On-site illicit-drug detection with an integrated near-infrared spectral sensor: A proof of concept.

Illicit-drug production, trafficking and seizures are on an all-time high. This consequently raises pressure on investigative authorities to provide rapid forensic results to assist law enforcement and legal processes in drug-related cases. Ideally, every police officer is equipped with a detector to reliably perform drug testing directly at the incident scene. Such a detector should preferably be small, portable, inexpensive and shock-resistant but should also provide sufficient selectivity to prevent erroneous identifications. This study explores the concept of on-site drugs-of-abuse detection using a 1.8 × 2.2 mm2 multipixel near-infrared (NIR) spectral sensor that potentially can be integrated into a smartphone. This integrated sensor, based on an InGaAs-on-silicon technology, exploits an array of resonant-cavity enhanced photodetectors without any moving parts. A 100% correct classification of 11 common illicit drugs, pharmaceuticals and adulterants was achieved by chemometric modelling of the response of 15 wavelength-specific pixels. The performance on actual forensic casework was investigated on 246 cocaine-suspected powders and 39 MDMA-suspected ecstasy tablets yielding an over 90% correct classification in both cases. These findings show that presumptive drug testing by miniaturized spectral sensors is a promising development ultimately paving the way for a fully integrated drug-sensor in mobile communication devices used by law enforcement.

Performance evaluation of handheld Raman spectroscopy for cocaine detection in forensic case samples.

Handheld Raman spectroscopy is an emerging technique for rapid on-site detection of drugs of abuse. Most devices are developed for on-scene operation with a user interface that only shows whether cocaine has been detected. Extensive validation studies are unavailable, and so are typically the insight in raw spectral data and the identification criteria. This work evaluates the performance of a commercial handheld Raman spectrometer for cocaine detection based on (i) its performance on 0-100 wt% binary cocaine mixtures, (ii) retrospective comparison of 3,168 case samples from 2015 to 2020 analyzed by both gas chromatography-mass spectrometry (GC-MS) and Raman, (iii) assessment of spectral selectivity, and (iv) comparison of the instrument's on-screen results with combined partial least square regression (PLS-R) and discriminant analysis (PLS-DA) models. The limit of detection was dependent on sample composition and varied between 10 wt% and 40 wt% cocaine. Because the average cocaine content in street samples is well above this limit, a 97.5% true positive rate was observed in case samples. No cocaine false positives were reported, although 12.5% of the negative samples were initially reported as inconclusive by the built-in software. The spectral assessment showed high selectivity for Raman peaks at 1,712 (cocaine base) and 1,716 cm-1 (cocaine HCl). Combined PLS-R and PLS-DA models using these features confirmed and further improved instrument performance. This study scientifically assessed the performance of a commercial Raman spectrometer, providing useful insight on its applicability for both presumptive detection and legally valid evidence of cocaine presence for law enforcement.