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Evaluating the Robustness and Ruggedness of a Statistical Model for Comparison of Mass Spectral Data for Seized Drug Identification

NCJ Number
Ruth Smith; Victoria L. McGuffin
Date Published
54 pages

This paper addresses the increasing challenges of identifying novel psychoactive substances based on visual evaluation of spectra in gas chromatography-mass spectrometry; it lays out a summary of the research project, including major goals and objectives, research design, methods, and data analysis, outcomes, limitations, artifacts, references cited, and five appendices.


The authors report on their efforts to evaluate the robustness and ruggedness of the statistical comparison method for compounds representing different novel psychoactive substance (NPS) classes. They suggest that the statistical method described and demonstrated in this report will provide an objective method to statistically compare mass spectra, and note that the method is an extension of current methods to compare spectra, with a statistical evaluation of the reference spectrum and the sample spectrum rather than a visual assessment. For their evaluation, the authors selected compounds representing different NPS classes including structural and positional isomers that were previously documented as being difficult to distinguish based on electron-ionization (EI) mass spectra. The four specific research were: to access the effect of sample concentration on statistical association and discrimination of positional isomers (robustness); to assess the effect of different instruments on statistical association and discrimination of positional isomers (ruggedness); to develop and implement testing of the statistical comparison method in operational forensic science laboratories (testing); and to develop and host training sessions to provide recommendations for implementing the method in forensic laboratories (training). The report describes the authors’ research design, methods, and data analysis techniques. Outcomes are discussed in detail, and descriptions are provided of the six data sets that were generated by the project. The appendices include: Instrument Parameters; Association and Discrimination of Synthetic Cathinones; Association and Discrimination of Fentanyl Analogs; Association and Discrimination of Synthetic Cannabinoids; and Association and Discrimination of Fluoroisobutyryl Fentanyl (FIBF) Position Isomers.