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

Detalhes bibliográficos
Autor(a) principal: Santos, Tiago P. D.
Data de Publicação: 2023
Outros Autores: Fernandes, Rita P., Ribeiro, Rui P. P. L., Peixoto, Cristina, Mota, José P. B.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/154555
Resumo: PhD grant BD/06003/2020 (R.P. Fernandes). Publisher Copyright: © 2022 The Authors
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spelling Model-based design and optimization of GSSR chromatography for peptide purificationGSSR processInterior point methodMulticolumn chromatographyOptimization under uncertaintyProcess optimizationSolvent gradientEngineering (miscellaneous)Chemical Engineering (miscellaneous)PhD grant BD/06003/2020 (R.P. Fernandes). Publisher Copyright: © 2022 The AuthorsGradient 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.DQ - Departamento de QuímicaLAQV@REQUIMTERUNSantos, Tiago P. D.Fernandes, Rita P.Ribeiro, Rui P. P. L.Peixoto, CristinaMota, José P. B.2023-06-28T22:17:53Z2023-032023-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16application/pdfhttp://hdl.handle.net/10362/154555eng2772-5081PURE: 64723144https://doi.org/10.1016/j.dche.2022.100081info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:36:58Zoai:run.unl.pt:10362/154555Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:55:39.896567Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Model-based design and optimization of GSSR chromatography for peptide purification
title Model-based design and optimization of GSSR chromatography for peptide purification
spellingShingle Model-based design and optimization of GSSR chromatography for peptide purification
Santos, Tiago P. D.
GSSR process
Interior point method
Multicolumn chromatography
Optimization under uncertainty
Process optimization
Solvent gradient
Engineering (miscellaneous)
Chemical Engineering (miscellaneous)
title_short Model-based design and optimization of GSSR chromatography for peptide purification
title_full Model-based design and optimization of GSSR chromatography for peptide purification
title_fullStr Model-based design and optimization of GSSR chromatography for peptide purification
title_full_unstemmed Model-based design and optimization of GSSR chromatography for peptide purification
title_sort Model-based design and optimization of GSSR chromatography for peptide purification
author Santos, Tiago P. D.
author_facet Santos, Tiago P. D.
Fernandes, Rita P.
Ribeiro, Rui P. P. L.
Peixoto, Cristina
Mota, José P. B.
author_role author
author2 Fernandes, Rita P.
Ribeiro, Rui P. P. L.
Peixoto, Cristina
Mota, José P. B.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv DQ - Departamento de Química
LAQV@REQUIMTE
RUN
dc.contributor.author.fl_str_mv Santos, Tiago P. D.
Fernandes, Rita P.
Ribeiro, Rui P. P. L.
Peixoto, Cristina
Mota, José P. B.
dc.subject.por.fl_str_mv GSSR process
Interior point method
Multicolumn chromatography
Optimization under uncertainty
Process optimization
Solvent gradient
Engineering (miscellaneous)
Chemical Engineering (miscellaneous)
topic GSSR process
Interior point method
Multicolumn chromatography
Optimization under uncertainty
Process optimization
Solvent gradient
Engineering (miscellaneous)
Chemical Engineering (miscellaneous)
description PhD grant BD/06003/2020 (R.P. Fernandes). Publisher Copyright: © 2022 The Authors
publishDate 2023
dc.date.none.fl_str_mv 2023-06-28T22:17:53Z
2023-03
2023-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/154555
url http://hdl.handle.net/10362/154555
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2772-5081
PURE: 64723144
https://doi.org/10.1016/j.dche.2022.100081
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16
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