Model-based optimization of a preparative ion-exchange step for antibody purification

Karlsson, David; Jakobsson, Niklas; Axelsson, Anders; Nilsson, Bernt

doi:10.1016/j.chroma.2004.08.151

Cited by 69 publications

(47 citation statements)

References 20 publications

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“…A chromatogram with experimental data and simulation of the purification process is shown in Fig. 1 [14]. The first breakthrough (A) is myoglobin and B is IgG.…”

Section: Purification Processmentioning

confidence: 99%

“…A commonly used model is the general rate model [14]. This describes the changes in concentration over time in the chromatography column with respect to dispersion, convective flow, diffusion into the particles and adsorption to the particles.…”

Section: Chromatographic Modelingmentioning

confidence: 99%

“…The studied process is the purification of Immunoglobulin G (IgG) from myoglobin and bovine serum albumin (BSA) on an ion exchange chromatography column [13,14]. The column is a Resource 15Q column (GE Healthcare).…”

Section: Purification Processmentioning

confidence: 99%

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Designing Robust Preparative Purification Processes with High Performance

2008

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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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“…A chromatogram with experimental data and simulation of the purification process is shown in Fig. 1 [14]. The first breakthrough (A) is myoglobin and B is IgG.…”

Section: Purification Processmentioning

confidence: 99%

Section: Chromatographic Modelingmentioning

confidence: 99%

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Designing Robust Preparative Purification Processes with High Performance

2008

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“…The drug molecules are getting more complex and requiring more experiments to characterize their properties. With the automated platform, a much larger design space could be explored to discover much better solutions, which leads to the increase of the experiments (Karlsson et al 2004). The automated platform can deal with the substantial increase in the experiments well via parallel or high throughput experimentation at micro scale.…”

Section: Discussionmentioning

confidence: 99%

Intelligent Automation Platform for Bioprocess Development

Zhou

2012

Computer Aided Chemical Engineering

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“…Predicting the performance of the process by mathematical modeling and computer simulation minimizes the amount of experiments required. For this reason, simulation of chromatographic processes is becoming a valuable tool [3].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Frontal Protein Affinity Chromatography Using MATLAB

Guerrero-Germán

Montesinos-Cisneros²,

Tejeda-Mansir³

2012

J Chem Eng Process Technol

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In this study a transport model that includes axial dispersion in the bulk liquid, pore diffusion, external film resistance and finite kinetic rate, was used to mathematically describe a frontal affinity chromatography system. The corresponding differential equations system was solved in a simple and accurate form by using the numerical method of lines implemented in MATLAB. The solution was compared with experimental data from literature and the analytic Thomas solution. The frontal affinity chromatography of lysozyme to Cibacron Blue Sepharose was used as a model system. A good fit to the experimental data was obtained with the simulated runs of the transport model using this methodology. This approach was used to perform a parametric analysis of the experimental frontal affinity system. The solution of the transport model results in simple way to predict frontal affinity performance as well a better understanding of the fundamental mechanisms responsible for the separation.

show abstract

Model-based optimization of a preparative ion-exchange step for antibody purification

Cited by 69 publications

References 20 publications

Designing Robust Preparative Purification Processes with High Performance

Designing Robust Preparative Purification Processes with High Performance

Intelligent Automation Platform for Bioprocess Development

Simulation of Frontal Protein Affinity Chromatography Using MATLAB

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