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@article{210914,
author = {Nishi Yadav and Anoop Kumar Singh},
title = {Atorvastatin-Loaded Mucoadhesive NLCs for Buccal Delivery: A Short Review},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {13},
number = {6},
pages = {2631-2642},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=210914},
abstract = {Atorvastatin calcium is one of the most widely prescribed lipid-lowering drugs, yet its absolute oral bioavailability is only about 14 % because of poor aqueous solubility, extensive presystemic metabolism by cytochrome P450 3A4 and intestinal efflux. The buccal mucosa offers a route that drains directly into the systemic circulation through the jugular venous system and therefore bypasses the hepatic first pass, but its usefulness is limited by short residence time and by the barrier properties of the non-keratinised epithelium. Nanostructured lipid carriers (NLCs), which are blends of solid and liquid lipids stabilised by surfactants, can increase the loading and apparent solubility of lipophilic drugs, and when dispersed in a mucoadhesive gel they may combine controlled release with prolonged mucosal contact. This short review summarises, from open online literature, the biopharmaceutical case for buccal delivery of atorvastatin, the anatomy and permeability of the buccal mucosa, the structure, composition and preparation of NLCs, the mechanisms and polymers of mucoadhesion, and the quantitative evidence available from NLC-based and statin-based buccal systems. Quality by design tools such as the Box-Behnken design and ex vivo permeation testing on porcine buccal mucosa are discussed as the practical route to a robust formulation. Current gaps, including the absence of in vivo pharmacokinetic data for an atorvastatin NLC buccal gel, are identified, and priorities for future work are proposed.},
keywords = {Atorvastatin; nanostructured lipid carriers; buccal delivery; mucoadhesion; first-pass metabolism; Box-Behnken design; ex vivo permeation},
month = {November},
}
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