Spectral Trends in DART-MS Data Obtained from the NIST DART-MS Forensics Database: A resource for unknown compound classification

The ever-changing drug landscape is causing a continual strain on resources for forensic laboratories. With the influx of novel psychoactive substances and other emerging compounds of concern, the utility of traditional screening approaches is being diminished. To fill this void, some laboratories are implementing techniques like direct analysis in real time mass spectrometry (DART-MS) that offer rapid analysis times. The use of screening tools that collect spectral information provides an opportunity for gaining more in-depth information about the compounds within a sample, including complete unknowns. This manuscript seeks to simplify the approach for unknown classification or identification using DART-MS data by compiling existing scientific literature and combining it with results from an exploratory analysis of the NIST DART-MS Forensic Database. Specifically, this work investigates protonated molecule abundance, shared and unique neutral losses, and mass spectral distributions for commonly encountered drug classes to provide a resource for unknown compound classification. Several examples of how this information can be used to classify new compounds are included.