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Cited by 337

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Very Large Scale Monoclonal Antibody Purification: The Case for Conventional Unit Operations

Kelley, B.·2007·Biotechnology Progress

Abstract

Technology development initiatives targeted for monoclonal antibody purification may be motivated by manufacturing limitations and are often aimed at solving current and future process bottlenecks. A subject under debate in many biotechnology companies is whether conventional unit operations such as chromatography will eventually become limiting for the production of recombinant protein therapeutics. An evaluation of the potential limitations of process chromatography and filtration using today's commercially available resins and membranes was conducted for a conceptual process scaled to produce 10 tons of monoclonal antibody per year from a single manufacturing plant, a scale representing one of the world's largest single-plant capacities for cGMP protein production. The process employs a simple, efficient purification train using only two chromatographic and two ultrafiltration steps, modeled after a platform antibody purification train that has generated 10 kg batches in clinical production. Based on analyses of cost of goods and the production capacity of this very large scale purification process, it is unlikely that non-conventional downstream unit operations would be needed to replace conventional chromatographic and filtration separation steps, at least for recombinant antibodies.

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Metadata

Authors
Kelley, B.
Venue
Biotechnology Progress
Publisher
Wiley
Published
2007-09-22
Volume
0
Issue
0
Pages
0-0
ISSN
  • 1520-6033 (ISSN-L)
  • 8756-7938
OpenAlex
W1978177075
Cited by
337
References
0
FWCI
6.70
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Very Large Scale Monoclonal Antibody Purification: The Case for Conventional Unit Operations. https://app.cochat.ai/papers/10.1021/bp070117s
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Kelley, B. (2007). Very Large Scale Monoclonal Antibody Purification: The Case for Conventional Unit Operations. Biotechnology Progress. https://doi.org/10.1021/bp070117s

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.