This proposal addresses several defined research needs of nijs forensic science research and development technical working group (TWG), including the ability to identify NPS by comparison to spectra…

This $399,300 Project Grant, awarded by the National Institute of Justice (NIJ) under the CFDA 16.560 National Institute of Justice Research, Evaluation, and Development Project Grants program, aims to develop the Expert Algorithm for Substance Identification (EASI) to improve the confidence of drug identifications involving tandem mass spectra. The key products and services to be delivered under this 2-year grant include:

• Developing the EASI algorithm to enable the identification of new psychoactive substances (NPS) by comparison to spectra from different instruments rather than just reference standards, and conducting error rate studies on qualitative analysis.
• Creating a database of replicate spectra of drug standards collected across multiple DEA laboratories and the principal investigator's lab, using both direct analysis in real-time (DART) and electrospray ionization mass spectrometry instruments.
• Collaborating with a major software company to incorporate the EASI algorithm into their commercial software to facilitate widespread adoption by crime labs.
• Presenting the research results at forensic science conferences, publishing in peer-reviewed journals, and incorporating findings into workshops for forensic practitioners. The tandem mass spectra database will also be made publicly available.

This proposal addresses several defined research needs of nijs forensic science research and development technical working group (TWG), including the ability to identify NPS by comparison to spectra from a different instrument rather than a reference standard and error rate studies on qualitative analysis. The major goal of this project is to develop the expert algorithm for substance identification (EASI) to improve the confidence of drug identifications involving tandem mass spectra. Algorithm development will employ a database of replicate spectra of drug standards collected in up to seven different DEA laboratories and the PIS lab. These instruments will include the use of both direct analysis in real time (DART)for rapid screening of samplesand an electrospray ionization source, to demonstrate the algorithms compatibility with liquid chromatography-mass spectrometry instruments in future toxicology applications. These inter-laboratory comparisons will include data obtained on two different vendors of DART-MS/MS instruments, thereby demonstrating the universal applicability of the algorithm. The library of test spectra will focus on seized drugs that are known to be especially difficult to resolve from their isomers, including the growing problem of O-, M-, and P-isomers of fluorofentanyl commonly found in deas casework. To assist with widespread adoption by practitioners, the PI will collaborate with a major company to incorporate the algorithm into their commercial software. This work will be conducted in parallel with the fundamental algorithm development in the PIS laboratory. The algorithm is transparent in its design, operation, and decision-making steps, and the algorithm should not be specific to the vendor, instrument, or acquisition conditions. Therefore, the algorithm will not become obsolete as instruments evolve over time but will exist in perpetuity to facilitate crime labs in making rapid drug identifications without running contemporaneous standards. Finally, the error rate of the algorithm will be presented in a variety of probabilistic forms, including estimates of the sensitivity, selectivity, and likelihood ratios. This research will immediately benefit deas operations in the short term and could ultimately benefit both forensic chemists and forensic toxicologists at the national level in the long term. The results will be presented at forensic science conferences, published in peer-reviewed journals, and incorporated into workshops that the PI regularly teaches to forensic practitioners. The database of tandem mass spectra will be made available to the public through an open access data repository. CA/NCF