Comparison of UV- and Raman-based monitoring of the Protein A load phase and evaluation of data fusion by PLS models and CNNs.
Raman spectroscopy
UV spectroscopy
data fusion
partial-least-squares regression
process analytical technology
Journal
Biotechnology and bioengineering
ISSN: 1097-0290
Titre abrégé: Biotechnol Bioeng
Pays: United States
ID NLM: 7502021
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
revised:
16
06
2021
received:
21
04
2021
accepted:
09
07
2021
pubmed:
24
7
2021
medline:
4
3
2022
entrez:
23
7
2021
Statut:
ppublish
Résumé
A promising application of Process Analytical Technology to the downstream process of monoclonal antibodies (mAbs) is the monitoring of the Protein A load phase as its control promises economic benefits. Different spectroscopic techniques have been evaluated in literature with regard to the ability to quantify the mAb concentration in the column effluent. Raman and Ultraviolet (UV) spectroscopy are among the most promising techniques. In this study, both were investigated in an in-line setup and directly compared. The data of each sensor were analyzed independently with Partial-Least-Squares (PLS) models and Convolutional Neural Networks (CNNs) for regression. Furthermore, data fusion strategies were investigated by combining both sensors in hierarchical PLS models or in CNNs. Among the tested options, UV spectroscopy alone allowed for the most precise and accurate prediction of the mAb concentration. A Root Mean Square Error of Prediction (RMSEP) of 0.013 g L
Substances chimiques
Staphylococcal Protein A
0
Types de publication
Comparative Study
Evaluation Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4255-4268Informations de copyright
© 2021 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals LLC.
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