Mid-infrared spectroscopy as process analytical technology tool for estimation of THC and CBD content in Cannabis flowers and extracts

Development of an accelerated ageing protocol for the study of phytocannabinoid stability in Cannabis sativa L

Cannabis sativa L. is a plant belonging to the Cannabaceae family known primarily for its recreational use due to the psychoactive properties of Δ9-tetrahydrocannabinol (THC). Despite this, several compounds belonging to the category of phytocannabinoids have shown in recent years a number of potentially promising therapeutic effects that have increased the interest in the pharmaceutical field towards this plant. However, the content of these compounds is very variable and influenced by different factors, such as growing conditions and time of the year. An indication of the status and age of Cannabis samples is provided by the content of CBN, a minor phytocannabinoid and degradation product of other phytocannabinoids, including THC. In this research work an innovative, solid state analytical approach has been developed to observe and evaluate the variations in the content of two phytocannabinoids (CBN and CBD) in Cannabis-derived products over time. In order to simulate the ageing of the Cannabis samples, an artificially accelerated ageing procedure has been developed and optimised by using high temperatures. The analyses were carried out using an innovative ATR-FTIR method for solid state analysis, enabling direct analysis of a solid sample without any pretreatment phase. This study has allowed the development of an innovative analytical approach for the evaluation of the age and state of conservation of Cannabis samples and may be a useful tool both in the industrial, pharmaceutical and forensic fields.

Comparative chemometric modeling of fresh and dry cannabis inflorescences using FT-NIR spectroscopy: Quantification and classification insights

INTRODUCTION

Cannabis sativa L. inflorescences are rich in cannabinoids and terpenes. Traditional chemical analysis methods for cannabinoids and terpenes, such as liquid and gas chromatography (using UV or MS detectors), are expensive and time-consuming.

OBJECTIVES

This study explores the use of Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometric approaches for classifying cannabis chemovars and predicting cannabinoid and terpene concentrations for the first time in freshly harvested (wet) cannabis inflorescence. The study also compares the performance of FT-NIR spectroscopy on wet versus dry cannabis inflorescences.

MATERIALS AND METHODS

Spectral data from 187 samples across seven cannabis chemovars were analyzed using partial least squares-discriminant analysis (PLS-DA) and partial least squares-regression (PLS-R) models.

RESULTS

The PLS-DA models effectively classified chemovars and major classes using only two latent variables (LVs) with minimal overfitting risk, with sensitivity, specificity, and accuracy values approaching 1. Despite the high water content in wet cannabis inflorescence, the PLS-R models demonstrated good to excellent predictive capabilities for nine cannabinoids and eight terpenes using FT-NIR spectra for the first time, achieving cross-validation and prediction R-squared values greater than 0.7, ratio of performance to interquartile range (RPIQ) exceeding 2, and a RMSECV/RMSEC ratio below 1.24. However, the low-cannabidiolic acid submodel and (-)-Δ9-trans-tetrahydrocannabinol model showed poor predictive performance. Some cannabinoid and terpene prediction models in wet cannabis inflorescence exhibited lower predictive capabilities compared with previously published models for dry cannabis inflorescence.

CONCLUSIONS

These findings suggest that FT-NIR spectroscopy can be a viable rapid on-site analytical tool for growers during the inflorescence flowering stage.

Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy

A rugged handheld sensor for rapid in-field classification of cannabis samples based on their THC content using ultra-compact near-infrared spectrometer technology is presented. The device is designed for use by the Austrian authorities to discriminate between legal and illegal cannabis samples directly at the place of intervention. Hence, the sensor allows direct measurement through commonly encountered transparent plastic packaging made from polypropylene or polyethylene without any sample preparation. The measurement time is below 20 s. Measured spectral data are evaluated using partial least squares discriminant analysis directly on the device's hardware, eliminating the need for internet connectivity for cloud computing. The classification result is visually indicated directly on the sensor via a colored LED. Validation of the sensor is performed on an independent data set acquired by non-expert users after a short introduction. Despite the challenging setting, the achieved classification accuracy is higher than 80%. Therefore, the handheld sensor has the potential to reduce the number of unnecessarily confiscated legal cannabis samples, which would lead to significant monetary savings for the authorities.

