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The aim of the present study was to explore the feasibility of applying near-infrared (NIR) spectroscopy for the quantitative analysis of Δ 9 -tetrahydrocannabinol (THC) in cannabis products using handheld devices. A preliminary study was conducted on different physical forms (entire, ground and sieved) of cannabis inflorescences in order to evaluate the impact of sample homogeneity on THC content predictions. Since entire cannabis inflorescences represent the most common types of samples found in both the pharmaceutical and illicit markets, they have been considered priority analytical targets. Two handheld NIR spectrophotometers (a low-cost device and a mid-cost device) were used to perform the analyses and their predictive performance was compared. Six partial least square (PLS) models based on reference data obtained by UHPLC-UV were built. The importance of the technical features of the spectrophotometer for quantitative applications was highlighted. The mid-cost system outperformed the low-cost system in terms of predictive performance, especially when analyzing entire cannabis inflorescences. In contrast, for the more homogeneous forms, the results were comparable. The mid-cost system was selected as the best-suited spectrophotometer for this application. The number of cannabis inflorescence samples was augmented with new real samples, and a chemometric model based on machine learning ensemble algorithms was developed to predict the concentration of THC in those samples. Good predictive performance was obtained with a root mean squared error of prediction of 1.75 % (w/w). The Bland-Altman method was then used to compare the NIR predictions to the quantitative results obtained by UHPLC-UV and to evaluate the degree of accordance between the two analytical techniques. Each result fell within the established limits of agreement, demonstrating the feasibility of this chemometric model for analytical purposes. Finally, resin samples were investigated by both NIR devices. Two PLS models were built by using a sample set of 45 samples. When the analytical performances were compared, the mid-cost spectrophotometer significantly outperformed the low-cost device for prediction accuracy and reproducibility., Competing Interests: Declaration of Competing Interest The authors report no declarations of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Cannabidiol (CBD) and Δ 9 -tetrahydrocannabinol (Δ 9 -THC) are considered as the most interesting cannabinoids in Cannabis sativa L. for the clinical practice. Since 2013, the Italian law allows pharmacists to prepare and dispense cannabis extracts to patients under medical prescription, and requires the evaluation of CBD and Δ 9 -THC content in cannabis extracts before sale. Cannabis olive oil extracts are prepared from dried female cannabis inflorescences, but a standard protocol is still missing. In this study, a fast RP-HPLC/UV method has been developed to quantify CBD and Δ 9 -THC in cannabis olive oil extracts. The analytical quality by design strategy has been applied to the method development, setting critical resolution and total analysis time as critical method attributes (CMAs), and selecting column temperature, buffer pH and flow rate as critical method parameters. Information from Doehlert Design in response surface methodology combined to Monte-Carlo simulations led to draw the risk of failure maps and to identify the method operable design region. The method was validated according to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines and then implemented in routine analysis. A control strategy based on system control charts was planned to monitor the developed method performances. Evaluation data were recorded over a period of one year of routine use, and both the CMAs showed values within the specifications in every analysis performed. Hence, a new risk evaluation for the future performances of the method was achieved by using a Bayesian approach based on the routine use data, computing the future distribution of the two CMAs. Finally, a study focusing on the monitoring of CBD and Δ 9 -THC concentrations in cannabis olive oil extracts was carried out. The developed method was applied to 459 extracts. The statistical analysis of the obtained results highlighted a wide variability in terms of concentrations among different samples from the same starting typology of cannabis, underlining the compelling need of a standardised procedure to harmonise the preparation of the extracts., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Pharmaceutical regulatory bodies increasingly require the implementation of systematic approaches in pharmaceutical product development. Quality control methods play a key role in the control strategy of drugs manufacturing to assure their quality. A risk-based approach in the analytical method development is strongly recommended to ensure that the method performances fit the purpose of the method during its entire life-cycle. In the last decade, analytical quality by design (AQbD), as risk management oriented methodology, has been progressively integrated with method development for fulfilling this objective. This approach has successfully allowed the quality to be designed into the analytical processes by obtaining a deep understanding of the procedures. In this paper the AQbD workflow and its application in the development of methods to be used for pharmaceutical quality control have been treated and discussed. Recent publications regarding how AQbD has been applied in separation techniques were reviewed. The different development strategies have been also showcased, highlighting their advantages and disadvantages, in order to give a useful overview., (Copyright © 2018 Elsevier B.V. All rights reserved.)