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 accessAbstract
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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Cites
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Cited by
Fisher, A. C., Kamga, M.-H., Agarabi, C., Brorson, K., Lee, S. L., & Yoon, S. (2019) · Trends in Biotechnology · doi:10.1016/j.tibtech.2018.08.008 · Cited by 180
Bioprocess Control: Current Progress and Future Perspectives
Rathore, A. S., Mishra, S., Nikita, S., & Priyanka, P. (2021) · Life · doi:10.3390/life11060557 · Cited by 141
Evolution of Escherichia coli Expression System in Producing Antibody Recombinant Fragments
Sandomenico, A., Sivaccumar, J. P., & Ruvo, M. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21176324 · Cited by 134
“Various cultivation parameters, such as media composition, pH, agitation, aeration, temperature, cell density, concentration of inducers, induction time and strategies affect the protein expression level depending upon expression system [82].”
BackgroundHa, T. K., Kim, D., Kim, C. L., Grav, L. M., & Lee, G. M. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107831 · Cited by 74
Kornecki, M., & Strube, J. (2018) · Bioengineering · doi:10.3390/bioengineering5010025 · Cited by 61
Self-citation
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)
- 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.
