Advanced Algorithms for the Discovery of Related Components and Application to PFAS and Fentanyl Research.

Algorithms to increase duty cycle for the acquisition of and increase selectivity for the processing of data containing unknown , but related compounds of interest will be presented.  In most cases, related compounds of interest are not present in anywhere near the intensity of the most abundant components in a sample.  This means that a purely automated data-dependent MSMS experiment may often fail to target these components for an autoMSMS experiment.  Once data are acquired unbiased compound searching algorithms are very efficient at finding compounds, but means that our compounds of interest are but a few among the housands of compounds in a sample mixture.  In addition, if the autoMSMS experiment failed to target the compound of interest, then confidence will require a second targeted acquisition.  The MassHunter acquisition concept of a Preferred MSMS list will be presented and how it can dramatically increase the duty cycle for compounds of interest.  The MassHunter concept of Mass Defect, MSMS pseudo Constant Neutral Loss, and MSMS Reporter Ions will also be presented as time and labor saving for sample data processing.

For Research Use Only. Not for use in diagnostic procedures.