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Cited by 329

The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.

Trends in Upstream and Downstream Process Development for Antibody Manufacturing

Open access
Gronemeyer, Petra, Ditz, Reinhard, Strube, Jochen·2014·Bioengineering
DOI 10.3390/bioengineering1040188
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Abstract

A steady increase of product titers and the corresponding change in impurity composition represent a challenge for development and optimization of antibody production processes. Additionally, increasing demands on product quality result in higher complexity of processes and analytics, thereby increasing the costs for product work-up. Concentration and composition of impurities are critical for efficient process development. These impurities can show significant variations, which primarily depend on culture conditions. They have a major impact on the work-up strategy and costs. The resulting “bottleneck” in downstream processing requires new optimization, technology and development approaches. These include the optimization and adaptation of existing unit operations respective to the new separation task, the assessment of alternative separation technologies and the search for new methods in process development. This review presents an overview of existing methods for process optimization and integration and indicates new approaches for future developments.

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Crossref · 10.3390/bioengineering1040188

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Metadata

Authors
Gronemeyer, P., Ditz, R., & Strube, J.
Venue
Bioengineering
Publisher
MDPI AG
Published
2014-10-01
Volume
1
Issue
4
Pages
188-212
ISSN
2306-5354 (ISSN-L)
DOI
10.3390/bioengineering1040188
OpenAlex
W2100508150
Cited by
329
References
103
FWCI
8.64
Type
journal article
Language
en
Open access
gold

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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