Combining attenuated total reflectance- infrared spectroscopy and chemometrics for the identification and the dosage estimation of MDMA tablets

A compact Fourier-transform near-infrared spectrophotometer and chemometrics for characterizing a comprehensive set of seized ecstasy samples

A comprehensive data set of ecstasy samples containing MDMA (N-methyl-3,4-methylenedioxyamphetamine) and MDA (3,4-methylenedioxyamphetamine) seized by the Brazilian Federal Police was characterized using spectral data obtained by a compact, low-cost, near-infrared Fourier-transform based spectrophotometer. Qualitative and quantitative characterization was accomplished using soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA) classification, discriminating partial least square (PLS-DA), and regression models based on partial least square (PLS). By applying chemometric analysis, a protocol can be proposed for the in-field screening of seized ecstasy samples. The validation led to an efficiency superior to 96 % for ecstasy classification and estimating total actives, MDMA, and MDA content in the samples with a root mean square error of validation of 4.4, 4.2, and 2.7 % (m/m), respectively. The feasibility and drawbacks of the NIR technology applied to ecstasy characterization and the compromise between false positives and false negatives rate achieved by the classification models are discussed and a new approach to improve the classification robustness was proposed considering the forensic context.

Full Characterisation of Heroin Samples Using Infrared Spectroscopy and Multivariate Calibration

The analysis of heroin samples, before use in the protected environment of user centra, could be a supplementary service in the context of harm reduction. Infrared spectroscopy hyphenated with multivariate calibration could be a valuable asset in this context, and therefore 125 heroin samples were collected directly from users and analysed with classical chromatographic techniques. Further, Mid-Infrared spectra were collected for all samples, to be used in Partial Least Squares (PLS) modelling, in order to obtain qualitative and quantitative models based on real live samples. The approach showed that it was possible to identify and quantify heroin in the samples based on the collected spectral data and PLS modelling. These models were able to identify heroin correctly for 96% of the samples of the external test set with precision, specificity and sensitivity values of 100.0, 75.0 and 95.5%, respectively. For regression, a root mean squared error of prediction (RMSEP) of 0.04 was obtained, pointing at good predictive properties. Furthermore, during mass spectrometric screening, 10 different adulterants and impurities were encountered. Using the spectral data to model the presence of each of these resulted in performant models for seven of them. All models showed promising correct-classification rates (between 92 and 96%) and good values for sensitivity, specificity and precision. For codeine and morphine, the models were not satisfactory, probably due to the low concentration of these impurities as a consequence of acetylation. For methacetin, the approach failed.

Headspace solid-phase microextraction - gas chromatography - mass spectrometry qualitative screening method for active compounds, adulterants and impurities in ecstasy tablets seized in Northern Santa Catarina State, Brazil

The present work describes the development of a headspace solid-phase microextraction (HS-SPME) followed by gas chromatography - mass spectrometry (GC-MS) method for the qualitative analysis of compounds in seized ecstasy tablets that can be easily implemented in regular laboratories. HS-SPME with a DVB/CAR/PDMS 50/30 µm fiber was used to extract the ecstasy pills' components, including major and minor ones, in a single extraction/chromatographic run. For HS-SPME, the incubation time (0 min to 30 min), the extraction time (10 min to 40 min) and temperature (40 °C to 80 ºC), the buffer volume (3 mL to 8 mL), the buffer pH (6 to 9) and the NaCl concentration (0 mol/L to 6 mol/L) were evaluated using fractional factorial design. Different split ratios and detector voltages were also evaluated. The optimal compromise between sensitivity and peak resolution was found to be incubation and extraction at 65 ºC for 10 min and 25 min, respectively, 3 mL of pH 9 buffer containing 3 mol/L NaCl, using 40.0 mg of the powdered samples in a 15-mL amber glass vial, and an injection with a split ratio of 1:10 at 260 ºC for 10 min. Under optimal conditions, 44 samples from different seizures were analyzed. Seventy-five compounds were tentatively identified by the proposed method, including active substances, medicines, caffeine, safrole derivatives, synthesis intermediates and solvent residues. The number of tentatively identified compounds per sample varied from 8 to 24, with a mean of 15. Important findings in ecstasy samples, such as norcinamolaurin, α-methyl-1,3-benzodioxole-5-propanamide, α-methyl-3,4-methylenedioxyphenylpropionitrile, acetylsalicylic acid, piperonylonitrile, methyl isobutyl ketone, mesitylene, and 4-[3-(dimethylamino)propyl]- 2,6-dimethylphenol, identified with a frequency higher than 10%, are not found in the literature so far. The method precision, based on relative standard deviation of peak areas, ranged from 5% to 15%, depending on the compound. The method was shown to be simple, relatively fast, precise and a powerful tool for the identification of major and minor components in ecstasy tablets in a single analytical cycle, being useful for screening or quantitative purposes, if authentic standards are available.

