The DOI matches its Crossref record; 144 of the 144 references it cites were found in a registry or an index.
Nanomedicine review: clinical developments in liposomal applications
Open accessAbstract
Background: In recent years, disease treatment has evolved strategies that require increase in pharmaceutical agent’s efficacy and selectivity while decreasing their toxicity in normal tissues. These requirements have led to the development of nanoscale liposome systems for drug release. This review focuses on lipid features, pharmacological properties of liposomal formulations and the clinical studies of their application. Main body: Several lipids are available, but their properties could affect pharmacological or clinical efficiency of drug formulations. Many liposomal formulations have been developed and are currently on the market. Proper selection of lipid is essential for the pharmacological effect to be improved. Most of the formulations use mainly zwitterionic, cationic or anionic lipids, PEG and/or cholesterol, which have different effects on stability, pharmacokinetics and delivery of the drug formulation. Clinical trials have shown that liposomes are pharmacologically and pharmacokinetically more efficient than drug-alone formulations in treating acute myeloid leukemia, hepatitis A, pain management, ovary, gastric breast and lung cancer, among others. Conclusion: Liposomal formulations are less toxic than drugs alone and have better pharmacological parameters. Although they seem to be the first choice for drug delivery systems for various diseases, further research about dosage regimen regarding dose and time needs to be carried out.
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Cancer nanomedicine: progress, challenges and opportunities
Shi, J., Kantoff, P. W., Wooster, R., & Farokhzad, O. C. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2016.108 · Cited by 5,873
Liposomal drug delivery systems: From concept to clinical applications
Allen, T. M., & Cullis, P. R. (2013) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2012.09.037 · Cited by 4,839
Patisiran, an RNAi Therapeutic, for Hereditary Transthyretin Amyloidosis
Adams, D., Gonzalez-Duarte, A., O’Riordan, W. D., Yang, C.-C., Ueda, M., Kristen, A. V., Tournev, I., Schmidt, H. H., Coelho, T., Berk, J. L., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1716153 · Cited by 3,047
Advances and Challenges of Liposome Assisted Drug Delivery
Sercombe, L., Veerati, T., Moheimani, F., Wu, S. Y., Sood, A. K., & Hua, S. (2015) · Frontiers in Pharmacology · doi:10.3389/fphar.2015.00286 · Cited by 2,632
Magnetic iron oxide nanoparticles: synthesis and surface functionalization strategies
Wu, W., He, Q., & Jiang, C. (2008) · Nanoscale Research Letters · doi:10.1007/s11671-008-9174-9 · Cited by 2,300
Liposomes as nanomedical devices
Bozzuto, G., & Molinari, A. (2015) · International Journal of Nanomedicine · doi:10.2147/ijn.s68861 · Cited by 2,261
Controlled drug delivery vehicles for cancer treatment and their performance
Senapati, S., Mahanta, A. K., Kumar, S., & Maiti, P. (2018) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-017-0004-3 · Cited by 2,167
Liposomal Formulations in Clinical Use: An Updated Review
Bulbake, U., Doppalapudi, S., Kommineni, N., & Khan, W. (2017) · Pharmaceutics · doi:10.3390/pharmaceutics9020012 · Cited by 2,156
Applications of Carbon Nanotubes in Drug Delivery
Kaur, J., Gill, G. S., & Jeet, K. (2019) · Characterization and Biology of Nanomaterials for Drug Delivery · doi:10.1016/b978-0-12-814031-4.00005-2 · Cited by 2,019
Nanoparticles in the clinic: an update
Anselmo, A. C., & Mitragotri, S. (2019) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10143 · Cited by 1,766
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Metadata
- Authors
- Beltrán-Gracia, E., López-Camacho, A., Higuera-Ciapara, I., Velázquez-Fernández, J. B., & Vallejo-Cardona, A. A.
- Venue
- Cancer Nanotechnology
- Published
- 2019-12
- Volume
- 10
- Issue
- 1
- ISSN
- 1868-6958 (ISSN-L)
- 1868-6966
- OpenAlex
- W2995385432
- Cited by
- 513
- References
- 144
- FWCI
- 16.49
- Type
- journal article
- Language
- en
- Open access
- gold
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