Non-Destructive Near-Infrared Technology for Efficient Cannabinoid Analysis in Cannabis Inflorescences

In the evolving field of cannabis research, scholars are exploring innovative methods to quantify cannabinoids rapidly and non-destructively. This study evaluates the effectiveness of a hand-held near-infrared (NIR) device for quantifying total cannabidiol (total CBD), total delta-9-tetrahydrocannabinol (total THC), and total cannabigerol (total CBG) in whole cannabis inflorescences. Employing pre-processing techniques, including standard normal variate (SNV) and Savitzky-Golay (SG) smoothing, we aim to optimize the portable NIR technology for rapid and non-destructive cannabinoid analysis. A partial least-squares regression (PLSR) model was utilized to predict cannabinoid concentration based on NIR spectra. The results indicated that SNV pre-processing exhibited superior performance in predicting total CBD concentration, yielding the lowest root mean square error of prediction (RMSEP) of 2.228 and the highest coefficient of determination for prediction (R2P) of 0.792. The ratio of performance to deviation (RPD) for total CBD was highest (2.195) with SNV. In contrast, raw data exhibited the least accurate predictions for total THC, with an R2P of 0.812, an RPD of 2.306, and an RMSEP of 1.651. Notably, total CBG prediction showed unique characteristics, with raw data yielding the highest R2P of 0.806. SNV pre-processing emerges as a robust method for precise total CBD quantification, offering valuable insights into the optimization of a hand-held NIR device for the rapid and non-destructive analysis of cannabinoid in whole inflorescence samples. These findings contribute to ongoing efforts in developing portable and efficient technologies for cannabinoid analysis, addressing the increasing demand for quick and accurate assessment methods in cannabis cultivation, pharmaceuticals, and regulatory compliance.

Stability, biofunctional, and antimicrobial characteristics of cannabidiol isolate for the design of topical formulations

Cannabidiol (CBD) is a high-value natural compound of Cannabis Sativa plant. It is a non-psychotropic phytocannabinoid, attracting significant attention as a multifunctional active ingredient for topical applications. Although it is demonstrated that CBD can be used for specific dermatological ailments, reliable data on functionalities are limited. The present study aimed to investigate the structural stability, biofunctionality, and antimicrobial characteristics of CBD isolate to assist in the design of various topical formulations. The stability of CBD in solid and solubilized states was assessed to establish storage and formulation conditions. The performance of CBD solubilized in organic and aqueous media was evaluated for free radical scavenging, tyrosinase, and collagenase enzyme inhibition, which showed good prospects for the ingredient. The antimicrobial activity of solubilized CBD was evaluated against Gram-negative (E. coli, P. aeruginosa), Gram-positive bacterial strains (S. aureus, S. epidermidis, C. acnes), and fungal strains (C. albicans, M. furfur) using agar well diffusion and broth microdilution methods. Due to the presence of surfactants in CBD aqueous solution, it displayed a lack of antimicrobial activity against all the tested microorganisms. CBD solubilized in an organic medium showed no activity against Gram-negative bacterial strains but higher activity against tested Gram-positive bacterial and fungal strains.

The progress of small molecules against cannabinoid 2 receptor (CB2R)

The two subtypes of cannabinoid receptors (CBR), namely CB1R and CB2R, belong to the G protein-coupled receptor (GPCR) superfamily and are confirmed as potential therapeutic targets for a variety of diseases such as inflammation, neuropathic pain, and immune-related disorders. Since CB1R is mainly distributed in the central nervous system (CNS), it could produce severe psychiatric adverse reactions and addiction. In contrast, CB2R are predominantly distributed in the peripheral immune system with minimal CNS-related side effects. Therefore, more attention has been devoted to the discovery of CB2R ligands. In view of the favorable profile of CB2R, many high-binding affinity and selectivity CB2R ligands have been developed recently. This paper reviews recent research progress on CB2R ligands, including endogenous CB2R ligands, natural compounds, and novel small molecules, in order to provide a reference for subsequent CB2R ligand development.

