Monoclonal antibodies for prophylactic and therapeutic use against viral infections
Open accessAbstract
Neutralizing antibodies play an essential part in antiviral immunity and are instrumental in preventing or modulating viral diseases. Polyclonal antibody preparations are increasingly being replaced by highly potent monoclonal antibodies (mAbs). Cocktails of mAbs and bispecific constructs can be used to simultaneously target multiple viral epitopes and to overcome issues of neutralization escape. Advances in antibody engineering have led to a large array of novel mAb formats, while deeper insight into the biology of several viruses and increasing knowledge of their neutralizing epitopes has extended the list of potential targets. In addition, progress in developing inexpensive production platforms will make antiviral mAbs more widely available and affordable.
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It is possible to generate protective mAbs against many viruses and microorganisms.
“there is ample evidence that it is possible to generate protective mAbs against many viruses and microorganisms (Teitelbaum et al, 1998; Nosanchuk et al, 2003; Both et al, 2013).”
From mRNA mediates passive vaccination against infectious agents, toxins, and tumors (2017) · cites this paper as Both et al, 2013
The Development of monoclonal antibodies section reports that many antiviral mAbs have been developed, and the Antiviral immunity section describes protection in mAb-treated mice. The paper supports the claim for viruses, but the passages do not establish it for other microorganisms (searched: bacteria, fungi, parasites, and nonviral pathogens). No page numbers are available in our copy. (LLM, conf=0.87)
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How mRNA therapeutics are entering the monoclonal antibody field
Van Hoecke, L., & Roose, K. (2019) · Journal of Translational Medicine · doi:10.1186/s12967-019-1804-8 · Cited by 205 · see citing works
mRNA mediates passive vaccination against infectious agents, toxins, and tumors
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“Nevertheless, there is ample evidence that it is possible to generate protective mAbs against many viruses and microorganisms (Teitelbaum et al, 1998; Nosanchuk et al, 2003; Both et al, 2013).”
BackgroundErasmus, J. H., Archer, J., Fuerte-Stone, J., Khandhar, A. P., Voigt, E., Granger, B., Bombardi, R. G., Govero, J., Tan, Q., Durnell, L. A., et al. (2020) · Molecular Therapy - Methods & Clinical Development · doi:10.1016/j.omtm.2020.06.011 · Cited by 118 · see citing works
- Authors
- Both, L., Banyard, A. C., van Dolleweerd, C., Wright, E., Ma, J. K.-C., & Fooks, A. R.
- Affiliations
- University of London (GB)
- Animal and Plant Health Agency (GB)
- University of Westminster (GB)
- University of Liverpool (GB)
- Corresponding author
- Fooks, Anthony R.
- Venue
- Vaccine
- Publisher
- Elsevier BV
- Published
- 2013-03
- Volume
- 31
- Issue
- 12
- Pages
- 1553-1559
- ISSN
- 0264-410X (ISSN-L)
- PMC
- PMC7115371
- OpenAlex
- W2157171051
- Cited by
- 107
- References
- 103
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 8 · 2023: 9 · 2022: 10 · 2021: 11 · 2020: 10 · 2019: 3 · 2018: 8 · 2017: 9 · 2016: 7 · 2015: 9 · 2014: 8 · 2013: 3
- FWCI
- 1.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Vaccine (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- WestminsterResearch (University of Westminster) (acceptedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Epidemiology › Virology and Viral Diseases
- Keywords
- monoclonal antibodies, neutralizing antibodies, antiviral immunity, prophylaxis, bispecific antibodies, neutralization escape, antibody engineering, viral epitopes, viral infection
- MeSH terms
- Antibodies, Monoclonal, Antibodies, Viral, Antibody Specificity, Antiviral Agents, Humans, Immunization, Passive, Virus Diseases, Protein Engineering, 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 ›
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