This poster, authored by Ailing Zhou, Nathan Fish, Tung Nguyen, Yijun Yi, and Tom Fleischmann from IQVIA Laboratories, describes how microflow and nanoflow LC-MS methods dramatically improve the sensitivity and reliability of metabolite identification for lipid-modified peptide therapeutics in preclinical studies. Traditional LC-MS approaches struggled with low-abundance metabolites and matrix interferences, but the enhanced workflow enabled the detection and characterization of sixteen metabolites across plasma, urine, bile, and feces. Key metabolic pathways included proteolytic cleavage, hydrolysis, beta-oxidation, and oxidative decarboxylation.
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