Effects of uncertainties in experimental conditions on the estimation of adsorption model parameters in preparative chromatography
Borg, Niklas LU ; Westerberg, Karin LU ; Andersson, Niklas LU
; von Lieres, Eric
and Nilsson, Bernt
LU
(2013)
In Computers & Chemical Engineering
55.
p.148-157
- Abstract
- Model-based process design is increasingly popular when designing pharmaceutical purification processes. The effect of uncertainties in concentration measurements on the estimation of model parameters is analyzed for two cases of non-isocratic adsorption chromatography. A model, calibrated to experiments, is used to generate data by adding a Monte Carlo sampled error in the inlet concentrations. New model parameters are estimated by minimizing the deviation between the synthetic data and the model. The first case is a separation of rare earth elements by ion-exchange chromatography and the second case is a purification of insulin from a product-related impurity by reversed-phase chromatography. It is shown that normally distributed errors... (More)
- Model-based process design is increasingly popular when designing pharmaceutical purification processes. The effect of uncertainties in concentration measurements on the estimation of model parameters is analyzed for two cases of non-isocratic adsorption chromatography. A model, calibrated to experiments, is used to generate data by adding a Monte Carlo sampled error in the inlet concentrations. New model parameters are estimated by minimizing the deviation between the synthetic data and the model. The first case is a separation of rare earth elements by ion-exchange chromatography and the second case is a purification of insulin from a product-related impurity by reversed-phase chromatography. It is shown that normally distributed errors in the concentrations result in deviations in the UV-signal that are not normally distributed. With the applied method, known concentration distributions can be translated into probability distributions of the model parameters, which can be taken into account in the model-based process design. (C) 2013 Elsevier Ltd. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3980006
- author
- Borg, Niklas
LU
; Westerberg, Karin
LU
; Andersson, Niklas
LU
; von Lieres, Eric
and Nilsson, Bernt
LU
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Modeling Ion-exchange chromatography, Reversed-phase chromatography, Model calibration, Parameter estimation, Parameter uncertainty
- in
- Computers & Chemical Engineering
- volume
- 55
- pages
- 148 - 157
- publisher
- Elsevier
- external identifiers
-
- wos:000320650300013
- scopus:84878469802
- ISSN
- 1873-4375
- DOI
- 10.1016/j.compchemeng.2013.04.013
- language
- English
- LU publication?
- yes
- id
- ef8e63f3-95a5-490a-a7a4-2c56de6c290c (old id 3980006)
- date added to LUP
- 2016-04-01 14:40:56
- date last changed
- 2023-11-13 10:57:15
@article{ef8e63f3-95a5-490a-a7a4-2c56de6c290c,
abstract = {{Model-based process design is increasingly popular when designing pharmaceutical purification processes. The effect of uncertainties in concentration measurements on the estimation of model parameters is analyzed for two cases of non-isocratic adsorption chromatography. A model, calibrated to experiments, is used to generate data by adding a Monte Carlo sampled error in the inlet concentrations. New model parameters are estimated by minimizing the deviation between the synthetic data and the model. The first case is a separation of rare earth elements by ion-exchange chromatography and the second case is a purification of insulin from a product-related impurity by reversed-phase chromatography. It is shown that normally distributed errors in the concentrations result in deviations in the UV-signal that are not normally distributed. With the applied method, known concentration distributions can be translated into probability distributions of the model parameters, which can be taken into account in the model-based process design. (C) 2013 Elsevier Ltd. All rights reserved.}},
author = {{Borg, Niklas and Westerberg, Karin and Andersson, Niklas and von Lieres, Eric and Nilsson, Bernt}},
issn = {{1873-4375}},
keywords = {{Modeling Ion-exchange chromatography; Reversed-phase chromatography; Model calibration; Parameter estimation; Parameter uncertainty}},
language = {{eng}},
pages = {{148--157}},
publisher = {{Elsevier}},
series = {{Computers & Chemical Engineering}},
title = {{Effects of uncertainties in experimental conditions on the estimation of adsorption model parameters in preparative chromatography}},
url = {{http://dx.doi.org/10.1016/j.compchemeng.2013.04.013}},
doi = {{10.1016/j.compchemeng.2013.04.013}},
volume = {{55}},
year = {{2013}},
}