The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
pH-Responsive Nanocarriers in Cancer Therapy
Open accessAbstract
A number of promising nano-sized particles (nanoparticles) have been developed to conquer the limitations of conventional chemotherapy. One of the most promising methods is stimuli-responsive nanoparticles because they enable the safe delivery of the drugs while controlling their release at the tumor sites. Different intrinsic and extrinsic stimuli can be used to trigger drug release such as temperature, redox, ultrasound, magnetic field, and pH. The intracellular pH of solid tumors is maintained below the extracellular pH. Thus, pH-sensitive nanoparticles are highly efficient in delivering drugs to tumors compared to conventional nanoparticles. This review provides a survey of the different strategies used to develop pH-sensitive nanoparticles used in cancer therapy.
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Cites
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“This will result in vesicular destabilization [38,43].”
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Cited by
Li, H., Li, B., Lv, D., Li, W., Lu, Y., & Luo, G. (2023) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2023.114778 · Cited by 142
Integrating Computational Design and Experimental Approaches for Next-Generation Biologics
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He, J., Xue, W., & Li, Y. (2026) · International Journal of Nanomedicine · doi:10.2147/ijn.s560983 · Cited by 16
Metadata
- Authors
- AlSawaftah, N. M., Awad, N. S., Pitt, W. G., & Husseini, G. A.
- Venue
- Polymers
- Publisher
- MDPI AG
- Published
- 2022-02-26
- Volume
- 14
- Issue
- 5
- Pages
- 936
- ISSN
- 2073-4360 (ISSN-L)
- OpenAlex
- W4214486368
- Cited by
- 268
- References
- 80
- FWCI
- 9.93
- Type
- journal article
- Language
- en
- Open access
- gold
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- AlSawaftah, N. M., Awad, N. S., Pitt, W. G., & Husseini, G. A. (2022). pH-Responsive Nanocarriers in Cancer Therapy. Polymers. https://doi.org/10.3390/polym14050936
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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.