In Vitro Wound Healing Potential of a Fibroin Film Incorporating a Cannabidiol/2-Hydroxypropyl-β-cyclodextrin Complex

This study aimed to develop a film dressing prepared by incorporating a complex of cannabidiol and 2-hydroxypropyl-β-cyclodextrin (CBD/HP-β-CD) into a fibroin-based film and to investigate its wound healing capabilities. The fibroin from silkworm cocoons exhibited a total protein content of 96.34 ± 0.14% w/w and a molecular weight range of 25 to 245 kDa. Fourier-transform infrared spectroscopy (FTIR) revealed the presence of characteristic amide peaks (I, II, and III) in the isolated fibroin. The CBD/HP-β-CD complex, prepared with a molar ratio of 1:2 (CBD to HP-β-CD), had 81.5 ± 1.2% w/w CBD content, as determined by high-performance liquid chromatography (HPLC). X-ray diffraction (XRD) and FTIR analyses demonstrated successful encapsulation of CBD's hydrophobic aromatic rings by HP-β-CD. Blending the fibroin solution with the CBD/HP-β-CD complex produced a transparent, slightly yellowish film. Mechanical testing revealed a tensile strength of 48.67 ± 2.57 MPa and a % elongation at a break of 1.71 ± 0.21%. XRD and FTIR analyses showed distinctive crystalline and chemical structures of the film. In subsequent in vitro experiments with normal human dermal fibroblasts, the film demonstrated potential for wound healing. An increase in cell division (G2/M phase) was observed compared to the fibroin film without the CBD/HP-β-CD complex. Additionally, fibroblasts treated with the film exhibited enhanced cell migration in a scratch assay and increased expression of vascular endothelial growth factor protein compared to the control group. Overall, these findings underscore the film's potential for enhancing wound healing outcomes.

Classification of Black Mahlab seeds (Monechma ciliatum) using GC-MS and FT-NIR and simultaneous prediction of their major volatile compounds using chemometrics

The identification of geographical origin is an important factor in assessing the quality of aromatic and medicinal seeds such as Black Mahlab (Monechma ciliatum). However, at present, there are no studies concerning Black Mahlab Seeds (BMSs). To identify the geographical origin of BMSs, we have used gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-NIR) combined with chemometrics. Chemometrics analysis showed that FT-NIR and GC-MS can be used to discriminate the geographical origin of BMSs. FT-NIR coupled with the partial least squares regression (PLSR) was applied to develop the calibration models. The calibration models had a coefficient of determination (R_c²) of 0.82 for coumarin and 0.81 for methyl salicylate. The prediction model (R_p²) values ranged from 0.83 for coumarin to 0.77 for methyl salicylate. Overall, the chemometrics presented correct classification, and PLSR accurately predicted the volatiles, with an RMSEP range of 0.9 to 0.16 for the two volatiles targeted.

Novel fluorescence spectroscopy method coupled with N-PLS-R and PLS-DA models for the quantification of cannabinoids and the classification of cannabis cultivars

INTRODUCTION

Cannabis sativa L. inflorescences are rich in secondary metabolites, particularly cannabinoids. The most common techniques for elucidating cannabinoid composition are expensive technologies, such as high-pressure liquid chromatography (HPLC).

OBJECTIVES

We aimed to develop and evaluate the performance of a novel fluorescence spectroscopy-based method coupled with N-way partial least squares regression (N-PLS-R) and partial least squares discriminant analysis (PLS-DA) models to replace the expensive chromatographic methods for preharvest cannabinoid quantification.

METHODOLOGY

Fresh medicinal cannabis inflorescences were collected and ethanol extracts were prepared. Their excitation-emission spectra were measured using fluorescence spectroscopy and their cannabinoid contents were determined by HPLC-PDA. Subsequently, N-PLS-R and PLS-DA models were applied to the excitation-emission matrices (EEMs) for cannabinoid concentration prediction and cultivar classification, respectively.

RESULTS

The N-PLS-R model was based on a set of EEMs (n = 82) and provided good to excellent quantification of (-)-Δ9-trans-tetrahydrocannabinolic acid, cannabidiolic acid, cannabigerolic acid, cannabichromenic acid, and (-)-Δ9-trans-tetrahydrocannabinol (R² _CV and R² _pred  > 0.75; RPD > 2.3 and RPIQ > 3.5; RMSECV/RMSEC ratio < 1.4). The PLS-DA model enabled a clear distinction between the four major classes studied (sensitivity, specificity, and accuracy of the prediction sets were all ≥0.9).

CONCLUSIONS

The fluorescence spectral region (excitation 220-400 nm, emission 280-550 nm) harbors sufficient information for accurate prediction of cannabinoid contents and accurate classification using a relatively small data set.

