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Spectroscopic techniques such as infrared spectroscopy and Raman spectroscopy are used for a long time in the context of the analysis of illicit drugs, and their use is increasing due to the development of more performant portable devices and easy application in the context of harm reduction through drug checking or onsite forensic analysis. Although these instruments are routinely used with a spectral library, the importance of chemometric techniques to extract relevant information and give a full characterisation of samples, especially in the context of adulteration, is increasing. This review gives an overview of the applications described in the context of the analysis of illicit drug products exploiting the advantages of the combination of spectroscopy with chemometrics. Next to an overview of the literature, the review also tries to emphasize the shortcomings of the presented research papers and to give an incentive to what is needed to include chemometrics as a part of the daily routine of drug checking services and mobile forensic applications.

The detection and quantification of additives in tobacco products are critical for ensuring consumer safety and compliance with regulatory standards. Traditional analytical techniques, like gas chromatography–mass spectrometry (GC–MS), liquid chromatography–mass spectrometry (LC–MS), and others, although effective, suffer from drawbacks, including complex sample preparation, high costs, lengthy analysis times, and the requirement for skilled operators. This study addresses these challenges by evaluating the efficacy of mid-infrared (MIR) spectroscopy and near-IR (NIR) spectroscopy, coupled with multivariate analysis, as potential solutions for the detection and quantification of additives in tobacco products. So, a representative set of tobacco products was selected and spiked with the targeted additives, namely caffeine, menthol, glycerol, and cocoa. Multivariate analysis of MIR and NIR spectra consisted of principal component analysis (PCA), hierarchical clustering analysis (HCA), partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) to classify samples based on targeted additives. Based on the unsupervised techniques (PCA and HCA), a distinction could be made between spiked and non-spiked samples for all four targeted additives based on both MIR and NIR spectral data. During supervised analysis, SIMCA achieved 87–100% classification accuracy for the different additives and for both spectroscopic techniques. PLS-DA models showed classification rates of 80% to 100%, also demonstrating robust performance. Regression studies, using PLS, showed that it is possible to effectively estimate the concentration levels of the targeted molecules. The results also highlight the necessity of optimizing data pretreatment for accurate quantification of the target additives. Overall, NIR spectroscopy combined with SIMCA provided the most accurate and robust classification models for all target molecules, indicating that it is the most effective single technique for this type of analysis. MIR, on the other hand, showed the overall best performance for quantitative estimation. [ABSTRACT FROM AUTHOR]

As cannabidiol (CBD) is not considered to be a drug and because of its potential health claims, it is an interesting compound that is often found in cosmetics. However, the safety of CBD, as well as the presence of trace amounts of other phytocannabinoids, including the psychoactive substance ∆9‐tetrahydrocannabinol (THC), is still being debated. A robust analytical technique capable of analysing cosmetic products and determining their phytocannabinoid content will be crucial in assessing the safety of these products. This systematic review aims to highlight the current analytical tools that could be used to analyse phytocannabinoids in cosmetics. The ideal method would be able to analyse high levels of CBD in combination with trace levels of THC and their acids. The method should provide good recoveries and accuracies in a variety of matrices while providing information on up‐coming phytocannabinoids such as cannabichromene (CBC), cannabigerol (CBG) and cannabinol (CBN). The systematic review approach was based on the Preferred Reporting Items for Systematic review and Meta‐Analyses method. The research focused on studies published from January 2010 to December 2022 in PubMed and Scopus. A total of 15 datasets met the inclusion and exclusion criteria and were tabulated to allow easy comparison. Although some of the reviewed methods can handle multiple matrices and provide satisfactory recoveries, this review process did not identify an ideal method. The most suitable methods either could not quantify phytocannabinoid acids or were not sensitive enough to quantify trace levels of psychoactive phytocannabinoids. [ABSTRACT FROM AUTHOR]

More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop‐in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4‐methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid‐infrared (MIR), near‐infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4‐methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances. [ABSTRACT FROM AUTHOR]

In 2019, a global viral pandemic, due to the SARS‐CoV‐2 virus, broke out. Soon after, the search for a vaccine and/or antiviral medicine began. One of the candidate antiviral medicines tested was ivermectin. Although several health authorities warned the public against the use of this medicine outside clinical trials, the drug was widely used at the end of 2020 and in 2021. Simultaneously, several reports started to emerge demonstrating serious adverse effects after self‐medicating with ivermectin. It stands to reason that the self‐administration of substandard or falsified (SF) medicines bearing harmful quality deficiencies have contributed to this phenomenon. In order to have a better view on the nature of these harmful quality deficiencies, SF ivermectin samples, intercepted in large quantities by the Belgian regulatory agencies during the period 2021–2022, were analyzed in our official medicines control laboratory. None of the samples (n = 19) were compliant to the quality criteria applicable to medicinal products. These SF products either suffered from a systematic underdosing of the active pharmaceutical ingredient or were severely contaminated with bacteria, two of which were contaminated with known pathogens that cause gastrointestinal illness upon oral intake. In addition to the direct risks of self‐medicating with such a product, the improper usage and dosage of ivermectin medication might also facilitate ivermectin tolerance or resistance in parasites. This may have detrimental consequences on a global scale, certainly as the number of newly developed active pharmaceutical ingredients that can safely be used to combat parasites is rather scarce. [ABSTRACT FROM AUTHOR]

