Improved process analytical technology for protein a chromatography using predictive principal component analysis tools
| Autor: | Ying Hou, Canping Jiang, Steven M. Cramer, Abhinav A. Shukla |
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| Rok vydání: | 2010 |
| Předmět: |
Principal Component Analysis
Chromatography Computer science Process analytical technology Bioengineering Applied Microbiology and Biotechnology Column (database) Antibodies Chromatography Affinity Recombinant Proteins Quality by Design Food and drug administration Principal component analysis Staphylococcal Protein A Chromatographic column Protein Binding Biotechnology |
| Zdroj: | Biotechnology and Bioengineering. 108:59-68 |
| ISSN: | 0006-3592 |
| Popis: | Protein A chromatography is widely employed for the capture and purification of antibodies and Fc-fusion proteins. Due to the high cost of protein A resins, there is a significant economic driving force for using these chromatographic materials for a large number of cycles. The maintenance of column performance over the resin lifetime is also a significant concern in large-scale manufacturing. In this work, several statistical methods are employed to develop a novel principal component analysis (PCA)-based tool for predicting protein A chromatographic column performance over time. A method is developed to carry out detection of column integrity failures before their occurrence without the need for a separate integrity test. In addition, analysis of various transitions in the chromatograms was also employed to develop PCA-based models to predict both subtle and general trends in real-time protein A column yield decay. The developed approach has significant potential for facilitating timely and improved decisions in large-scale chromatographic operations in line with the process analytical technology (PAT) guidance from the Food and Drug Administration (FDA). |
| Databáze: | OpenAIRE |
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