Exploring the added value of portable devices such as near infrared spectrometer in the field of illicit drugs analyses.

Facing the problem of backlogs in the forensic laboratories, the field of illicit drugs analyses has recently seen the development of different types of portable devices. Their main purpose is to be used directly by the police in order to reduce the number of specimens that are sent to the laboratories. Several portable devices have shown promising results. To avoid misuses, the added value of these devices should be explored, in order to establish "good practices" and keep the communication channels open between the police and the laboratories. Adapting sampling procedures around the use of portable devices allows for real-time qualitative and quantitative data. Forensic scientists can therefore rapidly assess whether every specimen in a seizure contain illicit drugs and if the seizure is composed of specimens showing different composition. Based on these information, forensic scientists can proceed to an intelligence-led sampling and prioritise specimens that would require further analyses. Additionally, the availability of more analysis data can strengthen the confidence in the reporting of the sampling process and the analyses results. Various scenarios have been tested in an operational context at the Geneva Cantonal Police Force using an ultraportable NIR device. The focus was oriented on sampling issues and the intelligence produced. Results indicate a great potential to detect the different classes within a seizure and therefore to ensure a representative sampling for further analyses.

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.

The aim of the present study was to explore the feasibility of applying near-infrared (NIR) spectroscopy for the quantitative analysis of Δ9-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.

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.

The analysis of illicit drugs faces many challenges, mainly regarding the production of timely and reliable results and the production of added value from the generated data. It is essential to rethink the way this analysis is operationalised, in order to cope with the trend toward the decentralization of forensic applications. This paper describes the deployment of an ultra-portable near-infrared detector connected to a mobile application. This allows analysis and display of results to end users within 5s. The development of prediction models and their validation, as well as strategies for deployment within law enforcement organizations and forensic laboratories are discussed.