CPSA Digest 2001

Proceedings -Wednesday, October 10, 2001

WOC4

Plasma Metabolite Identification Using Q-Tof Ultima

Background

Drug metabolism generally requires detailed information on the metabolism of compounds very early in the drug discovery process to improve the lead optimization process. Various mass spectrometry systems (LC-MS/MS, LCQ ion trap, and Q-TOF) have played a key role in the identification and evaluation of metabolites. The unique capabilities of each specific system can be exploited to provide detailed structural characterization of metabolites of potential lead candidate compounds. A brief comparison is provided below.

Triple quadrupole mass spectrometer

• Tandem MS techniques include the ability to perform precursor, product and neutral loss experiments

Ion trap mass spectrometer (LCQ)

• MSn provides the ability to perform sequential fragmentation experiments on a single metabolite to pinpoint the exact site of modification

Q-TOF mass spectrometer

• Very high sensitivity
• Very high resolution (up to 8000) and mass accuracy (+/- 5-10 mDa)
• Tandem MS - product ion scanning

Premise

This presentation highlights the use of Q-TOF Ultima in the search for a toxic metabolite in monkey plasma and urine. It was found that Schering candidate SCH 886 caused toxicity in monkeys but not in rats. The mode of toxicity was uncertain but appeared to be hepatotoxicity due to a metabolite. Plasma and urine samples were collected from dosed animals and metabolite identification was performed using both Q-TOF Classic and Q-TOF Ultima to compare the techniques. Analysis of samples (after protein precipitation) was done by LC-ESI-MS and MS/MS. Precursor ion scan experiments provided full scan MS/MS data for metabolites in monkey plasma and urine.

Value of the Technology

Below is a comparison of metabolites found using targeted Q-TOF Classic MS/MS and Ultima precursor ion scanning in monkey urine and plasma. Clearly, the capabilities of the Q-TOF Ultima allowed for identification of additional metabolites compared with the Q-TOF Classic.

Links
Kathleen A. Cox, Nigel J. Clarke, Diane Rindgen and Walter A. Korfmacher. "Higher Throughput Metabolite Identification in Drug Discovery: Current Capabilities and Future Trends." American Pharmaceutical Review (Spring 2001).

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