Automated Fast Screening Method for Cocaine Identification in Seized Drug Samples Using a Portable Fourier Transform Infrared (FT-IR) Instrument

Abstract

Quick and presumptive identification of seized drug samples without destroying evidence is necessary for law enforcement officials to control the trafficking and abuse of drugs. This work reports an automated screening method to detect the presence of cocaine in seized samples using portable Fourier transform infrared (FT-IR) spectrometers. The method is based on the identification of well-defined characteristic vibrational frequencies related to the functional group of the cocaine molecule and is fully automated through the use of an expert system. Traditionally, analysts look for key functional group bands in the infrared spectra and characterization of the molecules present is dependent on user interpretation. This implies the need for user expertise, especially in samples that likely are mixtures. As such, this approach is biased and also not suitable for non-experts. The method proposed in this work uses the well-established "center of gravity" peak picking mathematical algorithm and combines it with the conditional reporting feature in MicroLab software to provide an automated method that can be successfully employed by users with varied experience levels. The method reports the confidence level of cocaine present only when a certain number of cocaine related peaks are identified by the automated method. Unlike library search and chemometric methods that are dependent on the library database or the training set samples used to build the calibration model, the proposed method is relatively independent of adulterants and diluents present in the seized mixture. This automated method in combination with a portable FT-IR spectrometer provides law enforcement officials, criminal investigators, or forensic experts a quick field-based prescreening capability for the presence of cocaine in seized drug samples.

Detection of newly emerging psychoactive substances using Raman spectroscopy and chemometrics

“…An additional 21 NPS were used to further validate and test the generated model. These were split into two different groups, the validation set (17) and test set (4), where validation set NPS (SI.2 †) were compounds that were part of the initial 478 compound dataset but not used as training set, and test set substances, that were psychoactive drugs external to the initial dataset of 478 compounds (SI.3 †).…”

“…7 looks at pyrazolam with regards to the structurally related training set benzodiazepines (Category 8), etizolam and ubromazolam. All three structures bear the 3,7-dimethyl-9H- [1,2,4]triazolo [4,3-a] [1,4]diazepine core (depicted in black on the chemical structure). In most cases, benzodiazepines include a 7-membered ring, an additional benzene ring and an electron attracting group at position 7 of the fused heterocyclic rings to ensure biological activity.…”

“…[1][2][3] In most cases, this can be attributed to efforts by suppliers to evade their detection and circumvent existing legislation. 1,4 This rapid appearance, poor detectability, increased potency and availability of newly emerging drugs is oen accompanied by an increase in reported health harms, emergency department visits and even fatalities, making NPS a major public health concern. 1,2 In an attempt to restrict the production, supply and abuse of NPS, countries such as New Zealand, and more recently the United Kingdom, have approved psychoactive substances Acts, oen referred to as 'blanket bans'.…”

The Danger of Relying on Database Spectra

“…Vibrational spectroscopy in terms of Raman scattering and infrared (IR) absorption is experiencing an ever-increasing interest in academia and industry. One of the main drivers of this development is the advent of commercial instruments [1][2][3] that are easy to use even for inexperienced personnel. This basically means that someone without knowledge about spectroscopy or the underlying technology of the instrument is able to record spectra with good signal-to-noise ratio.…”

Identification of Opioids and Related Substances using Handheld Raman Spectrometers

“…Recent studies have described the use of field‐based techniques for identifying active pharmaceutical ingredients (APIs). Although many different types of handheld and field‐portable analytical devices are currently available for detecting APIs, the most popular and most established instruments are ion mobility spectrometers (IMS) , Fourier transform infrared (FT‐IR) spectrometers and Raman spectrometers . Handheld/portable IMS devices are sensitive for detecting APIs, but they have limited selectivity since they only utilize drift time for identification.…”