Nondestructive Direct Determination of Heroin in Seized Illicit Street Drugs by Diffuse Reflectance near-Infrared Spectroscopy

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.

How new nanotechnologies are changing the opioid analysis scenery? A comparison with classical analytical methods

Opioids such as heroin, fentanyl, raw opium, and morphine have become a serious threat to the world population in the recent past, due to their increasing use and abuse. The detection of these drugs in biological samples is usually carried out by spectroscopic and/or chromatographic techniques, but the need for quick, sensitive, selective, and low-cost new analytical tools has pushed the development of new methods based on selective nanosensors, able to meet these requirements. Modern sensors, which utilize "next-generation" technologies like nanotechnology, have revolutionized drug detection methods, due to easiness of use, their low cost, and their high sensitivity and reliability, allowing the detection of opioids at trace levels in raw, pharmaceutical, and biological samples (e.g. blood, urine, saliva, and other biological fluids). The peculiar characteristics of these sensors not only have allowed on-site analyses (in the field, at the crime scene, etc.) but also they are nowadays replacing the gold standard analytical methods in the laboratory, even if a proper method validation is still required. This paper reviews advances in the field of nanotechnology and nanosensors for the detection of commonly abused opioids both prescribed (i.e. codeine and morphine) and illegal narcotics (i.e. heroin and fentanyl analogues).

A green methodology for the determination of cocaine in camouflaged samples

A methodology based on the ultrasound-assisted extraction with ethanol and the dry film attenuated total reflectance infrared spectroscopy (DF-ATR-FTIR) measurement of extracts has been developed for a fast evaluation of non-conventional ("exotic") solid-sized cocaine samples. The method provides quantitative results in less than three minutes with a limit of detection in the solid sample of 1.6 μg g-1 of cocaine with a variation coefficient lower than 7%. Results found for seized samples of different natures were compared with those obtained by a reference gas chromatography method and the greenness of the whole proposed procedure was evaluated and compared using the analytical eco-scale, green analytical procedure index (GAPI), and analytical greenness metric (AGREE). The green evaluation of the proposed methodology provided green scores by considering different evaluation criteria.

On-site forensic analysis of colored seized materials: Detection of brown heroin and MDMA-tablets by a portable NIR spectrometer

The increasing workload for forensic laboratories and the expanding complexity of the drug market necessitates efficient approaches to detect drugs of abuse. Identification directly at the scene of crime enables investigative forces to make rapid decisions. Additionally, on-site identification of the material also leads to considerable efficiency and cost benefits. As such, paperwork, transportation, and time-consuming analysis in a laboratory may be avoided. Near-infrared (NIR) spectroscopy is an analysis technique suitable for rapid drug testing using portable equipment. A possible limitation of spectroscopic analysis concerns the complexity of seized materials. NIR measurements represent composite spectra for mixtures and diagnostic spectral features can be obscured by excipients such as colorants. Herein, a NIR-based (1300-2600 nm) detection of heroin and MDMA in colored casework (i.e., brown powders and ecstasy tablets) using a portable analyzer is presented. The application includes a multistage data analysis model based on the net analyte signal (NAS) approach. This identification model was specifically designed for mixture analysis and requires a limited set of pure reference spectra only. Consequently, model calibration efforts are reduced to a minimum. A total of 549 forensic samples was tested comprising brown heroine samples and a variety of colored tablets with different active ingredients. This investigation led to a >99% true negative and >93% true positive rate for heroin and MDMA. These results show that accurate on-site detection in colored casework is possible using NIR spectroscopy combined with an efficient data analysis model. These findings may eventually help in the transition of routine forensic laboratories from laboratory-based techniques to portable equipment operated on scene.

Non-Destructive Analysis of Chlorpheniramine Maleate Tablets and Granules by Chemometrics-Assisted Attenuated Total Reflectance Infrared Spectroscopy

Non-destructive analysis of chlorpheniramine maleate (CPM), pharmaceutical tablets, and granules was conducted by chemometrics-assisted attenuated total reflectance infrared spectroscopy (ATR-IR). For tablets, an optimum PLSR model with eight latent factors was obtained from area-normalized and standard normal variate (SNV) pretreated ATR-IR spectral data with correlation coefficients (R²) of calibration and cross-validation of 0.9716 and 0.9602, respectively. The model capability for the 42 test set samples was proven with R² between the reference and model prediction values of 0.9632, and a root-mean-square error of prediction (RMSEP) of 1.7786. The successive PLSR model for granules was constructed from SNV and first derivative pretreated ATR-IR spectral data with two latent factors and correlation coefficients (R²) of calibration and cross-validation of 0.9577 and 0.9450, respectively.