Enhanced Skin Penetration of Cannabidiol Using Organosilane Particles as Transdermal Delivery Vehicles

There is potential for cannabidiol to act as an analgesic, anxiolytic and antipsychotic active ingredient; however, there is a need to find alternate administration routes to overcome its low oral bioavailability. In this work, we propose a new delivery vehicle based on encapsulation of cannabidiol within organosilica particles as drug delivery vehicles, which are subsequently incorporated within polyvinyl alcohol films. We investigated the long-term stability of the encapsulated cannabidiol, as well as its release rate, in a range of simulated fluids with different characterization techniques, including Fourier Transform Infrared (FT-IR) and High-performance Liquid Chromatography (HPLC). Finally, we determined the transdermal penetration in an ex vivo skin model. Our results show that cannabidiol is stable for up to 14 weeks within polyvinyl alcohol films at a range of temperatures and humidity. Release profiles are first-order, consistent with a mechanism involving diffusion of the cannabidiol (CBD) out of the silica matrix. The silica particles do not penetrate beyond the stratum corneum in the skin. However, cannabidiol penetration is enhanced and is detected in the lower epidermis, which was 0.41% of the total CBD in a PVA formulation compared with 0.27% for pure CBD. This is partly due to an improvement of its solubility profile as it is released from the silica particles, but we cannot rule out effects of the polyvinyl alcohol. Our design opens a route for new membrane technologies for cannabidiol and other cannabinoid products, where administration via non-oral or pulmonary routes can lead to better outcomes for patient cohorts in a range of therapeutics.

Use of near-infrared spectroscopy for the classification of medicinal cannabis cultivars and the prediction of their cannabinoid and terpene contents

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R2CV and R2pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R2CV > 0.7 and R2pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models.

FTIR and Raman Spectroscopic Characterization of Cannabinoids

Tetrahydrocannabinol (THC), cannabidiol (CBD) and cannabinol (CBN) are three key phytochemical components of cannabis. All three have demonstrated phytochemical activity and are implicated in pharmacological use of cannabis. In this paper, we present the FTIR and Raman spectroscopic characterization of THC, CBD and CBN compounds obtained from certified reference materials. Spontaneous Raman, mid-Infrared (MIR) absorption spectra as well as the analogous surface-enhanced counterparts (Surface enhanced Raman spectroscopy (SERS) and surface enhanced Infrared absorption (SEIRA)) of the cannabinoids are discussed in detail here. We have also examined the laser induced photothermal changes that occur in THC and CBD under spontaneous Raman acquisition conditions as revealed in their Raman spectra. Vibrational spectroscopy provides a robust, portable and cost effective analytical approach to quality control for various medicinal and consumer cannabinoid products. The pure compound spectra of the three cannabinoids presented in this work will help end-users to establish better quantitative analysis methods based on these techniques.

A unique approach for in-situ monitoring of the THCA decarboxylation reaction in solid state

The decarboxylation of Δ9-tetrahydrocannabinolic acid (THCA) plays pivotal role in the potency of medical cannabis and its extracts. Our present work aims to draw attention to mid-infrared (MIR) spectroscopy to in-situ monitor and decipher the THCA decarboxylation reaction in the solid state. The initial TG/DTG curves of THCA, for a first time, outlined the solid-solid decarboxylation dynamics, defined the endpoint of the process and the temperature of the maximal conversion rate, which aided in the design of the further IR experiment. Temperature controlled IR spectroscopy experiments were performed on both THCA standard and cannabis flower by providing detailed band assignment and conducting spectra-structure correlations, based on the concept of functional groups vibrations. Moreover, a multivariate statistical analysis was employed to address the spectral regions of utmost importance for the THCA → THC interconversion process. The principal component analysis model was reduced to two PCs, where PC1 explained 94.76% and 98.21% of the total spectral variations in the THCA standard and in the plant sample, respectively. The PC1 plot score of the THCA standard, as a function of the temperature, neatly complemented to the TG/DTG curves and enabled determination of rate constants for the decarboxylation reaction undertaken on several selected temperatures. The predictive capability of MIR was further demonstrated with PLS (R2X = 0.99, R2Y = 0.994 and Q2 = 0.992) using thermally treated flower samples that covered broad range of THCA/THC content. Consequently, a progress in elucidation of kinetic models of THCA decarboxylation in terms of fitting the experimental data for both, solid state standard substance and a plant flower, was achieved. The results open the horizon to promote an appropriate process analytical technology (PAT) in the outgrowing medical cannabis industry.

