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Nahar L, Chaiwut P, Sangthong S, Theansungnoen T, Sarker SD. Progress in the analysis of phytocannabinoids by HPLC and UPLC (or UHPLC) during 2020-2023. PHYTOCHEMICAL ANALYSIS : PCA 2024; 35:927-989. [PMID: 38837522 DOI: 10.1002/pca.3374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 04/22/2024] [Accepted: 04/22/2024] [Indexed: 06/07/2024]
Abstract
INTRODUCTION Organic molecules that bind to cannabinoid receptors are known as cannabinoids. These molecules possess pharmacological properties similar to those produced by Cannabis sativa L. High-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC, also known as ultra-high-performance liquid chromatography, UHPLC) have become the most widely used analytical tools for detection and quantification of phytocannabinoids in various matrices. HPLC and UPLC (or UHPLC) are usually coupled to an ultraviolet (UV), photodiode array (PDA), or mass spectrometric (MS) detector. OBJECTIVE To critically appraise the literature on the application of HPLC and UPLC (or UHPLC) methods for the analysis of phytocannabinoids published from January 2020 to December 2023. METHODOLOGY An extensive literature search was conducted using Web of Science, PubMed, and Google Scholar and published materials including relevant books. In various combinations, using cannabinoid in all combinations, cannabis, hemp, hashish, C. sativa, marijuana, analysis, HPLC, UHPLC, UPLC, and quantitative, qualitative, and quality control were used as the keywords for the literature search. RESULTS Several HPLC- and UPLC (or UHPLC)-based methods for the analysis of phytocannabinoids were reported. While simple HPLC-UV or HPLC-PDA-based methods were common, the use of HPLC-MS, HPLC-MS/MS, UPLC (or UHPLC)-PDA, UPLC (or UHPLC)-MS, and UPLC (or UHPLC)-MS/MS was also reported. Applications of mathematical and computational models for optimization of protocols were noted. Pre-analyses included various environmentally friendly extraction protocols. CONCLUSION During the last 4 years, HPLC and UPLC (or UHPLC) remained the main analytical tools for phytocannabinoid analysis in different matrices.
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Affiliation(s)
- Lutfun Nahar
- Laboratory of Growth Regulators, Palacký University and Institute of Experimental Botany, The Czech Academy of Sciences, Olomouc, Czech Republic
| | - Phanuphong Chaiwut
- Green Cosmetic Technology Research Group, School of Cosmetic Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Sarita Sangthong
- Green Cosmetic Technology Research Group, School of Cosmetic Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Tinnakorn Theansungnoen
- Green Cosmetic Technology Research Group, School of Cosmetic Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Satyajit D Sarker
- Centre for Natural Products Discovery, School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
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Durante C, Anceschi L, Brighenti V, Caroli C, Afezolli C, Marchetti A, Cocchi M, Salamone S, Pollastro F, Pellati F. Application of experimental design in HPLC method optimisation for the simultaneous determination of multiple bioactive cannabinoids. J Pharm Biomed Anal 2022; 221:115037. [PMID: 36148721 DOI: 10.1016/j.jpba.2022.115037] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 12/24/2022]
Abstract
The scientific interest in Cannabis sativa L. analysis has been rapidly increasing in recent years, especially for what concerns cannabinoids, plant secondary metabolites which are well known for having many biological properties. High-performance liquid chromatography (HPLC) is frequently used for both the qualitative and quantitative analysis of cannabinoids in plant extracts from C. sativa and its derived products. Many studies have been focused on the main cannabinoids, such as ∆9-tetrahydrocannabinolic acid (∆9-THCA), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA) and their decarboxylated derivatives, such as ∆9-tetrahydrocannabinol (∆9-THC), cannabidiol (CBD) and cannabigerol (CBG). In addition to the abovementioned compounds, the plant produces other metabolites of the same chemical class, and some of them have shown interesting biological activities. In the light of this, it is important to have efficient analytical methods for the simultaneous separation of cannabinoids, which is quite complex since they present similar chemical-physical characteristics. The present work is focused on the use of the Design of Experiments technique (DoE) to develop and optimise an HPLC method for the simultaneous separation of 14 cannabinoids. Experimental design optimisation was applied by using a Central Composite Face-Centered design to achieve the best resolution with minimum experimental trials. Five significant variables affecting the chromatographic separation, including ammonium formate concentration, gradient elution, run time and flow rate, were studied. A multivariate strategy, based on Principal Component Analysis (PCA) and Partial Least Squared (PLS) regression, was used to define the best operative conditions. The developed method allowed for the separation of 12 out of 14 cannabinoids. Due to co-elution phenomena, HPLC coupled with a triple quadrupole mass analyser (HPLC-ESI-MS/MS) was applied, monitoring the specific transitions of each compound in the multiple reaction monitoring (MRM) mode. Finally, the optimised method was applied to C. sativa extracts having a different cannabinoid profile to demonstrate its efficiency to real samples. The methodology applied in this study can be useful for the separation of other cannabinoid mixtures, by means of appropriate optimisation of the experimental conditions.
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Affiliation(s)
- Caterina Durante
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, Modena 41125, Italy.
| | - Lisa Anceschi
- Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy; Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Via G. Campi 287, 41125 Modena, Italy
| | - Virginia Brighenti
- Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy
| | - Clarissa Caroli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy; Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Via G. Campi 287, 41125 Modena, Italy
| | - Cindy Afezolli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy
| | - Andrea Marchetti
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, Modena 41125, Italy
| | - Marina Cocchi
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, Modena 41125, Italy
| | - Stefano Salamone
- Department of Pharmaceutical Sciences, University of Eastern Piedmont, Largo Donegani 2, 28100 Novara, Italy; PlantaChem srls, via A. Canobio 4/6, 28100 Novara, Italy
| | - Federica Pollastro
- Department of Pharmaceutical Sciences, University of Eastern Piedmont, Largo Donegani 2, 28100 Novara, Italy; PlantaChem srls, via A. Canobio 4/6, 28100 Novara, Italy
| | - Federica Pellati
- Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy.
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