Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/155422 |
Resumo: | JP acknowledges the PhD grant SFRD/BD14610472019, Fundação para a Ciência e Tecnologia (FCT). |
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Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reductionhybrid modelingdeep learningADAM methodPichia pastoris GS115 Mut+single-chain antibody fragment (scFv)bioprocess digitalizationFood ScienceBiochemistry, Genetics and Molecular Biology (miscellaneous)Plant ScienceJP acknowledges the PhD grant SFRD/BD14610472019, Fundação para a Ciência e Tecnologia (FCT).Hybrid modeling workflows combining machine learning with mechanistic process descriptions are becoming essential tools for bioprocess digitalization. In this study, a hybrid deep modeling method with state–space reduction was developed and showcased with a P. pastoris GS115 Mut+ strain expressing a single-chain antibody fragment (scFv). Deep feedforward neural networks (FFNN) with varying depths were connected in series with bioreactor macroscopic material balance equations. The hybrid model structure was trained with a deep learning technique based on the adaptive moment estimation method (ADAM), semidirect sensitivity equations and stochastic regularization. A state–space reduction method was investigated based on a principal component analysis (PCA) of the cumulative reacted amount. Data of nine fed-batch P. pastoris 50 L cultivations served to validate the method. Hybrid deep models were developed describing process dynamics as a function of critical process parameters (CPPs). The state–space reduction method succeeded to decrease the hybrid model complexity by 60% and to improve the predictive power by 18.5% in relation to the nonreduced version. An exploratory design space analysis showed that the optimization of the feed of methanol and of inorganic elements has the potential to increase the scFv endpoint titer by 30% and 80%, respectively, in relation to the reference condition.LAQV@REQUIMTEDQ - Departamento de QuímicaRUNPinto, JoséRamos, João R. C.Costa, Rafael S.Oliveira, Rui2023-07-17T22:16:17Z2023-07-082023-07-08T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article19application/pdfhttp://hdl.handle.net/10362/155422eng2311-5637PURE: 66016819https://doi.org/10.3390/fermentation9070643info: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:RCAAP2024-03-11T05:37:59Zoai:run.unl.pt:10362/155422Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:56:03.471585Repositório 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 |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
title |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
spellingShingle |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction Pinto, José hybrid modeling deep learning ADAM method Pichia pastoris GS115 Mut+ single-chain antibody fragment (scFv) bioprocess digitalization Food Science Biochemistry, Genetics and Molecular Biology (miscellaneous) Plant Science |
title_short |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
title_full |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
title_fullStr |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
title_full_unstemmed |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
title_sort |
Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction |
author |
Pinto, José |
author_facet |
Pinto, José Ramos, João R. C. Costa, Rafael S. Oliveira, Rui |
author_role |
author |
author2 |
Ramos, João R. C. Costa, Rafael S. Oliveira, Rui |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
LAQV@REQUIMTE DQ - Departamento de Química RUN |
dc.contributor.author.fl_str_mv |
Pinto, José Ramos, João R. C. Costa, Rafael S. Oliveira, Rui |
dc.subject.por.fl_str_mv |
hybrid modeling deep learning ADAM method Pichia pastoris GS115 Mut+ single-chain antibody fragment (scFv) bioprocess digitalization Food Science Biochemistry, Genetics and Molecular Biology (miscellaneous) Plant Science |
topic |
hybrid modeling deep learning ADAM method Pichia pastoris GS115 Mut+ single-chain antibody fragment (scFv) bioprocess digitalization Food Science Biochemistry, Genetics and Molecular Biology (miscellaneous) Plant Science |
description |
JP acknowledges the PhD grant SFRD/BD14610472019, Fundação para a Ciência e Tecnologia (FCT). |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-17T22:16:17Z 2023-07-08 2023-07-08T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/155422 |
url |
http://hdl.handle.net/10362/155422 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2311-5637 PURE: 66016819 https://doi.org/10.3390/fermentation9070643 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
19 application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799138146669035520 |