Illicit drugs street samples and their cutting agents. The result of the GC-MS based profiling define the guidelines for sensors development

In this work, we have focused on the profiling of 5647 street samples covering marijuana, common and new recreational illicit drugs. All samples were analyzed using gas chromatography-mass spectrometry (GC-MS) technique. In total we have identified 53 illicit drugs with Δ-9-tetrahydrocannabinol (THC), amphetamine, N-ethylhexedrone, 3,4-methylenedioxy methamphetamine (MDMA), 4-chloromethcathinone (4-CMC), α-pyrrolidinoisohexaphenone (α-PHiP), cocaine, and 4-chloroethcathinone (4-CEC) being most commonly found and making 38.5, 17.8, 15.5, 8.0, 3.5, 2.7, 2.1, and 2.0% of the total studied pool, respectively. Except for methadone, all analyzed street samples were spiked with at least one cutting agent. Caffeine was the most frequently found adulterating addition present in around 33% (excluding marijuana) of the analyzed samples. Other identified cutting agents make an impressive group of more than 160 compounds. Finally, we have tabulated, illustrated, and discussed presented data in a view of smart and portable sensors development.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

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.

Direct and rapid characterization of illicit drugs in adulterated samples using thermal desorption electrospray ionization mass spectrometry

Foods and drinks have been adulterated with illicit drugs to facilitate criminal activities. Unfortunately, conventional analytical methods are incapable of rapidly characterizing these drugs in samples, as serious interferences from sample matrices must be removed through tedious and time-consuming pretreatment. Ambient ionization mass spectrometry (AMS) generally does not require sample pretreatment and is thus a suitable tool for directly and rapidly detecting illicit drugs in samples in different physical states. In this study, thermal desorption electrospray ionization mass spectrometry (TD-ESI/MS), an AMS technique, was utilized to efficiently characterize illicit drugs spiked in samples including drinks, powders, and jelly candies. To perform sensitive analysis, the mass analyzer was operated in multiple reaction monitoring mode to monitor the molecular and fragment ions of the target analytes. The time required to complete a typical TD-ESI/MS analysis was less than 30 s. The limits of detection (LODs) for illicit drugs were found to be 100 ppb in drinks, 100–1000 ppb in instant powders, and 1.3–6.5 ng/mm² on stamp surfaces. FM2 and nitrazepam laced in the inner layer of a jelly candy were detected by TD-ESI/MS, showcasing the advantage of the technique for direct and rapid analysis as opposed to conventional methods.

Rapid qualitative and quantitative analysis of methamphetamine, ketamine, heroin, and cocaine by near-infrared spectroscopy

Rapid and nondestructive near infrared spectroscopy (NIR) methods have been developed for simultaneous qualitative and quantitative analysis of methamphetamine, ketamine, heroin, and cocaine in seized samples. This is the first systematic report regarding a qualitative and quantitative procedure of applying NIR for drug analysis. A total of 282 calibration samples and 836 prediction samples were used for the building and validating of qualitative and quantitative models. Two qualitative analysis modeling methods for soft independent modeling by class analogy (SIMCA) and supporting vector machine (SVM) were compared. From its excellent performance in rejecting false positive results, SIMCA was chosen. The drug concentrations in the calibration and validation sample sets were analyzed using high-performance liquid chromatography. Based on the use of first-order derivative spectral data after standard normal variate (SNV) transformation correction, in the wavelength range from 10,000 to 4000cm^-1, four partial least squares quantitative-analysis models were built. The coefficients of determination for all calibration models were >99.3, and the RMSEC, RMSECV, and RMSEP were all less than 1.6, 2.9, and 3.6%, respectively. The results obtained here indicated that NIR with chemometric methods was accurate for qualitative and quantitative analysis of drug samples. This methodology provided a potentially useful alternative to time-consuming gas chromatography-mass spectroscopy and high-performance liquid chromatography methods.

Validation of a straightforward high performance liquid chromatographic method for morphine quantitation

Background

Morphine is illegal to use unless it is prescribed by a medical doctor. This compound is commonly abused in the form of illicit heroin.

Methods

An easy-to-use method for determining morphine in illicit heroin using high performance liquid chromatography-photodiode array detector (HPLC-PDA) was developed. With the aid of 50:50 acetonitrile:ammonium formate, this target compound traveling in a pentafluorophenyl (PFP) column was successfully separated from other compounds frequently present in the heroin matrix.

Results

The method was precise with an intra-day relative standard deviation (RSD) ≤ 0.8% and inter-day RSD < 5%. It was able to detect as low as 0.001 mg/mL morphine. The detector’s response was linear (R² > 0.999) and reliable for morphine quantitation from 0.005 up to 1 mg/mL. Through recovery studies, accuracy of the method was averagely estimated to be 89.54–101.91%.

Conclusions

This method saves time in terms of mobile phase preparation and cuts cost by excluding additional purchase of expensive chemicals. More importantly, it proves to be able to determine the target analyte with sufficient accuracy and precision.

