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Determination of robustness and optimal work conditions for a purification process of a therapeutic recombinant protein using response surface methodology
Author(s) -
Amadeo Ignacio,
Mauro Laura V.,
Ortí Eduardo,
Forno Guillermina
Publication year - 2011
Publication title -
biotechnology progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 129
eISSN - 1520-6033
pISSN - 8756-7938
DOI - 10.1002/btpr.588
Subject(s) - robustness (evolution) , quality by design , bioprocess , response surface methodology , biopharmaceutical , biochemical engineering , computer science , design of experiments , process (computing) , process engineering , new product development , chemistry , microbiology and biotechnology , mathematics , engineering , machine learning , biology , statistics , biochemistry , marketing , chemical engineering , business , gene , operating system
A typical chromatographic purification step has numerous operating parameters that can impact its performance. As it is not feasible to evaluate the influence of each one, the current practice in biopharmaceutical industry is to apply risk analysis approach to identify process parameters that should be examined during process characterization. Once these parameters are identified, a response surface study can be run to help understand the relationship between critical inputs and outputs. We performed a study comprising optimization and robustness determination for a Blue‐Sepharose purification step of rhEPO, a well‐known therapeutic glycoprotein. Initially, risk analysis was fulfilled to identify key parameters. A small‐scale model was created and qualified before its use in experimental studies, given by a Box–Behnken design with three factors. This method proved to be a very useful tool in bioprocess validation studies in which many input variables can affect product quality and safety. © 2011 American Institute of Chemical Engineers Biotechnol. Prog., 2011