Title
Identification of drug metabolites in human plasma or serum integrating metabolite prediction, LC-HRMS and untargeted data processing
Author
Jacobs, P.L.
Ridder, L.
Ruijken, M.
Rosing, H.
Jager, N.G.L.
Beijnen, J.H.
Bas, R.R.
van Dongen, W.D.
TNO Triskelion BV
Publication year
2013
Abstract
Background: Comprehensive identification of human drug metabolites in first-in-man studies is crucial to avoid delays in later stages of drug development. We developed an efficient workflow for systematic identification of human metabolites in plasma or serum that combines metabolite prediction, high-resolution accurate mass LC-MS and MS vendor independent data processing. Retrospective evaluation of predictions for 14 14C-ADME studies published in the period 2007-January 2012 indicates that on average 90% of the major metabolites in human plasma can be identified by searching for accurate masses of predicted metabolites. Furthermore, the workflow can identify unexpected metabolites in the same processing run, by differential analysis of samples of drug-dosed subjects and (placebo-dosed, pre-dose or otherwise blank) control samples. To demonstrate the utility of the workflow we applied it to identify tamoxifen metabolites in serum of a breast cancer patient treated with tamoxifen. Results & Conclusion: Previously published metabolites were confirmed in this study and additional metabolites were identified, two of which are discussed to illustrate the advantages of the workflow. © 2013 Future Science Ltd.
Subject
Triskelion BV
ARF - Analytical Research (Food)
TNO Bedrijven
Biomedical Innovation
Health
Healthy Living
To reference this document use:
http://resolver.tudelft.nl/uuid:a21d760b-2228-4ba5-bbe5-847fd22833ad
DOI
https://doi.org/10.4155/bio.13.178
TNO identifier
478820
ISSN
1757-6180
Source
Bioanalysis, 5 (17), 2115-2128
Document type
article