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1.	Degerman, Marcus, et al. (author) Designing robust preparative purification processes with high performance 2008 In: Chemical Engineering & Technology. - : Wiley. - 1521-4125 .- 0930-7516. ; 31:6, s. 875-882 Journal article (peer-reviewed)abstract In the production of pharmaceutical drugs, a large part of the production costs stem from the downstream processing and the chromatographic purifications required. In order to reduce purification costs the process performance must be increased, which means that the processes need to be less robust since robustness comes with the price of lower process performance, and thus, higher production costs. It is difficult to find a good estimate of the robustness of a process experimentally, and therefore, the pharmaceutical industry has been forced to design processes to be very robust. This work presents a model-based method for optimizing purification processes both with regard to performance and robustness. A model of chromatographic processes and methods of calibration are presented. The model is then used to determine the operating conditions with highest performance when robustness is not taken into account. With this as a starting point, the process is then optimized for higher robustness and lower probability of batch failure. The purification of Immunoglobulin G through ion exchange chromatography is used to demonstrate the method.

Degerman, Marcus, et al. (author)
Designing robust preparative purification processes with high performance
2008
In: Chemical Engineering & Technology. - : Wiley. - 1521-4125 .- 0930-7516. ; 31:6, s. 875-882
Journal article (peer-reviewed)abstract
- In the production of pharmaceutical drugs, a large part of the production costs stem from the downstream processing and the chromatographic purifications required. In order to reduce purification costs the process performance must be increased, which means that the processes need to be less robust since robustness comes with the price of lower process performance, and thus, higher production costs. It is difficult to find a good estimate of the robustness of a process experimentally, and therefore, the pharmaceutical industry has been forced to design processes to be very robust. This work presents a model-based method for optimizing purification processes both with regard to performance and robustness. A model of chromatographic processes and methods of calibration are presented. The model is then used to determine the operating conditions with highest performance when robustness is not taken into account. With this as a starting point, the process is then optimized for higher robustness and lower probability of batch failure. The purification of Immunoglobulin G through ion exchange chromatography is used to demonstrate the method.

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