Towards an Inter-Source Comparison of Dart-Ms and Psi-Ms for Drug Evidence Processing on Commercial and Portable Systems
The comparisons efforts presented here sought to elucidate the effect of employed source, evidence type, instrument utilized, and incorporated handling methods. For inter-instrument testing, a Thermo LCQ Fleet ion trap MS and a FLIR Systems AI-MS 1.2 portable ion trap MS were used to determine relative performance across commercial-grade and portable MS systems. Across bulk and trace-level testing, variable sample handling methods were examined. For direct sampling of bulk powder, glass capillary tubes (DART-MS) or paper substrates (PSI-MS) were directly exposed to the condensed phase and analyzed as-is. Alternatively, the examination of bulk evidence dissolved in methanol was explored in a similar way. For trace evidence analysis, an MQuant blank strip was wetted and used to probe a surface-bound analyte from glass. This substrate was placed directly in the DART analysis region or used as the disposable ion source for PSI. For each test variable, at least 100 samples were processed to allow statistical assessment of analytical performance, including spectra intensity, duration of analyte signal, and false positive/false negative error rates. In an effort to assess the overall usability of the sources, sample throughput, observed carryover rates, and hygiene protocols required to mitigate carryover were tracked. From this, overall user comfort with the methodology can be discerned. Initial results suggests that while both sources are capable of processing the intended evidence, situational proficiencies can be observed. For instance, as user experience grows, DART-MS was shown to have overall higher sample throughput, but PSI-MS was marked by overall higher spectral intensity. This address will highlight the general trends observed across this comprehensive study.
Fatigante, William, "Towards an Inter-Source Comparison of Dart-Ms and Psi-Ms for Drug Evidence Processing on Commercial and Portable Systems" (2018). University Research Symposium. 49.