Lipid-drug-conjugate (LDC) solid lipid nanoparticles (SLN) for the delivery of nicotine to the oral cavity – Optimization of nicotine loading efficiency

[Display omitted] Nicotine, obtained from tobacco leaves, has been used to promote the cessation of smoking and reduce the risk of COPD and lung cancer. Incorporating the active in lipid nanoparticles is an effective tool to minimize its irritation potential and to use the particles as intermediate...

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Published inEuropean journal of pharmaceutics and biopharmaceutics Vol. 128; pp. 10 - 17
Main Authors Ding, Yuan, Nielsen, Kent A., Nielsen, Bruno P., Bøje, Niels W., Müller, Rainer H., Pyo, Sung Min
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.07.2018
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Summary:[Display omitted] Nicotine, obtained from tobacco leaves, has been used to promote the cessation of smoking and reduce the risk of COPD and lung cancer. Incorporating the active in lipid nanoparticles is an effective tool to minimize its irritation potential and to use the particles as intermediate to produce final products. However, as a hydrophilic active, it is a challenge to prepare nicotine loaded lipid nanoparticles with high drug loading. In this study, lipid-drug-conjugates (LDC) were formed by nicotine and different fatty acids to enable the production of sufficiently loaded nicotine lipid nanoparticles. The encapsulation efficiency of nicotine in LDC-containing SLN was about 50%, which increased at least fourfold compared to the non-LDC formulations (around 10%) due to the increased lipophilicity of nicotine by strong interactions between positively charged nicotine and negatively charged fatty acids (formation of LDCs). The z-average of all formulations (150–350 nm) proved to be in the required submicron size range with a narrow size distribution. In summary, nicotine loaded LDC lipid nanoparticles with high drug loading were successfully developed with Kolliwax® S and stearic acid as counter-ion forming the LDC and hydrogenated sunflower oil (HSO) as lipid particle matrix.
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ISSN:0939-6411
1873-3441
DOI:10.1016/j.ejpb.2018.03.004