An innovative method for the extraction and HPLC analysis of bioactive policosanols from non-psychoactive Cannabis sativa L

J Pharm Biomed Anal. 2023 Jun 24;234:115547. doi: 10.1016/j.jpba.2023.115547. Online ahead of print.

ABSTRACT

Policosanols (PCs) refer to a mixture of long-chain aliphatic alcohols. Sugar cane is the main industrial source of PCs, but others, including beeswax and Cannabis sativa L., are also known. In the raw material PCs are bonded to fatty acids to form long-chain esters, known as waxes. PCs are mainly used as a cholesterol-lowering product, even though their efficacy is controversial. More recently, the pharmacological interest in PCs has increased, as they have been investigated as antioxidant, anti-inflammatory and anti-proliferative agents. Given their promising biological implications, the development of efficient extraction and analytical methodologies for the determination of PCs is extremely important to identify new potential sources of these compounds and to ensure the reproducibility of biological data. Conventional techniques used for the extraction of PCs involve time-consuming approaches leading to low yields, while analytical methods for their quantification are based on gas-chromatographic (GC) techniques, which require an additional derivatization step during the sample preparation to increase their volatility. In the light of all the above, this work was aimed at the development of an innovative method for the extraction of PCs from non-psychoactive C. sativa (hemp) inflorescences, taking advantage of the microwave-assisted technology. In addition, a new analytical method based on high-performance liquid chromatography (HPLC) coupled with an evaporative light scattering detector (ELSD) was developed for the first time for both the qualitative and quantitative analysis of these compounds in the extracts. The method was validated according to ICH guidelines, and it was applied to the analysis of PCs in hemp inflorescences belonging to different varieties. The results were analyzed using Principal Component Analysis (PCA) and hierarchical clustering analysis to rapidly identify samples with the highest content of PCs, which might find an application as alternative sources of these bioactive compounds in both the pharmaceutical and nutraceutical fields.

PMID:37413918 | DOI:10.1016/j.jpba.2023.115547