Classification of fentanyl precursors by multivariate analysis of low-field nuclear magnetic resonance spectroscopy data

Abstract

High-field Nuclear Magnetic Resonance (NMR) spectroscopy combined with multivariate analysis techniques have been used extensively in several fields particularly, metabolomics and food quality assessment. In contrast, low-field Fourier transform NMR instruments are a relatively new analytical platform and recent studies have shown its potential application for forensic narcotic identification. In this study Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were applied on spectra data from both low-field (43 MHz) and high-field (300 MHz) NMR of two key precursors to fentanyl, N-phenethyl-4-piperidone (NPP) and 4-anilino-N-phenethylpiperidine (ANPP). Three different methods were employed for the synthesis of these two precursors – the Siegfried, Valdez and One-Pot methods. The application of low-field NMR spectroscopy combined with multivariate analysis allowed successful classification of fentanyl precursors, NPP and ANPP, based on each synthetic method’s unique impurity profile. This approach supports the possibility of low-field NMR being employed by law enforcement for forensic attribution of clandestine fentanyl and its precursors to a specific synthetic method.