Electrochemical detection of MDMA and 2C-B in ecstasy tablets using a selectivity enhancement strategy by in-situ derivatization

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.

A Calibration Friendly Approach to Identify Drugs of Abuse Mixtures with a Portable Near‐Infrared Analyzer

Both the increasing number and diversity of illicit‐drug seizures complicate forensic drug identification. Traditionally, colorimetric tests are performed on‐site, followed by transport to a laboratory for confirmatory analysis. Higher caseloads increase laboratory workload and associated transport and chain‐of‐evidence assurance performed by police officers. Colorimetric tests are specific only for a small set of drugs. The rise of new psychoactive substances therefore introduces risks for erroneous results. Near‐infrared (NIR)‐based analyzers may overcome these encumbrances by their compound‐specific spectral selectivity and broad applicability. This work introduces a portable NIR analyzer that combines a broad wavelength range (1300–2600 nm) with a chemometric model developed specifically for forensic samples. The application requires only a limited set of reference spectra for time‐efficient model training. This calibration‐light approach thus eliminates the need of extensive training sets including mixtures. Performance was demonstrated with 520 casework samples resulting in a 99.6% true negative and 97.6% true positive rate for cocaine. Similar results were obtained for MDMA, methamphetamine, ketamine, and heroin. Additionally, 236 samples were analyzed by scanning directly through their plastic packaging. Also here, a >97% true positive rate was obtained. This allows for non‐invasive, operator‐safe chemical identification of potentially potent drugs of abuse. Our results demonstrate the applicability for multiple drug‐related substances. Ideally, the combination of this NIR approach with other portable techniques, such as Raman and IR spectroscopy and electrochemical tests, may eventually eliminate the need for subsequent laboratory analysis; therefore, saving tremendous resources in the overall forensic process of confirmatory illicit drug identification.