Standardized method for mechanistic modeling of multimodal anion exchange chromatography in flow through operation.

Analytical parameter determination Mixed-mode gradient elution Model calibration and validation Parameter uncertainty assessment Therapeutic antibody

Journal

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

Informations de publication

Date de publication:
08 Feb 2023
Historique:
received: 14 09 2022
revised: 14 12 2022
accepted: 08 01 2023
pubmed: 18 1 2023
medline: 4 2 2023
entrez: 17 1 2023
Statut: ppublish

Résumé

Multimodal chromatography offers an increased selectivity compared to unimodal chromatographic methods and is often employed for challenging separation tasks in industrial downstream processing (DSP). Unfortunately, the implementation of multimodal polishing into a generic downstream platform can be hampered by non-robust platform conditions leading to a time and cost intensive process development. Mechanistic modeling can assist experimental process development but readily applicable and easy to calibrate multimodal chromatography models are lacking. In this work, we present a mechanistic modeling aided approach that paves the way for an accelerated development of anionic mixed-mode chromatography (MMC) for biopharmaceutical purification. A modified multimodal isotherm model was calibrated using only three chromatographic experiments and was employed in the retention prediction of four antibody formats including a Fab, a bispecific, as well as an IgG1 and IgG4 antibody subtype at pH 5.0 and 6.0. The chromatographic experiments were conducted using the anionic mixed-mode resin Capto adhere at industrial relevant process conditions to enable flow through purification. An existing multimodal isotherm model was reduced to hydrophobic interactions in the linear range of the adsorption isotherm and successfully employed in the simulation of six chromatographic experiments per molecule in concert with the transport dispersive model (TDM). The model reduction to only three parameters did prevent structural parameter non-identifiability and enabled an analytical isotherm parameter determination that was further refined by incorporation of size exclusion effects of the selected multimodal resin. During the model calibration, three linear salt gradient elution experiments were performed for each molecule followed by an isotherm parameter uncertainty assessment. Lastly, each model was validated with a set of step and isocratic elution experiments. This standardized modeling approach facilitates the implementation of multimodal chromatography as a key unit operation for the biopharmaceutical downstream platform, while increasing the mechanistic insight to the multimodal adsorption behavior of complex biologics.

Identifiants

pubmed: 36649667
pii: S0021-9673(23)00017-1
doi: 10.1016/j.chroma.2023.463789
pii:
doi:

Substances chimiques

Sodium Chloride 451W47IQ8X
Antibodies, Monoclonal 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

463789

Informations de copyright

Copyright © 2023 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

Rudger Hess (R)

Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe, Germany; DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Doil Yun (D)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

David Saleh (D)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Till Briskot (T)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Jan-Hendrik Grosch (JH)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Gang Wang (G)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Thomas Schwab (T)

DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Jürgen Hubbuch (J)

Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe, Germany. Electronic address: juergen.hubbuch@kit.edu.

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Classifications MeSH