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An effective QWBA/UHPLC-MS/tissue punch approach: solving a pharmacokinetic issue via quantitative Met-ID...

by Jozsef Panczel, Manfred Schudok, Matthias Schiell, Jens Riedel, Vilmos Kertesz
Publication Type
Journal
Journal Name
Drug Metabolism Letters
Publication Date
Volume
14
Issue
x

Background: Methods to provide absolute quantitation of the administered drug and corresponding metabolites in tissue in a spatially resolved manner is a challenging but much needed necessity in pharmaceutical research. Quantitative whole-body autoradiography (QWBA) after a single-dose intravenous (3 mg/kg) and extravascular (30 mg/kg) administrations of an in vitro metabolically stable test compound (structure not reported here) indicated quick tissue distribution and excretion.

Objective: Good bioavailability and short in vivo half-lives were determined formerly for the same test compound. For closing gaps in the understanding of pharmacokinetic data and in vitro results, radioactive hot spots on whole-body tissue sections had been profiled.

Method: Punches from selected tissue regions containing high radioactivity in the tissue sections previously analyzed by QWBA were extracted by a highly organic solvent and analyzed without any consecutive sample preparation step, applying ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS) and off-line radioanalysis to maximize signal levels for metabolite identification and profiling.

Results: The analysis revealed that the test compound was metabolized intensively by phase I reactions in vivo and the metabolites formed were excreted in bile and in urine. The predominant metabolites showed abundant signal intensities both by MS and by radioanalysis but the MS signal intensities generally underestimated the real abundances of metabolites relative to the unchanged drug.

Conclusions: This work illustrates that maximizing the sensitivity of tissue punch radioanalysis and the combination with UHPLC-MS leads to a better insight of pharmacokinetic processes by providing quantitative data with high molecular selectivity.