Department of Archaeology, Anthropology and Forensic Science
Introduction
Raman spectroscopy has emerged as a rapid and powerful tool for critical applications in forensic science. The advantage of Raman spectroscopy is that the Raman signal is often selective to pharmacologically active drug substances [1, 2]. On the other hand, pharmacologically inactive substances do not exhibit a Raman signal and their spectra are often masked by fluorescence. This could be advantageous in identifying drug substances, especially new psychoactive substances.
New psychoactive substances, also known as ‘legal highs’, are often labelled as containing a pure form of one drug product, for example 2-aminoindan (Figure 1).
However, these substances often show to contain a mixture of other drugs/inactive substances which affect their actions/ adverse effects [3]. In 2012, deaths due to legal highs increased severely with 43 fatalities in the UK from mephedrone [4]. This stimulates the need for rapid and non-destructive techniques to identify the substances present in legal highs, as such:
Figure 1. Internet product labelled as 2-aminoindan and advertised as pure
- Does the product contain the drug stated on ‘Label Claim’?
- Is the product pure?
- If the product is not pure, does it contain any drug or pharmacologically inactive substances?
Handheld Raman spectroscopy off ers the advantage of rapidity, mobility, low-cost and accuracy in identifying drug products. Although laboratory-based Raman instruments provide better spectral quality; handheld instruments have proved better accuracy in identifi cation and quantifi cation of pharmaceutical products [5].
The objective of this work is to identify new psychoactives, products labelled as 2-aminoindan purchased from the Internet using handheld Raman spectroscopy.
Experimental
Six legal high products labelled as 2-aminoindan were purchased from the Internet and consisted of three powders and three capsule products (Table 1). The powders and the capsule contents were emptied into glass vials and stored in a desiccator. Reference analysis for these products was made using GC-MS (Table 1).
Table 1. Details of the products used in the application
The Raman spectra of the products were measured through the glass vials using a handheld instrument with laser power 785 nm with a charged coupled device (CCD) detector with thermoelectric cooling. Twenty spectra were collected from each vial, such that each spectrum was the sum of one scan.
The raw spectra were exported to Matlab 2012a for data analysis where correlation in wavelength space (CWS), principal component analysis (PCA) along with Gaussian mixture models (GMM) was applied.
Results
Figure 2. Raman spectra of Internet products of (a) 2-AI, (b) Blurberry, (c) DXM, (d) Magic Beans (e) NRG-3 and (f) Pink Champagnes measured using a handheld instrument
All of the measured products showed Raman scattering (Figure 2c), which indicated the presence of pharmacologically-active substances at an acceptable concentration [2, 6]. This was confi rmed by the GCMS analysis, which showed that the three powder products contained caff eine; whereas the three capsule products contained a mixture of 2-aminoindan and caff eine. 2AI, DXM and NRG-3 showed similar Raman spectra, which were expected as the three products contained caff eine in high concentration. The correlation coeffi cient value of DXM against NRG-3 was 0.95, which further confi rmed the strong similarity in the chemical species in both products. All the other products had correlation coeffi cient values below 0.95. On the other hand, Blurberry, Magic Beans and Pink Champagnes had similar Raman spectra; but Magic Beans had less scattering intensity which showed either lower concentration of the scattering species or the presence of impurities which decreased the Raman intensity.
Figure 3. PCA scores plot of the six Internet products analyzed (a) 2-AI, (b) Blurberry, (c) DXM, (d) Magic Beans (e) NRG-3 and (f) Pink Champagnes measured using a handheld instrument
DXM and NRG3 which both contained caffeine. On the other hand, two outliers were observed with the 2AI products and were misclassified. Then two cluster centers were plotted for these scores, which showed two major clusters: (1) Cluster one, containing 2AI, DXM and NRG-3, which contained caffeine. This cluster had two type I errors (two 2AI scores were set outside the cluster) and one type II error (one Magic Beans score classified inside cluster one). (2) Cluster two contained the PCA scores of Blurberry, Magic Beans and Pink Champagnes, which both contained 2-aminoindan and caffeine. However, only type I error was observed here, as two Blurberry and six Magic Beans scores were outside the cluster. Yet, this contributed greatly to the similarity/ difference among the scattering species in these batches.
Conclusion
Handheld Raman spectroscopy offered a rapid, simple and nondestructive way for identifying legal highs purchased from the Internet. The use of chemometrics can help track the similarities/differences in the chemical composition of the products.
Author biography
Dr. Sulaf Assi is a postdoctoral research fellow in Drug Misuse and Abuse at the University of Hertfordshire. She finished her Ph.D. on the identification of counterfeit medicines from the School of Pharmacy, University of London. Her active research is focused on the identification of novel psychoactive substances and counterfeit medicines using diff erent analytical techniques and chemometrics.
References
- Sulaf Assi, Robert Watt and Tony Moff at (2011), Authentication of medicines using Raman spectroscopy, European Pharmaceutical Review, 16 (1), 49-55.
- Sulaf Assi, Robert A. Watt and Anthony C. Moff at (2011), On the quantifi cation of ciprofl oxacin in proprietary Ciproxin tablets and generic ciprofl oxacin tablets using handheld Raman spectroscopy, Journal of Raman Spectroscopy, doi: 10.1002/jrs.3125.
- Sulaf Assi, Suzanne Fergus and Jacqueline L. Stair (2012), Identifi cation of novel psychoactive substances (NPS) using hyphenated mass spectrometric techniques, Current Trends in Mass Spectrometry, 2012, 1 March. Special issue.
- BBC, 2012: http://www.bbc.co.uk/news/uk-20217967 accessed 07122012
- Sulaf Assi. (2012), Laboratory based versus handheld instruments: What you gain and what you lose, American Pharmaceutical Review.
- Sulaf Assi, Robert Watt and Tony Moff at (2011), Comparison of Laboratory and Handheld Raman Instruments for The Identifi cation of Counterfeit Medicines, Spectroscopy, June, 40-50. The similarity of these products was established using PCA with GMM on the Raman spectra of these products (Figure 3). The PCA scores plot was able to separate four of the six products.