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Herbal products for smoking containing cannabidiol (CBD) are available as "low-tetrahydrocannabinol cannabis products" in most EU countries. In Belgium, Δ9-tetrahydrocannabinol (THC) content of these products must be less than 0.2% w/w, which is also the limit for agricultural hemp. For agricultural hemp, the official and only valid method for European regulators is gas-chromatography coupled to flame ionization detector (GC-FID). There is no such method, for smoking products. Many of these herbal for smoking products are analyzed as part of their quality control and have certificate of analysis. During surveillance by official labs, discrepancies were seen between the official results and the certificate of analysis. In this study, a GC-FID method based on the European method and an ultra-high-performance liquid chromatography coupled to diode array detection (UHPLC-DAD) method were validated and applied for samples analysis in order to investigate these discrepancies. The GC-FID method shows better results for the validation parameters; notably, it has β-expectation tolerance limits within 10% with a β value of 95% while the validated UHPLC-DAD method has β-expectation tolerance limits within 15% with a β value of 90%. Furthermore, the other parameters evaluated are generally better with the GC-FID method. The statistic t test shows that the difference between both methods was significantly different for total-THC, but not significantly different for the total-CBD. The authors state that, as for agricultural hemp, the GC-FID method is to be preferred for the analysis of THC and CBD in products for smoking.

Introduction Since its introduction, the e-cigarette has become a commonly used consumer product. In this study, we investigate whether regulatory changes had an impact on the quality of refill liquids (e-liquids) available on the Belgian market through analysis of their chemical composition. Hence, the nicotine concentration accuracy was investigated in samples before, during and after the implementation of the revised Tobacco Product Directive (TPD) as an indicator of good manufacturing practices. This is, however, not enough to assure the quality. Therefore, extra criteria were also assessed based on TPD requirements. Methods By using in-house validated methods, a total of 246 e-liquids purchased prior (2013–2015), during (2016) and after (2017–2018) the implementation of the TPD revisions, were analyzed for the presence of nicotine, nicotine-related impurities, volatile organic compounds (VOCs), caffeine and taurine, and the flavors diacetyl and acetylpropionyl. Results Although not all manufacturers managed to produce and label their products accurately, nicotine labeling discrepancies have decreased over time. Moreover, also the number of e-liquids, containing high-risk VOCs (10% in 2016 vs. none of the samples in 2017–2018), caffeine (16% in 2017 vs. 5% in 2018), and diacetyl and acetylpropionyl (50% in 2017 vs. 27% in 2018 of sweet-flavored samples) diminished over time. Conclusion Our results demonstrate that the overall quality of the e-liquids has improved after the implementation of the revised TPD. However, the results also show that periodic quality control might be required to ensure further compliance to the TPD. Implications This study clearly demonstrates that the implementation of the revised TPD has improved the quality of the e-liquids on the Belgian market. However, there are still e-liquids that are not in agreement with the TPD due to nicotine concentration label discrepancies, presence of e-liquid impurities and controversial flavors diacetyl and acetylpropionyl or the additive caffeine.

The electronic cigarette (e-cigarette) has emerged as a popular alternative to the traditional hazardous tobacco cigarette. The substantial increase in e-cigarette use also urgently calls for controlling the quality of e-cigarette refill liquid products (e-liquids). Currently, the most important quality indicator of e-liquid products is the quantification of nicotine and its related impurities. Although different methods have been published to measure nicotine and impurity levels, the majority of them use a targeted LC-MS/MS approach. There is, however, a need for more robust quantification methods that are easy to implement in most control (industrial and governmental) laboratories. Therefore, in this study, a simple dilute-and-shoot UHPLC-DAD method has been developed and validated for the simultaneous quantification of nicotine and its alkaloid impurities in electronic cigarette refills. An optimal separation of the alkaloids was achieved in a runtime of 11 min. The method was successfully validated using the “total error” approach in accordance with the validation requirements of ISO-17025. During this validation, interference between the target components and a number of popular flavouring compounds such as vanillin, maltol, ethylacetate, etc. could be excluded. In addition, small changes to the column temperature, pH and molar concentration of the mobile phase buffer were deliberately introduced in order to assess the robustness of the method. Only a slightly different outcome between the newly developed UV-detection method and the targeted MS approach was found, due to the sensitivity of the different detection techniques. However, in the context of quality control of nicotine related impurities, for which the European Pharmacopoeia limits are currently applied, the sensitivity of the UHPLC-DAD method was found to be within the acceptable range. Despite the somewhat lower selectivity of the newly developed UV-detection technique versus a targeted LC-MS/MS approach, it may be concluded that this method is a suitable alternative for quality control purposes.

