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A Model-Based Approach to Determine the Design Space of Preparative Chromatography

Degerman, Marcus LU ; Westerberg, Karin LU and Nilsson, Bernt LU (2009) In Chemical Engineering & Technology 32(8). p.1195-1202
Abstract
A dream of many pharmaceutical companies is to be able to register a large design space with the regulatory agencies. The problem is that this will require both time and money, so an intelligent method of validating a design space is needed. The design space should only cover operating points at which the process runs optimally. This means that the process should be optimized for different process scenarios and objective functions and the found operating points should be registered as design space. This paper presents a method of determining a good design space by creating Pareto fronts for the ideal case and for various process disturbance scenarios. Optimal operating points are found for varying ratios between feed costs and operating... (More)
A dream of many pharmaceutical companies is to be able to register a large design space with the regulatory agencies. The problem is that this will require both time and money, so an intelligent method of validating a design space is needed. The design space should only cover operating points at which the process runs optimally. This means that the process should be optimized for different process scenarios and objective functions and the found operating points should be registered as design space. This paper presents a method of determining a good design space by creating Pareto fronts for the ideal case and for various process disturbance scenarios. Optimal operating points are found for varying ratios between feed costs and operating costs, making it possible to make a quantitative choice of an operating point based on this ratio and a qualitative choice based on the whole front. The analysis will show how the chromatographic process can be made more robust when optimizing for higher yields, and how the effect of the critical process parameters can change. To be certain that a robust process is found and that it has a high performance, process disturbances must be taken into account when optimizing a process. (Less)
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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Uncertainty analysis, Sensitivity analysis, Preparative chromatography, Optimization, Design space, Modeling
in
Chemical Engineering & Technology
volume
32
issue
8
pages
1195 - 1202
publisher
John Wiley & Sons Inc.
external identifiers
  • wos:000269231700007
  • scopus:69649094493
ISSN
1521-4125
DOI
10.1002/ceat.200900102
language
English
LU publication?
yes
id
562d17e4-267c-4a59-8176-32e55bc87087 (old id 1476735)
date added to LUP
2016-04-01 11:56:19
date last changed
2023-10-13 15:48:23
@article{562d17e4-267c-4a59-8176-32e55bc87087,
  abstract     = {{A dream of many pharmaceutical companies is to be able to register a large design space with the regulatory agencies. The problem is that this will require both time and money, so an intelligent method of validating a design space is needed. The design space should only cover operating points at which the process runs optimally. This means that the process should be optimized for different process scenarios and objective functions and the found operating points should be registered as design space. This paper presents a method of determining a good design space by creating Pareto fronts for the ideal case and for various process disturbance scenarios. Optimal operating points are found for varying ratios between feed costs and operating costs, making it possible to make a quantitative choice of an operating point based on this ratio and a qualitative choice based on the whole front. The analysis will show how the chromatographic process can be made more robust when optimizing for higher yields, and how the effect of the critical process parameters can change. To be certain that a robust process is found and that it has a high performance, process disturbances must be taken into account when optimizing a process.}},
  author       = {{Degerman, Marcus and Westerberg, Karin and Nilsson, Bernt}},
  issn         = {{1521-4125}},
  keywords     = {{Uncertainty analysis; Sensitivity analysis; Preparative chromatography; Optimization; Design space; Modeling}},
  language     = {{eng}},
  number       = {{8}},
  pages        = {{1195--1202}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Chemical Engineering & Technology}},
  title        = {{A Model-Based Approach to Determine the Design Space of Preparative Chromatography}},
  url          = {{http://dx.doi.org/10.1002/ceat.200900102}},
  doi          = {{10.1002/ceat.200900102}},
  volume       = {{32}},
  year         = {{2009}},
}