Providing illicit drugs results in five seconds using ultra-portable NIR technology: An opportunity for forensic laboratories to cope with the trend toward the decentralization of forensic capabilities

Coppey, Florentin; Bécue, Andy; Sacré, Pierre-Yves; Ziémons, Eric; Hubert, Philippe; Esseiva, Pierre

doi:10.1016/j.forsciint.2020.110498

Cited by 48 publications

(52 citation statements)

References 22 publications

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“…Good accuracy was obtained with an RMSEP of 1.75 % (w/w). However, it must be said that the advantages in terms of performance of this type of chemometric model are better exploited when large-scale datasets are involved, as demonstrated in a previous study [21]. In contrast, GA-PLS models could become less accurate when heterogeneous samples are integrated into the dataset due to the effect of other variable parameters, such as humidity, color and size.…”

Section: Feasibility Study On Entire Cannabis Inflorescence: Application Of Ensemble Regression Models To Thc Content Predictionsmentioning

confidence: 94%

“…In a recent work, the possibility of differentiating between legal and illegal cannabis inflorescences by using a qualitative model implemented with a handheld system was explored. The chemometric model showed 100 % sensitivity (true positive) and selectivity (true negative) during validation studies [21].…”

Section: Introductionmentioning

confidence: 93%

“…Various combinations of spectral preprocessing were evaluated in a previous study on similar substances [21]. The Savitzky-Golay 2 nd derivative (polynomial order: 2, window size: 3) and standard normal variate (SNV) were the preprocessing with the best results to quantify substances with the MicroNIR.…”

Section: Chemometricsmentioning

confidence: 99%

“…Regarding the application of NIR spectroscopy to cannabis analysis, only a few works can be found in the literature, showing some interesting applications [19][20][21][22]. In a recent work, the possibility of differentiating between legal and illegal cannabis inflorescences by using a qualitative model implemented with a handheld system was explored.…”

Section: Introductionmentioning

confidence: 99%

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New perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol

Deidda

Coppey

Damergi

et al. 2021

Journal of Pharmaceutical and Biomedical Analysis

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The aim of the present study was to explore the feasibility of applying near-infrared (NIR) spectroscopy for the quantitative analysis of 9 -tetrahydrocannabinol (THC) in cannabis products using handheld devices. A preliminary study was conducted on different physical forms (entire, ground and sieved) of cannabis inflorescences in order to evaluate the impact of sample homogeneity on THC content predictions. Since entire cannabis inflorescences represent the most common types of samples found in both the pharmaceutical and illicit markets, they have been considered priority analytical targets. Two handheld NIR spectrophotometers (a low-cost device and a mid-cost device) were used to perform the analyses and their predictive performance was compared. Six partial least square (PLS) models based on reference data obtained by UHPLC-UV were built. The importance of the technical features of the spectrophotometer for quantitative applications was highlighted. The mid-cost system outperformed the low-cost system in terms of predictive performance, especially when analyzing entire cannabis inflorescences. In contrast, for the more homogeneous forms, the results were comparable.The mid-cost system was selected as the best-suited spectrophotometer for this application. The number of cannabis inflorescence samples was augmented with new real samples, and a chemometric model based on machine learning ensemble algorithms was developed to predict the concentration of THC in those samples. Good predictive performance was obtained with a root mean squared error of prediction of 1.75 % (w/w). The Bland-Altman method was then used to compare the NIR predictions to the quantitative results obtained by UHPLC-UV and to evaluate the degree of accordance between the two analytical techniques. Each result fell within the established limits of agreement, demonstrating the feasibility of this chemometric model for analytical purposes.Finally, resin samples were investigated by both NIR devices. Two PLS models were built by using a sample set of 45 samples. When the analytical performances were compared, the mid-cost spectrophotometer significantly outperformed the low-cost device for prediction accuracy and reproducibility.

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Section: Feasibility Study On Entire Cannabis Inflorescence: Application Of Ensemble Regression Models To Thc Content Predictionsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 93%

Section: Chemometricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

New perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol

Deidda

Coppey

Damergi

et al. 2021

Journal of Pharmaceutical and Biomedical Analysis

Self Cite

View full text Add to dashboard Cite

show abstract

“…This may lead to false negative (FN) results when the incorrect test is performed or a controlled substance is encountered for which no test is available. 3 Other indicative testing strategies for on-site cocaine detection using handheld devices include electrochemical analysis, 6 (near) infrared spectroscopy, [7][8][9][10] and Raman spectroscopy [11][12][13][14] where the latter two offer possibilities to analyze substances directly through packaging material (when this material is sufficiently transparent). Over the last decade, Raman spectroscopy has become a viable tool in forensic chemistry, and its applications have been reviewed multiple times.…”

mentioning

confidence: 99%

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

Kranenburg

Verduin

Ridder³

et al. 2021

Drug Testing and Analysis

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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.

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Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

Schram

Parrilla

Sleegers

et al. 2021

Drug Testing and Analysis

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The emergence of new psychoactive drugs in the market demands rapid and accurate tools for the on‐site classification of illegal and legal compounds with similar structures. Herein, a novel method for the classification of synthetic cathinones (SCs) is presented based on their electrochemical profile. First, the electrochemical profile of five common SC (i.e., mephedrone, ethcathinone, methylone, butylone, and 4‐chloro‐alpha‐pyrrolidinovalerophenone) is collected to build calibration curves using square wave voltammetry on graphite screen‐printed electrodes (SPEs). Second, the elucidation of the oxidation pathways, obtained by liquid chromatography–high‐resolution mass spectrometry, allows the pairing of the oxidation products to the SC electrochemical profile, providing a selective and robust classification. Additionally, the effect of common adulterants and illicit drugs on the electrochemical profile of the SC is explored. Interestingly, a cathodic pretreatment of the SPE allows the selective detection of each SC in presence of electroactive adulterants. Finally, the electrochemical approach is validated with gas chromatography–mass spectrometry by analyzing 26 confiscated samples from seizures and illegal webshops. Overall, the electrochemical method exhibits a successful classification of SC including structural derivatives, a crucial attribute in an ever‐diversifying drug market.

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Providing illicit drugs results in five seconds using ultra-portable NIR technology: An opportunity for forensic laboratories to cope with the trend toward the decentralization of forensic capabilities

Cited by 48 publications

References 22 publications

New perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol

New perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol

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

Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

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