20Z
dc.date.issued2015-06
dc.description.abstractThe development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coil cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R-2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.pt_PT
dc.identifier.citationSALES, Kevin C.; [et al.] - In Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production. Applied Spectroscopy. ISSN.0003-7028. Vol. 69, N.º 6 (2015), pp. 760-772pt_PT
dc.identifier.doi10.1366/14-07588pt_PT
dc.identifier.issn0003-7028
dc.identifier.issn1943-3530
dc.identifier.urihttp://hdl.handle.net/10400.21/6057
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSOC APPLIED SPECTROSCOPYpt_PT
dc.relation.publisherversionhttp://asp.sagepub.com/content/69/6/760pt_PT
dc.subjectBiopharmaceuticalspt_PT
dc.subjectBioprocess monitoringpt_PT
dc.subjectMid-infrared spectroscopypt_PT
dc.subjectNear-infrared spectroscopypt_PT
dc.subjectPartial least squares modelspt_PT
dc.subjectPLS: Process analytical technologiespt_PT
dc.subjectPATpt_PT
dc.titleIn Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Productionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FBIO%2F69242%2F2006/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBPD%2F73758%2F2010/PT
oaire.citation.endPage772pt_PT
oaire.citation.issue6pt_PT
oaire.citation.startPage760pt_PT
oaire.citation.volume69pt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStreamSFRH
person.familyNameB. Lopes
person.familyNameCalado
person.givenNameMarta
person.givenNameCecília
person.identifier1195979
person.identifier130332
person.identifier.ciencia-idFD16-A07F-7B12
person.identifier.ciencia-id9418-E320-3177
person.identifier.orcid0000-0002-4135-1857
person.identifier.orcid0000-0002-5264-9755
person.identifier.ridF-5378-2011
person.identifier.ridE-2102-2014
person.identifier.scopus-author-id55489480400
person.identifier.scopus-author-id6603163260
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication183b936b-4a1d-4c80-9405-17491abb3d64
relation.isAuthorOfPublicatione8577257-c64c-4481-9b2b-940fedb360cc
relation.isAuthorOfPublication.latestForDiscovery183b936b-4a1d-4c80-9405-17491abb3d64
relation.isProjectOfPublicatione934d4a3-07d0-4c5d-8183-e76b3b0bf237
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