The use of e-cigarettes as alternative for tobacco cigarettes has become increasingly popular, even though their safety has not yet been scientifically established. One of the frequently raised concerns is the potential toxicity of certain flavours present in the e-liquids, such as diacetyl and acetylpropionyl. It is therefore important to be able to identify and quantify both compounds. Numerous analytical methods have been published for determining e-liquid compositions, but concerns exist with respect to the lack of analytical evaluation. Hence in this study, a new HS/GC-MS-based method was developed for the screening and quantification of diacetyl and acetylpropionyl in e-liquids. This method was fully validated using the 'total error' approach. The LOQ of the analytical method was 5ppm for diacetyl and acetylpropionyl. The obtained accuracy profiles show that the β-expectation tolerance intervals did not exceed the acceptance limits of±10%, meaning that 95% of future measurements will be included in the [-10%, 10%] bias limits. As proof of applicability, the validated method was successfully applied on a small set of e-liquid samples, indicating that this methodology could be used for routine quality control analyses of e-liquids.

E-cigarettes have become very popular, a trend that has been stimulated by the wide variety of available e-liquid flavours. Considering the large number of e-liquid flavours (>7000), there is an urgent need to establish a screening strategy to prioritize the flavouring substances of highest concern for human health. In the present study, a prioritization strategy combining analytical screening, in silico tools and literature data was developed to identify potentially genotoxic e-liquid flavourings. Based on the analysis of 129 e-liquids collected on the Belgian market, 60 flavourings with positive in silico predictions for genotoxicity were identified. By using literature data, genotoxicity was excluded for 33 of them whereas for 5, i.e. estragole, safrole, 2-furylmethylketon, 2,5-dimethyl-4-hydroxyl-3(2H)-furanone and transhexanal, there was a clear concern for in vivo genotoxicity. A selection of 4 out of the remaining 22 flavourings was tested in two in vitro genotoxicity assays. Three out of the four tested flavourings induced gene mutations and chromosome damage in vitro, whereas equivocal results were obtained for the fourth compound. Thus, although there is a legislative framework which excludes the use of CMR compounds in e-liquids, flavourings of genotoxic concern are present and might pose a health risk for e-cigarette users.

In a few countries, including Belgium, nicotine-containing e-cigarettes and e-liquids are considered medicines, and therefore cannot freely be sold, but should be distributed in a pharmacy. The fact that in the neighbouring countries these products are freely available, poses a problem for custom personnel, the more the nicotine content of the products is not always labelled, especially when they are bought through internet. Therefore there is a need for easy-to-use equipment and methods to perform a first on site screening of intercepted samples, both for border control as to check label compliance of the sample. The use of attenuated total reflectance-infrared spectroscopy (ATR-IR) and near infrared spectroscopy (NIR), combined with chemometrics was evaluated for the discrimination between nicotine containing and non-nicotine containing samples. It could be concluded that both ATR-IR and NIR could be used for the discrimination when combined with the appropriate chemometric techniques. The presented techniques do not need sample preparation and result in models with a minimum of false negative samples. If a large enough training set can be established the interpretation can be fully automated, making the presented approach suitable for on-site screening of e-liquid samples.