The interface between forensic science and technology: how technology could cause a paradigm shift in the role of forensic institutes in the criminal justice system

In this paper, the importance of modern technology in forensic investigations is discussed. Recent technological developments are creating new possibilities to perform robust scientific measurements and studies outside the controlled laboratory environment. The benefits of real-time, on-site forensic investigations are manifold and such technology has the potential to strongly increase the speed and efficacy of the criminal justice system. However, such benefits are only realized when quality can be guaranteed at all times and findings can be used as forensic evidence in court. At the Netherlands Forensic Institute, innovation efforts are currently undertaken to develop integrated forensic platform solutions that allow for the forensic investigation of human biological traces, the chemical identification of illicit drugs and the study of large amounts of digital evidence. These platforms enable field investigations, yield robust and validated evidence and allow for forensic intelligence and targeted use of expert capacity at the forensic institutes. This technological revolution in forensic science could ultimately lead to a paradigm shift in which a new role of the forensic expert emerges as developer and custodian of integrated forensic platforms.

Molecularly imprinted polymers on multi-walled carbon nanotubes as an efficient absorbent for preconcentration of morphine and its chemiluminometric determination

A simple and selective method was described for the determination of morphine based on its preconcentration by molecularly imprinted polymers on multi-walled carbon nanotubes prior to its chemiluminometric recognition.

Near-infrared reflectance spectroscopy (NIRS) for rapid determination of ginsenoside Rg1 and Re in Chinese patent medicine Naosaitong pill

Ginsenosides in plant samples have been extensively studied because protopanaxadiol saponins are ubiquitous in Chinese patent medicines, in which they can be used in promoting human health as the main active ingredients. A method for rapid determination of two ginsenosides (Rg1 and Re) in Naosaitong (NST) samples using near-infrared reflectance spectroscopy (NIRS) is studied to determine the contents of ginsenoside Rg1 and Re in this work. Partial least square (PLS) regression was used for building the calibration models, and the effects of spectral preprocessing and variable selection on the models are investigated for optimization of the models. A total of 93 samples were scanned by NIRS, and also by high performance liquid chromatography coupled to a diode array detector to determine the contents of ginsenoside Rg1 and Re. The calibration models for Rg1 and Re had high values of the coefficient of determination (R(2)) (0.9766 and 0.9764) and low root mean square error of cross validation (RMSECV) (0.0136 and 0.0104), and the values of the standard error of prediction set (SEP) are 0.00764 and 0.0103, which indicate a good correlation between reference values and NIRS predicted values. The overall results show that NIRS could be applied for the rapid determination of the contents of ginsenosides in Ginseng byproducts for pharmaceuticals that develop high-quality Chinese patent medicines.

Characterization of heroin samples by 1H NMR and 2D DOSY 1H NMR

Twenty-four samples of heroin from different illicit drug seizures were analyzed using proton Nuclear Magnetic Resonance ((1)H NMR) and two-dimensional diffusion-ordered spectroscopy (2D DOSY) (1)H NMR. A careful assignment and quantification of (1)H signals enabled a comprehensive characterization of the substances present in the samples investigated: heroin, its main related impurities (6-acetylmorphine, acetylcodeine, morphine, noscapine and papaverine) and cutting agents (caffeine and acetaminophen in nearly all samples as well as lactose, lidocaine, mannitol, piracetam in one sample only), and hence to establish their spectral signatures. The good agreement between the amounts of heroin, noscapine, caffeine and acetaminophen determined by (1)H NMR and gas chromatography, the reference method in forensic laboratories, demonstrates the validity of the (1)H NMR technique. In this paper, 2D DOSY (1)H NMR offers a new approach for a whole characterization of the various components of these complex mixtures.

Direct Determination Methods Without Sample Preparation

The greenest alternatives to the traditional methods of analysis based on sample digestion and/or analyte extraction, are clearly those that permit the direct determination of as many analytes as possible without any sample pretreatment. This chapter deals with the main aspects and applications of remote sensing and teledetection systems, and the use of non-invasive methods of analysis, which permit a direct analysis of samples without any sample damage. In addition, the possibilities offered by several techniques to analyse solids directly without the use of reagents through the direct atomization of small portions of samples, the arc, spark or laser ablation of materials for their analysis by optical emission or mass spectrometry, are evaluated. This chapter attempts to provide a literature survey of all the aforementioned tools which have been evaluated from the perspective of greening analytical practices.

Quantitative determination by temperature dependent near-infrared spectra: a further study

Quantitative spectra-temperature relationship (QSTR) between near-infrared (NIR) spectra and temperature has been studied in our previous work (Talanta, 2010, 82, 1017-1021). In this study, applicability of the QSTR model for quantitative determination is further studied using the spectra of aqueous ethanol samples in the temperature range of 31-40°C and the concentration range of 1-99%. The results show that QSTR model can be built by using the spectra in a small temperature range and the quantitative analysis can be achieved by only two spectra at different temperatures. Moreover, calibration curves for different concentration ranges (1-5%, 20-70%, 95-99%, v/v) are investigated by using linear and nonlinear curve fitting, respectively. Both of the linear and nonlinear curves are found to be applicable within these concentration ranges. Therefore, the temperature dependent NIR spectra may provide a new way for quantitative determination and may have high potential in bio-fluids analysis or industrial practices.

Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).