The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Aggregates in monoclonal antibody manufacturing processes
Abstract
Monoclonal antibodies have proved to be a highly successful class of therapeutic products. Large‐scale manufacturing of pharmaceutical antibodies is a complex activity that requires considerable effort in both process and analytical development. If a therapeutic protein cannot be stabilized adequately, it will lose partially or totally its therapeutic properties or even cause immunogenic reactions thus potentially further endangering the patients' health. The phenomenon of protein aggregation is a common issue that compromises the quality, safety, and efficacy of antibodies and can happen at different steps of the manufacturing process, including fermentation, purification, final formulation, and storage. Aggregate levels in drug substance and final drug product are a key factor when assessing quality attributes of the molecule, since aggregation might impact biological activity of the biopharmaceutical. In this review it is analyzed how aggregates are formed during monoclonal antibody industrial production, why they have to be removed and the manufacturing process steps that are designed to either minimize or remove aggregates in the final product. Biotechnol. Bioeng. 2011; 108:1494–1508. © 2011 Wiley Periodicals, Inc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Effects of protein aggregates: An immunologic perspective
Rosenberg, A. S. (2006) · The AAPS Journal · doi:10.1208/aapsj080359 · Cited by 1,355
Impact of Product-Related Factors on Immunogenicity of Biotherapeutics
Singh, S. K. (2011) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.22276 · Cited by 350
Potential aggregation prone regions in biotherapeutics: A survey of commercial monoclonal antibodies
Wang, X., Das, T. K., Singh, S. K., & Kumar, S. (2009) · mAbs · doi:10.4161/mabs.1.3.8035 · Cited by 198
Current and future issues in the manufacturing and development of monoclonal antibodies
Kozlowski, S., & Swann, P. (2006) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2006.05.002 · Cited by 170 · cited 1×
“In the absence of information on clinical relevance and process control, many specifications are instituted with narrower than necessary acceptance ranges based on manufacturing experience (Kozlowski and Swann, 2006).”
Background
Cited by
Aggregation risk prediction for antibodies and its application to biotherapeutic development
Obrezanova, O., Arnell, A., de la Cuesta, R. G., Berthelot, M. E., Gallagher, T. R., Zurdo, J., & Stallwood, Y. (2015) · mAbs · doi:10.1080/19420862.2015.1007828 · Cited by 107
Bush, D. R., Zang, L., Belov, A. M., Ivanov, A. R., & Karger, B. L. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b03218 · Cited by 92
Ha, 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
Patel, B. A., Gospodarek, A., Larkin, M., Kenrick, S. A., Haverick, M. A., Tugcu, N., Brower, M. A., & Richardson, D. D. (2018) · mAbs · doi:10.1080/19420862.2018.1505178 · Cited by 52
Uchino, T., Miyazaki, Y., Yamazaki, T., & Kagawa, Y. (2017) · Journal of Pharmacy and Pharmacology · doi:10.1111/jphp.12765 · Cited by 49
Metadata
- Authors
- Vázquez‐Rey, M., & Lang, D. A.
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 2011-04-20
- Volume
- 108
- Issue
- 7
- Pages
- 1494-1508
- ISSN
- 0006-3592 (ISSN-L)
- 1097-0290
- OpenAlex
- W2028489320
- Cited by
- 479
- References
- 4
- FWCI
- 7.88
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Aggregates in monoclonal antibody manufacturing processes. https://app.cochat.ai/papers/10.1002/bit.23155
- The paper
- Vázquez‐Rey, M., & Lang, D. A. (2011). Aggregates in monoclonal antibody manufacturing processes. Biotechnology and Bioengineering. https://doi.org/10.1002/bit.23155
Data sources
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.
