A green method for the determination of cocaine in illicit samples

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.

Overview of cocaine identification by vibrational spectroscopy and chemometrics

The use of non-destructive forensic methods for cocaine identification is of outstanding importance, given the amount of samples seized. Techniques such as ATR-FTIR, Raman, and NIR spectroscopy have become alternatives to circumvent this problem, as they allow fast, cheap analysis, and enable the reanalysis of samples. When combined with chemometrics, these spectroscopic methods can be used to determine and quantify cocaine samples, meaning that the limitations of existing techniques can be overcome. This review article covers spectroscopic techniques for identifying cocaine in different forms and matrices, such as food and textiles, which are materials used for smuggling. The chemometric identification of cocaine in oral fluid and water is also discussed. In addition, vibrational spectroscopy techniques using portable equipment are described. This work seeks to evaluate the main chemometric applications of spectroscopic data and to find new perspectives on the identification of cocaine using chemometrics.

Understanding Australian methylamphetamine drug markets through relational, temporal and spatial analyses

In the area of illicit drugs, forensic case data have proven effective at detecting links between seizures and providing greater insights into illicit drug markets. This research explored the application of mathematical and statistical techniques to several chemical profiles of Australian methylamphetamine seizures. The main aim was to create and deliver a method that would expand the use of illicit drug profiling for strategic intelligence purposes, contributing to the fight against illicit drug trafficking. The use of comparison metrics and clustering analysis to determine links between existing illicit drug specimens and subsequent new specimens was evaluated and automated. Relational, temporal and spatial analyses were subsequently used to gain an insight into illicit drug markets. Relational analysis identified clusters of seizures central to the network. Temporal analysis then provided insights into the behaviour of distribution markets, specifically the emergence and extinction of certain clusters of seizures over time. Spatial analysis aided the understanding of the inter-jurisdictional nature of illicit drug markets. These analyses allowed for the generation of strategic intelligence relating to when and where the Australian methylamphetamine illicit drug market was the most active. Additionally, the strategic level trends identified clusters of seizures that were worth investigating further. These clusters were explored through a case study, which exploited additional chemical profiling data to provide drug market knowledge at an operational level. In turn, the intelligence produced at various levels could allow relevant law enforcement agencies to take necessary measures in disrupting markets.

On Selecting a Suitable Spectral Matching Method for Automated Analytical Applications of Raman Spectroscopy

Raman spectra are molecular structure-specific and hence are employed in applications requiring chemical identification. The advent of efficient handheld and smartphone-based Raman instruments is promoting widespread applications of the technique, which often involve less trained end users. Software modules that enable spectral library searches based on spectral pattern matching is an essential part of such applications. The Raman spectrum recorded by end users will naturally have varying levels of signal to noise (SN), baseline fluctuations, etc., depending on the sample environment. Further, in biological, forensic, food, pharmaceuticals, etc., fields where a vast amount of Raman spectral data is generated, careful removal of background is often impossible. In other words, a 100% match between the library spectrum and user input cannot be often guaranteed or expected. Often, such influences are discounted upon developing mathematical methods for general applications. In this manuscript, we carefully examine how such effects would determine the results of spectral similarity-based library search. We show that several popular mathematical spectral matching approaches give incorrect results under the influence of small changes in the baseline and/or the noise. We also discuss the points to be carefully considered while generating a spectral library. We believe our results will be a guiding note for developing applications of Raman spectroscopy that uses a standard spectral library and mathematical spectral matching.