Upon original publication, this article contained a typographical error, which could lead to confusion in the results related to the number of diacetyl/acteylpropionyl samples and thus which might affect the academic accuracy of published information. During the compilation of the Figure, internal review led to a change in the total number of investigated sweet samples. These changes to the abstract, results, and discussion sections have since been corrected. The changes are as follows: In the Abstract, “Moreover, also the number of e-liquids, containing high-risk VOCs (10% in 2016 vs. none of the samples in 2017–2018), caffeine (16% in 2017 vs. 5% in 2018), and diacetyl and acetylpropionyl (55% in 2017 vs. 27% in 2018 of sweet-flavored samples) diminished over time” became “Moreover, also the number of e-liquids, containing high-risk VOCs (10% in 2016 vs. none of the samples in 2017–2018), caffeine (16% in 2017 vs. 5% in 2018), and diacetyl and acetylpropionyl (50% in 2017 vs. 27% in 2018 of sweet-flavored samples) diminished over time.” In the Results section under the subheading Harmful ingredients: Diacetyl and Acetylpropionyl, “The amount of diacetyl and acetylpropionyl, putatively present in 56 sweet-flavored e-liquids (2016–2018), was assessed by HS-GC-MS” became “The amount of diacetyl and acetylpropionyl, putatively present in 40 sweet-flavored e-liquids (2016–2018), was assessed by HS-GC-MS.” In the Discussion section, “Compared to our study, we found that in 2017, nine samples out of the 26 sweet-flavored e-liquids (25%) were either positive for DA, AP or both, while in 2018 this was the case for 6 out of 30 sweet-flavored samples (20%)” became “Compared to our study, we found that in 2017, nine samples out of the 18 sweet-flavored e-liquids (50%) were either positive for DA, AP or both, while in 2018 this was the case for six out of 22 sweetflavored samples (27%)”.

With the recent successes of biopharmaceuticals, new bioanalytical tools are needed for the functional quality characterization of new biological entities and biosimilars towards marketing authorization approval and during the product life. Biosensors are emerging technologies in the pharmaceutical field in drug discovery, development and Quality Control (QC) stages; however, they are not yet included in any pharmacopoeia. Surface acoustic wave (SAW) biosensors allow the user to detect and quantify binding events, giving information not only on affinity (KD) and kinetics (kon and koff), but also on viscoelastic effects. We present here an analytical quality by design (aQbD) based approach using somatropin (rhGH, recombinant human growth hormone) and derivatives as model biotechnological drugs and an antibody interaction partner to evaluate the functional quality. Using techniques described in ICH Q2, Q5 and Q8–11, we evaluated the performance of this SAW biosensor technique from a pharmaceutical quality point of view. CMAs (Critical Method Attributes) such as sensitivity, selectivity and variability are evaluated as a function of different experimental variables using DoEs (design of experiments). We suggest qualification tests as well as SSTs (system suitability tests), as required by the pharmaceutical competent authorities and recommend the inclusion of biosensor techniques into the different pharmacopoeia and pharmaceutical guidelines.

During the past decade, e-cigarettes have become increasingly popular. To guarantee their safe use and to comply with the notification requirements of the EU Tobacco Product Directive, the EU member state regulatory authorities need information about the exact composition of the e-liquids and their emissions. However, one of the challenges encountered during the analysis of e-liquids is the presence of the highly abundant e-liquid matrix components propylene glycol and glycerol. In this study, headspace gas chromatography (HS-GC) analysis is presented as an excellent method for the analysis of high volatile components in e-liquids. For the analysis of semivolatile ingredients, an additional sample preparation step is proposed based on a liquid–liquid extraction (LLE) followed by a freeze-out of the matrix components. The developed method was successfully validated in accordance with the validation requirements of ICH guidelines for the quantification of four flavourings with a potential health concern for e-cigarette users.