HPLC–DAD method for cannabinoid quantification in Brazilian Cannabis oils and extracts

Abstract Background Cannabis sativa L. is one of the most versatile plants used by different cultures worldwide as a source of food, fiber, and medicine. Due to the variability of Cannabis, research on this plant and the standardization of medications and Cannabis-based products prove to be challenging. This study aimed to optimize and validate a high-performance liquid chromatography method coupled with photodiode array detection (HPLC–DAD) for the determination of cannabinoids in Cannabis extracts and medicinal oils produced in Brazil. Method The analytical procedure is distinguished by its simple sample preparation for cannabis oils and extracts, consisting only of dilution with anhydrous alcohol, this solvent eliminated phase separation and emulsions in lipid-rich matrices. Cannabinoid quantification was performed using conventional HPLC–DAD. Its performance was evaluated through validation parameters, including linearity, sensitivity, precision, and accuracy, and was applied to quantify eight cannabinoids in 15 different samples. Results The method demonstrated excellent linearity (R 2 > 0.999) for all analytes. It showed adequate sensitivity, with LOQ ranging from 0.11 to 0.34 µg/mL, as well as high precision, with RSD values below 5% for both intraday and interday analysis. Accuracy was confirmed through recovery studies, with an excellent recovery (103.2% to 103.4%) for CBD in a concentrated cannabis extract, while Δ 9 -THC recovery ranged from 86.1% to 90.6% in the medicinal oil matrix. Conclusion The results are promising for broadening the application of this chromatographic method to the determination of cannabinoids in Cannabis products produced by Brazilian Cannabis producers’ associations. The simple sample preparation methodology, combined with reliable validation parameters, provides a fast, sustainable, and cost-effective alternative to traditional, solvent-heavy extraction methods, addressing the demand for quality control.