Tim Stratton, Yingying Huang
GLDMDG 2012 Poster
The determination of the metabolic profile of new chemical entities in pharmaceutical development is a critical step in approval. The need to understand the major routes of elimination, potential for drug-drug interaction, presence of pharmacologically active or biologically reactive metabolites, and the need to confirm coverage of toxicology studies all drive metabolite identification. In vitro studies are often the first option for identification studies however the inability of such systems to completely model in vivo metabolism is understood. As such, in vivo metabolite identification on samples from pharmacokinetic, toxicological, and mass balance studies is common. The complexity of such sample matrices as plasma, urine, feces, and bile makes such studies difficult. In this study we have analyzed the metabolism of omeprazole in human urine samples using a structurally intelligent acquisition and processing technique to overcome the complexity of the matrix.
Thermo Fisher Scientific
United States
