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Using partition designs to enhance purification process understanding
Author(s) -
Pieracci John,
Perry Leonard,
Conley Lynn
Publication year - 2010
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.22866
Subject(s) - partition (number theory) , computer science , process (computing) , process design , quality by design , limit (mathematics) , biochemical engineering , process engineering , new product development , mathematics , engineering , process integration , mathematical analysis , combinatorics , marketing , business , operating system
Characterization of purification processes by identifying significant input parameters and establishing predictive models is vital to developing robust processes. Current experimental design approaches restrict analysis to one process step at a time, which can severely limit the ability to identify interactions between process steps. This can be overcome by the use of partition designs which can model multiple, sequential process steps simultaneously. This paper presents the application of partition designs to a monoclonal antibody purification process. Three sequential purification steps were modeled using both traditional experimental designs and partition designs and the results compared as a proof of concept study. The partition and traditional design approaches identified the same input parameters within each process step that significantly affected the product quality output examined. The partition design also identified significant interactions between input parameters across process steps that could not be uncovered by the traditional approach. Biotechnol. Bioeng. 2010;107: 814–824. © 2010 Wiley Periodicals, Inc.