Abstract
The utility of high-resolution MS (HRMS) with post-acquisition data mining in DMPK goes much further than the now established approach to simultaneously acquire quantitative and qualitative information for lead compounds at the discovery stage. Indeed, HRMS has promise for addressing multiple complex drug-development applications in a single experiment. In the present study, one HRMS dataset acquired for in vitro incubations of the model compound dasatinib was mined post-acquisition to address four different issues: stability, metabolite profiling, glutathione conjugate analysis, and endogenous lipid profiling. The derived results demonstrated that HRMS has potential for generating high information content datasets that can be stored and mined as needed to answer numerous complex development-stage questions without the need for additional sample generation or analysis.
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