Surface Analysis Techniques in Forensic Science: Successes, Challenges, and Opportunities for Operational Deployment

Surface analysis techniques have rapidly evolved in the last decade. Some of these are already routinely used in forensics, such as for the detection of gunshot residue or for glass analysis. Some surface analysis approaches are attractive for their portability to the crime scene. Others can be very helpful in forensic laboratories owing to their high spatial resolution, analyte coverage, speed, and specificity. Despite this, many proposed applications of the techniques have not yet led to operational deployment. Here, we explore the application of these techniques to the most important traces commonly found in forensic casework. We highlight where there is potential to add value and outline the progress that is needed to achieve operational deployment. We consider within the scope of this review surface mass spectrometry, surface spectroscopy, and surface X-ray spectrometry. We show how these tools show great promise for the analysis of fingerprints, hair, drugs, explosives, and microtraces.

Applications of NIR spectroscopy and chemometrics to illicit drug analysis: An example from inhalant drug screening tests

The "loló" stands out among the most used inhalant drugs in Brazil. This drug is a non-specific blend of organic solvents, traditionally composed of ether and chloroform. Reports in the literature and forensic practice have revealed changes in the composition profile of this drug, based on availability of acquisition. This diversity has an effect on the efficiency of the preliminary tests used to detect illicit substances in situations that require rapid response time from the criminal investigations, such as arrests in the act. Considering the diversity of volatile substances with potential use as inhalant drugs and the limited detection abilities of preliminary exams routinely used by forensic laboratories, this present work applied NIR spectroscopy associated with chemometric models to detect the presence of organic solvents in samples of "loló". Initially, the chemical profile of the seized samples was surveyed in the geographic region of study (Paraiba State, Brazilian northeast), and from the observation of the prevalent substances, classification models were produced using samples made in the laboratory and samples from real apprehensions. Then, an analysis protocol was developed, based on SIMCA models, to detect the predominant solvents in the regional composition profile (dichloromethane, trichloroethene and chloroform). The proposed analysis protocol obtained an overall accuracy of 94.7% in detecting halogenated hydrocarbons in suspect samples and 100% accuracy in characterizing the composition of samples composed exclusively of the studied halogenated hydrocarbons and their binary mixtures. Considering that the colorimetric tests used in the routine of forensic laboratories do not detect many components, the proposed method was technically and economically viable in preliminary tests for samples seized as suspicious of being "loló".

Comparison of Spectroscopic Techniques Combined with Chemometrics for Cocaine Powder Analysis

Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.

An infrared spectroscopic approach to characterise white powders, easily applicable in the context of drug checking, drug prevention and on-site analysis

More and more events, such as the summer music festivals, are considering the possibilities for implementing on-site testing of psychoactive drugs in the context of prevention and harm reduction. Although the on-site identification is already implemented by plenty of drug checking services, the required rapid quantitative dosing of the composition of illicit substances is still a missing aspect for a successful harm reduction strategy at events. In this paper, an approach is presented to identify white powders as amphetamine, cocaine, ketamine or others and to estimate the purity of the amphetamine, cocaine and ketamine samples using spectroscopic techniques hyphenated with partial least squares (PLS) modelling. For identification purposes, it was observed that mid-infrared spectroscopy hyphenated with PLS-discriminant analysis allowed the distinction between amphetamine, cocaine, ketamine and other samples and this with a correct classification rate of 93.1% for an external test set. For quantitative estimation, near-infrared spectroscopy was more performant and allowed the estimation of the dosage/purity of the amphetamine, cocaine and ketamine samples with an error of more or less 10% w/w. An easily applicable, practical and cost-effective approach for on-site characterisation of the majority of the psychoactive samples encountered in Belgian nightlife settings based on IR spectroscopy was proposed.

A near-infrared spectroscopy-based end-point determination method for the blending process of Dahuang soda tablets

OBJECTIVES

This study is aimed to explore the blending process of Dahuang soda tablets. These are composed of two active pharmaceutical ingredients (APIs, emodin and emodin methyl ether) and four kinds of excipients (sodium bicarbonate, starch, sucrose, and magnesium stearate). Also, the objective is to develop a more robust model to determine the blending end-point.

METHODS

Qualitative and quantitative methods based on near-infrared (NIR) spectroscopy were established to monitor the homogeneity of the powder during the blending process. A calibration set consisting of samples from 15 batches was used to develop two types of calibration models with the partial least squares regression (PLSR) method to explore the influence of density on the model robustness. The principal component analysis-moving block standard deviation (PCA-MBSD) method was used for the end-point determination of the blending with the process spectra.

RESULTS

The model with different densities showed better prediction performance and robustness than the model with fixed powder density. In addition, the blending end-points of APIs and excipients were inconsistent because of the differences in the physical properties and chemical contents among the materials of the design batches. For the complex systems of multi-components, using the PCA-MBSD method to determine the blending end-point of each component is difficult. In these conditions, a quantitative method is a more suitable alternative.

CONCLUSIONS

Our results demonstrated that the effect of density plays an important role in improving the performance of the model, and a robust modeling method has been developed.

Interpol review of controlled substances 2016-2019

This review paper covers the forensic-relevant literature in controlled substances from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.