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The ability to accurately and noninvasively analyze illicit drugs is important for criminal investigations and prosecution. Current methods involve significant sample pretreatment and most are destructive. The goal of this work is to develop a method based on Raman spectroscopy to classify simulated street drug mixtures composed of one drug component and up to three cutting agents including those routinely found in confiscated illicit street drug mixtures. Spectra were collected on both a homebuilt instrument using a HeNe laser and on a handheld commercial instrument with a 785 nm light source. Mixtures were prepared with drug concentrations ranging from 10 to 100 percent. Optimal preprocessing for the data set included truncating, Savitzky-Golay smoothing, normalization, differentiating, and mean centering. Using principal component analysis (PCA), it was possible to resolve the spectral differences between benzocaine, lidocaine, isoxsuprine, and norephedrine and correctly classify them 100 percent of the time.

Measurement of illicit drugs on paper currency is of interest for evidentiary purposes in legal cases involving the drug trade. Current methods, primarily based on mass spectrometry, are destructive and prevent re-analysis of the evidence. This article details a method based on Raman microspectroscopy that is able to collect spectra from individual crystals on the surface of paper currency. Mixtures of isoxsuprine and norephedrine, which are non-pharmacologically active drug surrogates, as well as lidocaine and benzocaine, common excipients in street drugs, were doped in small quantities onto US currency. Significant fluorescence interference resulted from the underlying dollar bill. This work presents two methods for reducing the fluorescence background, photobleaching and background subtraction, which both worked well. Finally, a method for determining the percent composition of individual components in heterogeneous mixtures was developed by systematically sampling the surface of the dollar bill. Results were accurate within a few percent, although the method was quite time consuming.