Parameter-by-parameter method for steric mass action model of ion exchange chromatography: Theoretical considerations and experimental verification.

Ion-exchange chromatography Mechanistic model Parameter estimation Steric mass action model

Journal

Journal of chromatography. A
ISSN: 1873-3778
Titre abrégé: J Chromatogr A
Pays: Netherlands
ID NLM: 9318488

Informations de publication

Date de publication:
13 Sep 2022
Historique:
received: 07 06 2022
revised: 08 08 2022
accepted: 10 08 2022
pubmed: 25 8 2022
medline: 14 9 2022
entrez: 24 8 2022
Statut: ppublish

Résumé

Ion exchange chromatography (IEC) is one of the most widely-used techniques for protein separation and has been characterized by mechanistic models. However, the time-consuming and cumbersome model calibration hinders the application of mechanistic models for process development. A new methodology called "parameter-by-parameter method (PbP)" was proposed with mechanistic derivations of the steric mass action (SMA) model of IEC. The protocol includes four steps: (1) first linear regression (LR1) for characteristic charge; (2) second linear regression (LR2) for equilibrium coefficient; (3) linear approximation (LA) for shielding factor; (4) inverse method (IM) for kinetic coefficient. Four SMA parameters could be one-by-one determined in sequence, reducing the number of unknown parameters per species from four to one, and predicting almost consistent retention. Numerical single-component experiments were investigated firstly, and the PbP method showed excellent agreement between experiments and simulations. The effects of loadings on the PbP and Yamamoto methods were compared. It was found that the PbP method had higher accuracy and robustness than the Yamamoto method. Moreover, a five-experiment strategy was suggested to implement the PbP method, which is straightforward to reduce the cost of calibration experiments. Finally, a real-world multi-component separation was challenged and further confirmed the feasibility of the PbP method. In general, the proposed method can not only reliably estimate the SMA parameters with comprehensive physical understanding but also accurately predict retention over a wide range of loading conditions.

Identifiants

pubmed: 36001908
pii: S0021-9673(22)00610-0
doi: 10.1016/j.chroma.2022.463418
pii:
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

463418

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yu-Cheng Chen (YC)

Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.

Shan-Jing Yao (SJ)

Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.

Dong-Qiang Lin (DQ)

Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China. Electronic address: lindq@zju.edu.cn.

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Classifications MeSH