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Automatic procedure for modelling, calibration, and optimization of a three-component chromatographic separation

Espinoza, Daniel LU ; Tallvod, Simon LU ; Andersson, Niklas LU orcid and Nilsson, Bernt LU (2024) In Journal of Chromatography A 1720.
Abstract
The current landscape of biopharmaceutical production necessitates an ever-growing set of tools to meet the demands for shorter development times and lower production costs. One path towards meeting these demands is the implementation of digital tools in the development stages. Mathematical modelling of process chromatography, one of the key unit operations in the biopharmaceutical downstream process, is one such tool. However, obtaining parameter values for such models is a time-consuming task that grows in complexity with the number of compounds in the mixture being purified.

In this study, we tackle this issue by developing an automated model calibration procedure for purification of a multi-component mixture by linear gradient... (More)
The current landscape of biopharmaceutical production necessitates an ever-growing set of tools to meet the demands for shorter development times and lower production costs. One path towards meeting these demands is the implementation of digital tools in the development stages. Mathematical modelling of process chromatography, one of the key unit operations in the biopharmaceutical downstream process, is one such tool. However, obtaining parameter values for such models is a time-consuming task that grows in complexity with the number of compounds in the mixture being purified.

In this study, we tackle this issue by developing an automated model calibration procedure for purification of a multi-component mixture by linear gradient ion exchange chromatography. The procedure was implemented using the Orbit software (Lund University, Department of Chemical Engineering), which both generates a mathematical model structure and performs the experiments necessary to obtain data for model calibration. The procedure was extended to suggest operating points for the purification of one of the components in the mixture by means of multi-objective optimization using three different objectives. The procedure was tested on a three-component protein mixture and was able to generate a calibrated model capable of reproducing the experimental chromatograms to a satisfactory degree, using a total of six assays. An additional seventh experiment was performed to validate the model response under one of the suggested optimum conditions, respecting a 95 % purity requirement. All of the above was automated and set in motion by the push of a button. With these results, we have taken a step towards fully automating model calibration and thus accelerating digitalization in the development stages of new biopharmaceuticals. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Chromatography A
volume
1720
article number
464805
pages
11 pages
publisher
Elsevier
external identifiers
  • pmid:38471300
  • scopus:85187207918
ISSN
0021-9673
DOI
10.1016/j.chroma.2024.464805
language
English
LU publication?
yes
id
0b7658ab-5dad-4c45-b798-a5071c473a9e
date added to LUP
2024-03-14 20:53:05
date last changed
2024-03-19 13:27:41
@article{0b7658ab-5dad-4c45-b798-a5071c473a9e,
  abstract     = {{The current landscape of biopharmaceutical production necessitates an ever-growing set of tools to meet the demands for shorter development times and lower production costs. One path towards meeting these demands is the implementation of digital tools in the development stages. Mathematical modelling of process chromatography, one of the key unit operations in the biopharmaceutical downstream process, is one such tool. However, obtaining parameter values for such models is a time-consuming task that grows in complexity with the number of compounds in the mixture being purified.<br/><br/>In this study, we tackle this issue by developing an automated model calibration procedure for purification of a multi-component mixture by linear gradient ion exchange chromatography. The procedure was implemented using the Orbit software (Lund University, Department of Chemical Engineering), which both generates a mathematical model structure and performs the experiments necessary to obtain data for model calibration. The procedure was extended to suggest operating points for the purification of one of the components in the mixture by means of multi-objective optimization using three different objectives. The procedure was tested on a three-component protein mixture and was able to generate a calibrated model capable of reproducing the experimental chromatograms to a satisfactory degree, using a total of six assays. An additional seventh experiment was performed to validate the model response under one of the suggested optimum conditions, respecting a 95 % purity requirement. All of the above was automated and set in motion by the push of a button. With these results, we have taken a step towards fully automating model calibration and thus accelerating digitalization in the development stages of new biopharmaceuticals.}},
  author       = {{Espinoza, Daniel and Tallvod, Simon and Andersson, Niklas and Nilsson, Bernt}},
  issn         = {{0021-9673}},
  language     = {{eng}},
  month        = {{04}},
  publisher    = {{Elsevier}},
  series       = {{Journal of Chromatography A}},
  title        = {{Automatic procedure for modelling, calibration, and optimization of a three-component chromatographic separation}},
  url          = {{http://dx.doi.org/10.1016/j.chroma.2024.464805}},
  doi          = {{10.1016/j.chroma.2024.464805}},
  volume       = {{1720}},
  year         = {{2024}},
}