Development and evaluation of portable NIR technology for the identification and quantification of Australian illicit drugs.

The efficient and accurate analysis of illicit drugs remains a constant challenge in Australia given the high volume of drugs trafficked into and around the country. Portable drug testing technologies facilitate the decentralisation of the forensic laboratory and enable analytical data to be acted upon more efficiently. Near-infrared (NIR) spectroscopy combined with chemometric modelling (machine learning algorithms) has been highlighted as a portable drug testing technology that is rapid and accurate. However, its effectiveness depends upon a database of chemically relevant specimens that are representative of the market. There are chemical differences between drugs in different countries that need to be incorporated into the database to ensure accurate chemometric model prediction. This study aimed to optimise and assess the implementation of NIR spectroscopy combined with machine learning models to rapidly identify and quantify illicit drugs within an Australian context. The MicroNIR (Viavi Solutions Inc.) was used to scan 608 illicit drug specimens seized by the Australian Federal Police comprising of mainly crystalline methamphetamine hydrochloride (HCl), cocaine HCl, and heroin HCl. A number of other traditional drugs, new psychoactive substances and adulterants were also scanned to assess selectivity. The 3673 NIR scans were compared to the identity and quantification values obtained from a reference laboratory in order to assess the proficiency of the chemometric models. The identification of crystalline methamphetamine HCl, cocaine HCl, and heroin HCl specimens was highly accurate, with accuracy rates of 98.4 %, 97.5 %, and 99.2 %, respectively. The sensitivity of these three drugs was more varied with heroin HCl identification being the least sensitive (methamphetamine = 96.6 %, cocaine = 93.5 % and heroin = 91.3 %). For these three drugs, the NIR technology provided accurate quantification, with 99 % of values falling within the relative uncertainty of ±15 %. The MicroNIR with NIRLAB infrastructure has demonstrated to provide accurate results in real-time with clear operational applications. There is potential to improve informed decision-making, safety, efficiency and effectiveness of frontline and proactive policing within Australia.

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.