Description of original award (Fiscal Year 2020, $198,290)
Facing increasing caseloads and an everchanging drug landscape, forensic laboratories have been implementing new analytical tools. Direct analysis in real time mass spectrometer (DART-MS) is often one of these tools because it provides a wealth of information from a rapid, simple analysis. The data produced by these systems, while extremely useful, can be difficult to interpret, especially in the case of complex mixtures. Unlike traditional gas chromatography mass spectrometry (GC-MS) systems, software to aid in spectral analysis and interpretation is limited and primitive. The purpose of this proposal is to create DART-MS spectral interpretation, library building, and report generation software with input from the community that is vendor agnostic, freely available, and open-source. Implementing search algorithms currently under development at the National Institute of Standards and Technology (NIST), the software will allow laboratories to gain more insight into their DART-MS data by identifying potential components in a mixture while also leveraging multiple in-source fragmentation spectra to provide quantitative indices of the likelihood of each identification. This produces results similar to what forensic chemists are accustomed to when they use GC-MS search software. Importantly, the creation of the software, the user experience, and the included features will be completed through collaboration with four forensic laboratories that represent local, state, and federal levels with different instrumentation and different CONOPs. Development and deployment of this software package will occur on one-year timeline through the accomplishment of three objectives: (1) development of an intuitive user experience and training material, (2) software testing and feedback with forensic laboratories, and (3) deployment of the software to the community. Input from collaborating laboratories will allow for refinement and development of multiple iterations of the software to ensure it will be a viable tool for the community. Development of these tools, along with parallel, internally funded efforts for algorithm refinement, algorithm optimization, and creation of updated spectral databases will allow for the forensic community to more efficiently and confidently harness the powerful data produced by DART-MS systems.
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