Raman spectroscopy with far-red excitation has been used to study seized, tableted samples of MDMA (N-methyl-3,4-methylenedioxyamphetamine) and related compounds (MDA, MDEA, MBDB, 2C-B and amphetamine sulfate), as well as pure standards of these drugs. We have found that by using far-red (785 nm) excitation the level of fluorescence background even in untreated seized samples is sufficiently low that there is little difficulty in obtaining good quality data with moderate 2 min data accumulation times. The spectra can be used to distinguish between even chemically-similar substances, such as the geometrical isomers MDEA and MBDB, and between different polymorphic/hydrated forms of the same drug. Moreover, these differences can be found even in directly recorded spectra of seized samples which have been bulked with other materials, giving a rapid and non-destructive method for drug identification. The spectra can be processed to give unambiguous identification of both drug and excipients (even when more than one compound has been used as the bulking agent) and the relative intensities of drug and excipient bands can be used for quantitative or at least semi-quantitative analysis. Finally, the simple nature of the measurements lends itself to automatic sample handling so that sample throughputs of 20 samples per hour can be achieved with no real difficulty.

Raman spectroscopy with far-red excitation has been investigated as a simple and rapid technique for composition profiling of seized ecstasy (MDMA, N-methyl-3,4-methylenedioxyamphetamine) tablets. The spectra obtained are rich in vibrational bands and allow the active drug and excipient used to bulk the tablets to be identified. Relative band heights can be used to determine drug/excipient ratios and the degree of hydration of the drug while the fact that 50 tablets per hour can be analysed allows large numbers of spectra to be recorded. The ability of Raman spectroscopy to distinguish between ecstasy tablets on the basis of their chemical composition is illustrated here by a sample set of 400 tablets taken from a large seizure of > 50,000 tablets that were found in eight large bags. The tablets are all similar in appearance and carry the same logo. Conventional analysis by GC-MS showed they contained MDMA. Initial Raman studies of samples from each of the eight bags showed that despite some tablet-to-tablet variation within each bag the contents could be classified on the basis of the excipients used. The tablets in five of the bags were sorbitol-based, two were cellulose-based and one bag contained tablets with a glucose excipient. More extensive analysis of 50 tablets from each of a representative series of sample bags have distribution profiles that showed the contents of each bag were approximately normally distributed about a mean value, rather than being mixtures of several discrete types. Two of the sorbitol-containing sample sets were indistinguishable while a third was similar but not identical to these, in that it contained the same excipient and MDMA with the same degree of hydration but had a slightly different MDMA/sorbitol ratio. The cellulose-based samples were badly manufactured and showed considerable tablet-to-tablet variation in their drug/excipient ratio while the glucose-based tablets had a tight distribution in their drug/excipient ratios. The degree of hydration in the MDMA feedstocks used to manufacture the cellulose-, glucose- and sorbitol-based tablets were all different from each other. This study, because it centres on a single seizure of physically similar tablets with the same active drug, highlights the fact that simple physical descriptions coupled with active drug content do not in themselves fully characterize the nature of the seized materials. There is considerable variation in the composition of the tablets within this single seizure and the fact that this variation can be detected from Raman spectra demonstrates that the potential benefits of obtaining highly detailed spectra can indeed translate into information that is not readily available from other methods but would be useful for tracing of drug distribution networks.

The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (l ex = 785 nm, 3 µm diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 µm in diameter. Spectra collected with a microscope from eight points on a 200 µm grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, m r , was 1.19 with an unacceptably high standard deviation, s r , of 1.20. In contrast, with a conventional macro-Raman system (150 µm spot diameter), combined eight grid point data gave m r = 1.47 with s r = 0.16. A simple statistical model which could be used to predict s r under the various conditions used was developed. The model showed that the decrease in s r on moving to a 150 µm spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R 2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.

The potential of IR absorption and Raman spectroscopy for rapid identification of novel psychoactive substances (NPS) has been tested using a set of 221 unsorted seized samples suspected of containing NPS. Both IR and Raman spectra showed large variation between the different sub-classifications of NPS and smaller, but still distinguishable, differences between closely related compounds within the same class. In initial tests, screening the samples using spectral searching against a limited reference library allowed only 41% of the samples to be fully identified. The limiting factor in the identification was the large number of active compounds in the seized samples for which no reference vibrational data were available in the libraries rather than poor spectral quality. Therefore, when 33 of these compounds were independently identified by NMR and mass spectrometry and their spectra used to extend the libraries, the percentage of samples identified by IR and Raman screening alone increased to 76%, with only 7% of samples having no identifiable constituents. This study, which is the largest of its type ever carried out, therefore demonstrates that this approach of detecting non-matching samples and then identifying them using standard analytical methods has considerable potential in NPS screening since it allows rapid identification of the constituents of the majority of street quality samples. Only one complete feedback cycle was carried out in this study but there is clearly the potential to carry out continuous identification/updating when this system is used in operational settings.

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