Metabolomics: A tool for early detection of toxicological effects and an opportunity for biology based grouping of chemicals-From QSAR to QBAR

被引:83
作者
van Ravenzwaay, B. [1 ]
Herold, M. [2 ]
Kamp, H. [1 ]
Kapp, M. D. [1 ]
Fabian, E. [1 ]
Looser, R. [2 ]
Krennrich, G. [3 ]
Mellert, W. [1 ]
Prokoudine, A. [2 ]
Strauss, V. [1 ]
Walk, T. [2 ]
Wiemer, J. [2 ]
机构
[1] BASF SE, Expt Toxicol & Ecol, D-67056 Ludwigshafen, Germany
[2] Metanomics GmbH, D-10589 Berlin, Germany
[3] BASF SE, Sci Comp, D-67056 Ludwigshafen, Germany
关键词
Metabolomics; Metabolite profiling; Mode of action; Chemical grouping; QBAR; ENZYME-INDUCTION; THYROID TOXICITY; METABOLISM; ACID; SYSTEMS; GENDER; MCPA; RAT;
D O I
10.1016/j.mrgentox.2012.01.006
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 [微生物学]; 090105 [作物生产系统与生态工程];
摘要
BASF has developed a Metabolomics database (MetaMap (R) Tox) containing approximately 500 data rich chemicals, agrochemicals and drugs. This metabolome-database has been built based upon 28-day studies in rats (adapted to OECD 407 guideline) with blood sampling and metabolic profiling after 7, 14 and 28 days of test substance treatment. Numerous metabolome patterns have been established for different toxicological targets (liver, kidney, thyroid, testes, blood, nervous system and endocrine system) which are specific for different toxicological modes of action. With these patterns early detection of toxicological effects and the underlying mechanism can now be obtained from routine studies. Early recognition of toxicological mode of action will help to develop new compounds with a more favourable toxicological profile and will also help to reduce the number of animal studies necessary to do so. Thus this technology contributes to animal welfare by means of reduction through refinement (2R), but also has potential as a replacement method by analyzing samples from in vitro studies. With respect to the REACH legislation for which a large number of animal studies will need to be performed, one of the most promising methods to reduce the number of animal experiments is grouping of chemicals and read-across to those which are data rich. So far mostly chemical similarity or QSAR models are driving the selection process of chemical grouping. However, "omics" technologies such as metabolomics may help to optimize the chemical grouping process by providing biologically based criteria for toxicological equivalence. "From QSAR to QBAR" (quantitative biological activity relationship). (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:144 / 150
页数:7
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