Biomedical Engineering Reference
In-Depth Information
variation in the duration of this step associated with more or less column cycling. This
flexibility in column loading and the number of chromatography cycles/batch would
allow the trade-offs between step yield, buffer usage and processing time to be managed
according to the lot of AEX resin that is in use. The potential effect of a variable load
volume onto the subsequent chromatography step would need to be well understood
before implementation of this aspect of the design space.
7.8 SUMMARY
An expanded, approved design spacewill allow for postapproval process changes (within
the design space) with a reduced burden of regulatory submission. This added flexibility
will allow manufacturers of biopharmaceutical products to better leverage process
understanding gained during process development and subsequent manufacturing
experience. Establishing design space during process development entails process
characterization studies with verified scaled-down systems that accurately model the
performance of the manufacturing-scale process. Design of Experiments is required to
detect interactions between variables, establish predictive models and ultimately estab-
lish operating ranges for key and critical operational parameters. Risk assessment will
help identify the subset of process steps most likely to benefit from an expanded design
space and early identification of critical and key parameters for these process steps will
further focus the experimental scope. The examples provided in this chapter demonstrate
how design space can be applied to biopharmaceutical purification processes for
improved control of product and process and to provide valuable flexibility to
manufacturing operations.
ACKNOWLEDGMENTS
The author would like to thankmembers of the purification process development group at
Biogen Idec, most notably Jorg Thommes, Lynn Conley, and John Pieracci, for their
suggestions and contributions.
REFERENCES
[1] Sarolta A, Kinley RD. Multivariate statistical monitoring of batch processes: an industrial
case study of fermentation supervision. Trends Biotechnol 2001;19:53-62.
[2] Ganguly J, Vogel G. Process analytical technology (PAT) and scalable automation for
bioprocess control and monitoring—a case study. Pharm Eng 2006;26(1).
[3] U.S. Food and Drug Administration. Guidance for Industry: PAT-A Framework for Innova-
tive Pharmaceutical Development, Manufacturing, and Quality Assurance. 2004. (http://
www.fda.gov/CDER/GUIDANCE/6419fnl.htm)
[4] U.S. Food and Drug Administration. Guidance for Industry: Q8 Pharmaceutical Develop-
ment. 2006. (http://www.fda.gov/CbER/gdlns/ichq8pharm.htm)
