Forensic analysis for the definitive identification of controlled substances using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is challenging for sample mixtures without extraction techniques. However, the application of principal components regression (PCR), to FTIR spectra is able to provide identification and quantification of controlled substances in sample mixtures in a single analysis without separation of components. In this study, sample binary mixtures were analyzed and used in the development of a PCR model. After model development, two other sets of sample mixtures were used to evaluate model performance. The model was then applied to “blind” sample mixtures; correct identification and accurate quantification were observed, demonstrating the potential of PCR to overcome the limitations of current analysis with ATR-FTIR. Synthetic designer drugs have recently become an international concern, leading research to be directed towards alternative methods of analysis for definitive identification of these drugs. The combination of high-resolution mass spectrometry (HRMS) and mass defect filters is able to overcome the limitations of current forensic methods and enable prioritization of novel synthetic drugs for identification by allowing rapid classification to structural class. In this study, three different types of mass defect filters were developed using phenethylamine and cathinone reference standards. The potential for mass defect filters to be incorporated into a classification scheme to discriminate between phenethylamines and cathinones is demonstrated, thus allowing other resources to be directed towards identification of novel synthetic designer drugs.
Read
