The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Oral lipid-based drug delivery systems – an overview
Open accessAbstract
The formulation of drugs is carried out with the principle objective of enhancing their bioavailability. Poorly water soluble drugs are challenging for the formulation scientists with regard to solubility and bioavailability. Lipid-based drug delivery systems (LBDDS) are one of the emerging technologies designed to address such challenges. Encapsulating or solubilizing the drug in lipid excipients can lead to increased solubilization and absorption, resulting in enhanced bioavailability. Recent advances in these formulation technologies have led to the successful commercialization of lipid-based formulations. This review provides a comprehensive summary and characterization of lipid-based formulations, especially for oral delivery, from both physicochemical and biopharmaceutical perspectives. This review also focuses on the processing techniques necessary to obtain solid lipid-based formulations for oral delivery, along with a brief discussion of lipid excipients and their characterization.
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Cites
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Self-citationRole of nanoparticle size, shape and surface chemistry in oral drug delivery
Banerjee, A., Qi, J., Gogoi, R., Wong, J., & Mitragotri, S. (2016) · Journal of Controlled Release · doi:10.1016/j.jconrel.2016.07.051 · Cited by 773
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Metadata
- Authors
- Kalepu, S., Manthina, M., & Padavala, V.
- Venue
- Acta Pharmaceutica Sinica B
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 3
- Issue
- 6
- Pages
- 361-372
- ISSN
- 2211-3835 (ISSN-L)
- OpenAlex
- W2029074248
- Cited by
- 494
- References
- 72
- FWCI
- 12.85
- Type
- journal article
- Language
- en
- Open access
- gold
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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.