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Modern Subunit Vaccines: Development, Components, and Research Opportunities
Abstract
Traditional vaccines, based on the administration of killed or attenuated microorganisms, have proven to be among the most effective methods for disease prevention. Safety issues related to administering these complex mixtures, however, prevent their universal application. Through identification of the microbial components responsible for protective immunity, vaccine formulations can be simplified, enabling molecular‐level vaccine characterization, improved safety profiles, prospects to develop new high‐priority vaccines (e.g. for HIV, tuberculosis, and malaria), and the opportunity for extensive vaccine component optimization. This subunit approach, however, comes at the expense of decreased immunity, requiring the addition of immunostimulatory agents (adjuvants). As few adjuvants are currently used in licensed vaccines, adjuvant development represents an exciting area for medicinal chemists to play a role in the future of vaccine development. In addition, immune responses can be further customized though optimization of delivery systems, tuning the size of particulate vaccines, targeting specific cells of the immune system (e.g. dendritic cells), and adding components to aid vaccine efficacy in whole immunized populations (e.g. promiscuous T‐helper epitopes). Herein we review the current state of the art and future direction in subunit vaccine development, with a focus on the described components and their potential to steer the immune response toward a desired response.
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Metadata
- Authors
- Moyle, P. M., & Toth, I.
- Venue
- ChemMedChem
- Publisher
- Wiley
- Published
- 2013-01-11
- Volume
- 8
- Issue
- 3
- Pages
- 360-376
- ISSN
- 1860-7179 (ISSN-L)
- 1860-7187
- OpenAlex
- W1976136842
- Cited by
- 464
- References
- 215
- FWCI
- 11.17
- 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.
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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.