The DOI matches its Crossref record; 222 of the 222 references it cites were found in a registry or an index.
Avidity in antibody effector functions and biotherapeutic drug design
Open accessAbstract
Antibodies are the cardinal effector molecules of the immune system and are being leveraged with enormous success as biotherapeutic drugs. A key part of the adaptive immune response is the production of an epitope-diverse, polyclonal antibody mixture that is capable of neutralizing invading pathogens or disease-causing molecules through binding interference and by mediating humoral and cellular effector functions. Avidity — the accumulated binding strength derived from the affinities of multiple individual non-covalent interactions — is fundamental to virtually all aspects of antibody biology, including antibody–antigen binding, clonal selection and effector functions. The manipulation of antibody avidity has since emerged as an important design principle for enhancing or engineering novel properties in antibody biotherapeutics. In this Review, we describe the multiple levels of avidity interactions that trigger the overall efficacy and control of functional responses in both natural antibody biology and their therapeutic applications. Within this framework, we comprehensively review therapeutic antibody mechanisms of action, with particular emphasis on engineered optimizations and platforms. Overall, we describe how affinity and avidity tuning of engineered antibody formats are enabling a new wave of differentiated antibody drugs with tailored properties and novel functions, promising improved treatment options for a wide variety of diseases. Antibody function is dependent on avidity — the accumulated strength of multiple affinity interactions between the antibody, antigen, cell surface receptors and other antibodies. In this Review, Oostindie et al. discuss the role of avidity in eliciting antibody functional responses and review the current engineering strategies for manipulating avidity interactions in antibody-based therapies.
Verifying this paper
8 of 9 steps done · this page updates itself — you can leave and come back
- Registry recordVerified
- Full textRead the full text
- Reference list222 references found
- Reference checkChecking each cited work — 222 of 222
- StatisticsNeeds the full text
- ClaimsNeeds the full text
- Cited sourcesNeeds claims to check
- Self-checkNeeds the full text
- VerificationFindings verified
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
Continuous cultures of fused cells secreting antibody of predefined specificity
KÖHLER, G., & MILSTEIN, C. (1975) · Nature · doi:10.1038/256495a0 · Cited by 17,229
Somatic generation of antibody diversity
Tonegawa, S. (1983) · Nature · doi:10.1038/302575a0 · Cited by 4,005
IgG Subclasses and Allotypes: From Structure to Effector Functions
Vidarsson, G., Dekkers, G., & Rispens, T. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00520 · Cited by 2,667
Clonal selection and learning in the antibody system
Rajewsky, K. (1996) · Nature · doi:10.1038/381751a0 · Cited by 1,709
A Randomized, Controlled Trial of Ebola Virus Disease Therapeutics
Mulangu, S., Dodd, L. E., Davey, R. T., Tshiani Mbaya, O., Proschan, M., Mukadi, D., Lusakibanza Manzo, M., Nzolo, D., Tshomba Oloma, A., Ibanda, A., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1910993 · Cited by 1,605
Bruhns, P., Iannascoli, B., England, P., Mancardi, D. A., Fernandez, N., Jorieux, S., & Daëron, M. (2009) · Blood · doi:10.1182/blood-2008-09-179754 · Cited by 1,479
Bispecific antibodies: a mechanistic review of the pipeline
Labrijn, A. F., Janmaat, M. L., Reichert, J. M., & Parren, P. W. H. I. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0028-1 · Cited by 1,303
Self-citationBaum, A., Fulton, B. O., Wloga, E., Copin, R., Pascal, K. E., Russo, V., Giordano, S., Lanza, K., Negron, N., Ni, M., et al. (2020) · Science · doi:10.1126/science.abd0831 · Cited by 1,253
Studies in humanized mice and convalescent humans yield a SARS-CoV-2 antibody cocktail
Hansen, J., Baum, A., Pascal, K. E., Russo, V., Giordano, S., Wloga, E., Fulton, B. O., Yan, Y., Koon, K., Patel, K., et al. (2020) · Science · doi:10.1126/science.abd0827 · Cited by 1,210
Shields, R. L., Namenuk, A. K., Hong, K., Meng, Y. G., Rae, J., Briggs, J., Xie, D., Lai, J., Stadlen, A., Li, B., et al. (2001) · Journal of Biological Chemistry · doi:10.1074/jbc.m009483200 · Cited by 1,161
Cited by
The Unique Properties of IgG4 and Its Roles in Health and Disease
Rispens, T., & Huijbers, M. G. (2023) · Nature Reviews Immunology · doi:10.1038/s41577-023-00871-z · Cited by 282
Advances in molecular pathology and therapy of non-small cell lung cancer
Huang, Q., Li, Y., Huang, Y., Wu, J., Bao, W., Xue, C., Li, X., Dong, S., Dong, Z., & Hu, S. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02243-6 · Cited by 197
The Dawn of a New Era: Targeting the “Undruggables” with Antibody-Based Therapeutics
Qian, L., Lin, X., Gao, X., Khan, R. U., Liao, J.-Y., Du, S., Ge, J., Zeng, S., & Yao, S. Q. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00915 · Cited by 155
Lv, J., Wang, J., Yang, L., Liu, W., Fu, H., Chu, P. K.-H., & Liu, C. (2024) · Sensors & Diagnostics · doi:10.1039/d4sd00045e · Cited by 141
T-Cell Engagers in Solid Cancers—Current Landscape and Future Directions
Shanshal, M., Caimi, P. F., Adjei, A. A., & Ma, W. W. (2023) · Cancers · doi:10.3390/cancers15102824 · Cited by 74
Metadata
- Authors
- Oostindie, S. C., Lazar, G. A., Schuurman, J., & Parren, P. W. H. I.
- Affiliations
- Leiden University Medical Center (NL)
- Genentech (US)
- Genmab (Netherlands) (NL)
- Corresponding author
- Parren, Paul W. H. I.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2022-07-05
- Volume
- 21
- Issue
- 10
- Pages
- 715-735
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- PMC
- PMC9255845
- OpenAlex
- W4284671925
- Semantic Scholar
- be6f5d6d3d37d0831e6f2257d741a96dd4f16cc9
- Cited by
- 298
- References
- 222
- Citations by year
- 2026: 82 · 2025: 87 · 2024: 77 · 2023: 47 · 2022: 5
- FWCI
- 5.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Locations
- Nature Reviews Drug Discovery (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Leiden Repository (Leiden University) (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
- Life Sciences › Immunology and Microbiology › Immunology › Biosimilars and Bioanalytical Methods
- Keywords
- antibody avidity, antibody affinity, biologic therapy, engineered antibodies, antibody effector functions, antibody-antigen binding, antibody-antibody interaction, neutralization, clonal selection
- MeSH terms
- Antibodies, Monoclonal, Antibody Affinity, Epitopes, Humans, Drug Design, Antibodies, Neutralizing
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: Avidity in antibody effector functions and biotherapeutic drug design. https://app.cochat.ai/papers/10.1038/s41573-022-00501-8
- The paper
- Oostindie, S. C., Lazar, G. A., Schuurman, J., & Parren, P. W. H. I. (2022). Avidity in antibody effector functions and biotherapeutic drug design. Nature Reviews Drug Discovery. https://doi.org/10.1038/s41573-022-00501-8
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.