Challenges for cocaine detection in smuggling samples

Screening of seized cocaine powders is routinely performed by means of colour tests. An alternative fast screening technique is Mid-InfraRed (MIR) spectroscopy. In the context of smuggling cases, however, drugs are often processed to circumvent detection. In this study, the current screening techniques (cocaine colour test and MIR spectroscopy using libraries and chemometrics) were applied to five smuggling cases. For each case, all samples were first screened with a cocaine colour test and MIR analysis, followed by confirmation analyses with GC-MS and GC-FID to identify and quantify cocaine and cutting agents. Finally, Scanning Electron Microscopy-Energy Dispersive X-ray spectroscopy (SEM-EDX) analyses were performed for additional characterization. All smuggling samples tested negative, both on-site as in the laboratory, for cocaine with the cocaine colour test. Four smuggling cases consisted of coloured samples. Consequently the colour test result was influenced because discolouration of the test showed almost the same colour as the colour of the powders (brown, green, red or black). In contrast, the (coloured) powders could be measured with MIR, but the MIR spectra showed no hit for cocaine using a reference library search. Moreover, cocaine was not detected in four out of the five cases after application of a chemometric classification model. GC-MS analysis, the golden standard for identification, resulted in a positive identification of cocaine in all cases. These samples contained cocaine ranging between 0.8w% and 35w%. Taking into account the results of the screening, the chromatographic and the SEM-EDX analyses, it could be presumed that cocaine was masked. False negative screening results were caused by chemically modified cocaine and/or cocaine mixed with coloured powders. In additional experiments, a sample extraction step prior to the screening techniques was performed. Two sample preparation methods (acetone and ethyl acetate) were tested and resulted in a positive screening of cocaine with the colour test and/or MIR spectroscopy. It can be concluded that the outcome of screening techniques such as colour tests and MIR spectroscopy is only presumptive and should always be confirmed.

Evaluation of a low-cost portable near-infrared spectrophotometer for in situ cocaine profiling

The potential of a low-cost (∼US$ 1000) portable near-infrared (NIR) spectrophotometer for in situ characterization of seized cocaine samples was evaluated. A set of 240 samples of cocaine seized in several regions and cities across Brazil by its federal police was employed in this study. These samples were previously analyzed by chromatography at the Forensic Chemistry Laboratory of the National Institute of Criminalistics in Brasília-DF for the contents of several constituents to chemically characterize the samples. A low-cost NanoNIR spectrophotometer (Texas instruments) was used to acquire the NIR spectra of the samples in the range 900-1700 nm. The spectra set was treated by the second derivative to construct and validate multivariate regression (Partial Least Square - PLS) and classification (software independent modeling of class analogy - SIMCA) models aiming to characterize the samples. Consequently, an informative toll for objective decision making could be used by the police agents to produce immediate answers to forensic questions raised at the point of seizing. Among those questions the most relevant are: does the seized sample contain cocaine? what is the cocaine form? what is its content? is the sample adulterated and/or diluted? what is the content of adulterant? is the sample significantly adulterated and/or diluted? what is the degree of oxidation of the cocaine? The results of this work allow to propose a NIR/chemometrics based analytical protocol providing fast answers to these questions with satisfactory confidence level for the purpose of reliably screen the seized samples.

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.

Automated Fast Screening Method for Cocaine Identification in Seized Drug Samples Using a Portable Fourier Transform Infrared (FT-IR) Instrument

Quick and presumptive identification of seized drug samples without destroying evidence is necessary for law enforcement officials to control the trafficking and abuse of drugs. This work reports an automated screening method to detect the presence of cocaine in seized samples using portable Fourier transform infrared (FT-IR) spectrometers. The method is based on the identification of well-defined characteristic vibrational frequencies related to the functional group of the cocaine molecule and is fully automated through the use of an expert system. Traditionally, analysts look for key functional group bands in the infrared spectra and characterization of the molecules present is dependent on user interpretation. This implies the need for user expertise, especially in samples that likely are mixtures. As such, this approach is biased and also not suitable for non-experts. The method proposed in this work uses the well-established "center of gravity" peak picking mathematical algorithm and combines it with the conditional reporting feature in MicroLab software to provide an automated method that can be successfully employed by users with varied experience levels. The method reports the confidence level of cocaine present only when a certain number of cocaine related peaks are identified by the automated method. Unlike library search and chemometric methods that are dependent on the library database or the training set samples used to build the calibration model, the proposed method is relatively independent of adulterants and diluents present in the seized mixture. This automated method in combination with a portable FT-IR spectrometer provides law enforcement officials, criminal investigators, or forensic experts a quick field-based prescreening capability for the presence of cocaine in seized drug samples.