Because of the increasing popularity of e-cigarettes, monitoring the e-cigarette market has become important for national health authorities to guarantee safety and quality. In the EU, the Tobacco Products Directive requires emission studies for e-cigarette products. The absence of industry guidelines for studying these emissions and the lack of proper validation in the literature led us to develop and validate a method using the total error approach for the determination of nicotine in e-cigarette aerosols. A commercial vaping device was used to generate aerosols, which were then collected on Cambridge filter pads and measured for nicotine concentration by UHPLC-DAD after extraction. The method was successfully validated by generating accuracy profiles, which show that the β-expectation tolerance intervals remained below the acceptance limits of ±20%. Within-run repeatability and intermediate precision were considered acceptable since the highest RSD value obtained was below 5%. The method was applied to 15 commercial e-liquids. A complete validation of a method for the analysis of e-cigarette emissions is presented, including several parameters that impact the accuracy and reproducibility. Similar systematic approaches for method development and validation could be used for other e-cigarette emission analysis methods to ensure the reliability of the measurements. [ABSTRACT FROM AUTHOR]

Introduction: For the majority of patients with acute myeloid leukemia (AML) an allogeneic stem cell transplant (SCT) in first complete remission (CR) is preferred. However, whether the number of courses required to achieve CR has a prognostic impact is unclear. It is unknown which factors remain important in patients requiring more than one course of induction to attain remission. Methods: This Acute Leukaemia Working Party study from the European Society for Blood and Marrow Transplantation identified adults who received an allograft in first CR from either a fully matched sibling or 10/10 or 9/10 human leucocyte antigen (HLA)‐matched unrelated donor (HLA‐A, HLA‐B, HLA‐C, HLA‐DR, or HLA‐DQ). Univariate and multivariate analyses were undertaken to identify the prognostic impact of one or two courses of induction to attain CR. Results: A total of 4995 patients were included with 3839 (77%) patients attaining a CR following one course of induction chemotherapy (IND1), and 1116 patients requiring two courses (IND2) to attain CR. IND2 as compared to IND1 was a poor prognostic factor in a univariate analysis and remained so in a multivariate Cox model, resulting in an increased hazard ratio of relapse (1.38; 95% confidence interval [CI], 1.16–1.64; p =.0003) and of death (1.27; 95% CI, 1.09–1.47; p =.002). Adverse prognostic factors in a multivariate analysis of the outcomes of patients requiring IND2 included age, FLT3‐ITD, adverse cytogenetics, and performance status. Pretransplant measurable residual disease retained a prognostic impact regardless of IND1 or IND2. Conclusion: Initial response to chemotherapy as determined by number of courses to attain CR, retained prognostic relevance even following SCT in CR. Patients requiring two courses of induction to attain complete remission (CR) have a higher incidence of relapse and inferior survival as compared to those who require one course. Pretransplant measurable residual disease remains important in predicting outcomes following an allogeneic stem cell transplant in those requiring two courses of induction to achieve CR. [ABSTRACT FROM AUTHOR]

The availability of cannabidiol (CBD) oil products has increased in recent years. No analytical controls are mandatory for these products leading to uncertainties about composition and quality. In this paper, a methodology was developed to identify the oil matrix and to estimate the CBD content in such samples, using mid‐infrared and near‐infrared spectroscopy. Different oils were selected based on the information labeled on products and were bought in food stores in order to create a sample set with a variety of matrices. These oils were spiked with CBD to obtain samples with CBD levels from 0% to 20%. The first part of the study was focused on the qualitative analysis of the oil matrix. A classification model, based on Soft Independent Modeling of Class Analogy, was build using the spiked oils to distinguish between the different oil matrices. For both spectroscopic techniques, the sensitivity, the specificity, the accuracy and the precision were equal to 100%. These models were applied to determine the oil matrix of seized samples. The second part of the study was focused on the quantitative estimation of CBD. After determination of CBD in seized samples using gas chromatography‐tandem mass spectrometry, partial least square regression (PLS‐R) models were built, one for each matrix in the sample set. Both techniques were able to classify unknown oily samples according to their matrix, and although only few samples were available to evaluate the PLS‐R models, the approach clearly showed promising results for the estimation of the CBD content in oil samples. [ABSTRACT FROM AUTHOR]