Analytical Techniques for Phytocannabinoid Profiling of Cannabis and Cannabis-Based Products-A Comprehensive Review

Cannabis is gaining increasing attention due to the high pharmacological potential and updated legislation authorizing multiple uses. The development of time- and cost-efficient analytical methods is of crucial importance for phytocannabinoid profiling. This review aims to capture the versatility of analytical methods for phytocannabinoid profiling of cannabis and cannabis-based products in the past four decades (1980-2021). The thorough overview of more than 220 scientific papers reporting different analytical techniques for phytocannabinoid profiling points out their respective advantages and drawbacks in terms of their complexity, duration, selectivity, sensitivity and robustness for their specific application, along with the most widely used sample preparation strategies. In particular, chromatographic and spectroscopic methods, are presented and discussed. Acquired knowledge of phytocannabinoid profile became extremely relevant and further enhanced chemotaxonomic classification, cultivation set-ups examination, association of medical and adverse health effects with potency and/or interplay of certain phytocannabinoids and other active constituents, quality control (QC), and stability studies, as well as development and harmonization of global quality standards. Further improvement in phytocannabinoid profiling should be focused on untargeted analysis using orthogonal analytical methods, which, joined with cheminformatics approaches for compound identification and MSLs, would lead to the identification of a multitude of new phytocannabinoids.

Application of a liquisolid technique to cannabis sativa extract compacts: Effect of liquid vehicles on the dissolution enhancement and stability of cannabinoids

This work describes the application of liquisolid technique to enhance cannabinoid dissolution from Cannabis sativa L. (CS) compacts. Effects of five vehicles, namely, volatile (ethanol) and nonvolatile (caprylocaproyl macrogolglycerides, polyethylene glycol 400, oleoyl macrogolglycerides and polysorbate 20) liquids, on tablet properties, dissolution and stability were investigated. The viscid oleoresin CS extract was mixed with vehicles before being transformed into free-flowing powder by the use of microcrystalline cellulose and colloidal silica as carrier and coating materials. Liquid vehicles had a nonsignificant effect on liquid load factor of CS extract. CS liquisolid compacts had acceptable tableting properties in terms of weight variation, friability, hardness, content uniformity and disintegration time. Different vehicles affected the hardness, disintegration, and wettability of CS compacts and thus the dissolution behaviors of cannabinoids to different extents. Dissolutions of cannabinoids from CS compacts were rate-limited by the disintegration process. Liquisolid formulations using nonvolatile liquids with low polarity or high hydrophilic-lipophilic balance yielded more than 90% cannabinoid dissolution. Stability studies revealed nonsignificant changes in tablet characteristics, cannabinoid content and dissolutions of CS compacts when stored at 5 ± 3 °C for 3 months. This work presents a general concept of how to successfully formulate CS extract with cannabinoid dissolution enhancement characteristics.

Discriminating different Cannabis sativa L. chemotypes using attenuated total reflectance - infrared (ATR-FTIR) spectroscopy: A proof of concept

An original, innovative, high-throughput method based on attenuated total reflectance - Fourier's transform infrared (ATR-FTIR) spectroscopy has been developed for the proof-of-concept discrimination of fibre-type from drug-type Cannabis sativa L. inflorescences. The cannabis sample is placed on the instrument plate and analysed without any previous sample pretreatment step. In this way, a complete analysis lasts just a few seconds, the time needed to record an ATR-FTIR spectrum. The method was calibrated and cross-validated using data provided by liquid chromatography - tandem mass spectrometry (LC-MS/MS) analysis of the different cannabis samples and carried out the statistical assays for quantitation. During cross-validation, complete agreement was obtained between ATR-FTIR and LC-MS/MS identification of the cannabis chemotype. Moreover, the method has proved to be capable of quantifying with excellent accuracy (75-103 % vs. LC-MS/MS) seven neutral and acidic cannabinoids (THC, THCA, CBD, CBDA, CBG, CBGA, CBN) in inflorescences from different sources. The extreme feasibility and speed of execution make this ATR-FTIR method highly attractive as a proof-of-concept for a possible application to quality controls during pharmaceutical product manufacturing, as well as on-the-street cannabis controls and user counselling.