Model-assisted process characterization and validation for a continuous two-column protein A capture process
Autor: | Sanchayita Ghose, Xuankuo Xu, Zheng Jian Li, James Angelo, Massimo Morbidelli, Thomas Müller-Späth, Daniel Baur, Srinivas Chollangi |
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Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
Risk analysis Biological Products Mathematical optimization Computer science 010401 analytical chemistry Process (computing) Bioengineering Characterization (mathematics) Process validation 01 natural sciences Applied Microbiology and Biotechnology Column (database) Chromatography Affinity 0104 chemical sciences Food and drug administration 03 medical and health sciences 030104 developmental biology Process description Technology Pharmaceutical Computer Simulation Staphylococcal Protein A Design space Biotechnology |
Zdroj: | Biotechnology and Bioengineering. 116:87-98 |
ISSN: | 0006-3592 |
DOI: | 10.1002/bit.26849 |
Popis: | In this study we introduce three process characterization approaches toward validation of continuous twin-column capture chromatography (CaptureSMB), referred to as "standard," "model assisted," and "hybrid." They are all based on a traditional risk-based approach, using process description, risk analysis, design-of-experiments (DoE), and statistical analysis as essential elements. The first approach, the "standard" approach uses a traditional experimental DoE to explore the design space of the high-ranked process parameters for the continuous process. Due to the larger number of process parameters in the continuous process, the DoE is extensive and includes a larger number of experiments than an equivalent DoE of a single column batch capture process. In the investigated case, many of the operating conditions were practically infeasible, indicating that the design space boundaries had been chosen inappropriately. To reduce experimental burden and at the same time enhance process understanding, an alternative "model assisted" approach was developed in parallel, employing a chromatographic process model to substitute experimental runs by computer simulations. Using the "model assisted" approach only experimental conditions that were feasible in terms of process yield constraints (>90%) were considered for statistical analysis. The "model assisted" approach included an optimization part that identified potential boundaries of the design space automatically. In summary, the "model assisted" approach contributed to increased process understanding compared to the "standard" approach. In this study, a "hybrid" approach was also used containing the general concepts of the "standard" approach but substituting a number of its experiments by computer simulations. The presented approaches contain essential elements of the Food and Drug Administration's process validation guideline. |
Databáze: | OpenAIRE |
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