The DOI matches its Crossref record; 119 of the 119 references it cites were found in a registry or an index.
An overview of active and passive targeting strategies to improve the nanocarriers efficiency to tumour sites
Abstract
Objectives: This review highlights both the physicochemical characteristics of the nanocarriers (NCs) and the physiological features of tumour microenvironment (TME) to outline what strategies undertaken to deliver the molecules of interest specifically to certain lesions. This review discusses these properties describing the convenient choice between passive and active targeting mechanisms with details, illustrated with examples of targeting agents up to preclinical research or clinical advances. Key findings: Targeted delivery approaches for anticancers have shown a steep rise over the past few decades. Though many successful preclinical trials, only few passive targeted nanocarriers are approved for clinical use and none of the active targeted nanoparticles. Herein, we review the principles and for both processes and the correlation with the tumour microenvironment. We also focus on the limitation and advantages of each systems regarding laboratory and industrial scale. Summary: The current literature discusses how the NCs and the enhanced permeation and retention effect impact the passive targeting. Whereas the active targeting relies on the ligand-receptor binding, which improves selective accumulation to targeted sites and thus discriminates between the diseased and healthy tissues. The latter could be achieved by targeting the endothelial cells, tumour cells, the acidic environment of cancers and nucleus.
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Immune Cell Membrane‐Coated Biomimetic Nanoparticles for Targeted Cancer Therapy
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Metadata
- Authors
- Attia, M. F., Anton, N., Wallyn, J., Omran, Z., & Vandamme, T. F.
- Venue
- Journal of Pharmacy and Pharmacology
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-08-01
- Volume
- 71
- Issue
- 8
- Pages
- 1185-1198
- ISSN
- 0022-3573 (ISSN-L)
- 2042-7158
- OpenAlex
- W2943106036
- Cited by
- 1,085
- References
- 119
- FWCI
- 24.01
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
