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Model-based design and optimization of GSSR chromatography for peptide purification

2023-03Artigo científico Acesso aberto
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dc.contributor.authorSantos, Tiago P. D.
dc.contributor.authorFernandes, Rita P.
dc.contributor.authorRibeiro, Rui P. P. L.
dc.contributor.authorPeixoto, Cristina
dc.contributor.authorMota, José P. B.
dc.contributor.institutionDQ - Departamento de Química
dc.contributor.institutionLAQV@REQUIMTE
dc.contributor.pblElsevier
dc.date.accessioned2023-06-28T22:17:53Z
dc.date.available2023-06-28T22:17:53Z
dc.date.issued2023-03
dc.descriptionPhD grant BD/06003/2020 (R.P. Fernandes). Publisher Copyright: © 2022 The Authors
dc.description.abstractGradient with Steady State Recycle (GSSR) is a recently developed process for center-cut separation by solvent-gradient chromatography. The process comprises a multicolumn, open-loop system with cyclic steady-state operation that simulates a solvent gradient moving countercurrently with respect to the solid phase. However, the feed is always injected into the same column and the product always collected from the same column as in single-column batch chromatography. Here, three-column GSSR chromatography for peptide purification is optimized using state-of-the-art mathematical programming tools. The optimization problem is formulated using a full-discretization approach for steady periodic dynamics. The resulting nonlinear programming problem is solved by an efficient open-source interior-point solver coupled to a high-performance parallel linear solver for sparse symmetric indefinite matrices. The procedure is successfully employed to find optimal solutions for a series of process design problems with increasing number of decision variables. In addition to productivity and recovery, process performance is analyzed in terms of two key performance indicators: dilution ratio and solvent consumption ratio. Finally, the problem of robust process design under uncertainty in the solvent gradient manipulation is examined. The best solution is chosen only among candidate solutions that are robust feasible, i.e., remain feasible for all modifier gradient perturbations within the accuracy range of the gradient pump. This gives rise to a robust approach to optimal design in which the nominal problem is replaced by a worst case problem. Overall, our work illustrates the advantages of using advanced mathematical programming tools in designing and optimizing a GSSR process for which it is difficult to deduce sufficiently general heuristic design rules.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent16
dc.format.extent1116432
dc.identifier.doi10.1016/j.dche.2022.100081
dc.identifier.issn2772-5081
dc.identifier.otherPURE: 64723144
dc.identifier.otherPURE UUID: 1bf0f962-cbb4-4685-8114-236b276cdf12
dc.identifier.otherScopus: 85148978575
dc.identifier.urihttp://hdl.handle.net/10362/154555
dc.identifier.urlhttps://www.scopus.com/pages/publications/85148978575
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/OE/PD%2FBD%2F142951%2F2018/PT
dc.relationDebottlenecking the purification of complex biopharmaceuticals with new 3D-printed chromatographic processes, advanced analytics and computer-aided process design tools
dc.relationAssociated Laboratory for Green Chemistry - Clean Technologies and Processes
dc.relationAssociated Laboratory for Green Chemistry - Clean Technologies and Processes
dc.subjectGSSR process
dc.subjectInterior point method
dc.subjectMulticolumn chromatography
dc.subjectOptimization under uncertainty
dc.subjectProcess optimization
dc.subjectSolvent gradient
dc.subjectEngineering (miscellaneous)
dc.subjectChemical Engineering (miscellaneous)
dc.titleModel-based design and optimization of GSSR chromatography for peptide purificationen
dc.typejournal article
degois.publication.titleDigital Chemical Engineering
degois.publication.volume6
dspace.entity.typePublication
oaire.awardNumberPD/BD/142951/2018
oaire.awardNumberUIDB/50006/2020
oaire.awardNumberUIDP/50006/2020
oaire.awardTitleDebottlenecking the purification of complex biopharmaceuticals with new 3D-printed chromatographic processes, advanced analytics and computer-aided process design tools
oaire.awardTitleAssociated Laboratory for Green Chemistry - Clean Technologies and Processes
oaire.awardTitleAssociated Laboratory for Green Chemistry - Clean Technologies and Processes
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/OE/PD%2FBD%2F142951%2F2018/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50006%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50006%2F2020/PT
oaire.fundingStreamOE
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
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
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublicationb4370ff1-8c61-4228-81ad-74ca89f701ba
relation.isProjectOfPublicationadc84c24-ba1d-4bcd-b753-2128ce9a5faa
relation.isProjectOfPublication4d9a4d40-4803-4f3a-976b-d6eaaef42510
relation.isProjectOfPublication.latestForDiscoveryb4370ff1-8c61-4228-81ad-74ca89f701ba

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