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  4. Structural features of endocrine active chemicals - a comparison of in vivo and in vitro data
 
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2015
Journal Article
Title

Structural features of endocrine active chemicals - a comparison of in vivo and in vitro data

Abstract
Studies on reproductive toxicity need high numbers of test animals. Therefore, we investigated whether chemical structural features (SF) in combination with in vitro data on specific adverse outcome pathways (AOPs) may be used for predicting reproductive toxicity of untested chemicals. Using the OECD Toolbox and expert judgment, we identified 89 structure groups for 275 chemicals for which the results of prenatal developmental toxicity or multigeneration studies were present in the Fraunhofer database on Fertility and Developmental Toxicity in experimental animals (FeDTex) database. Likewise, we evaluated 220 chemicals which had been tested in reporter gene assays on endocrine ((anti)estrogenic and (anti)androgenic) properties in the CALUX® test battery. There was a large spread of effect levels for substances within the chemical structure groups for both, in vivo and in vitro results. The groups of highest concern (diphenyl derivatives, planar conjugated systems with fused rings, phenols and organophosphates) correlated quite well, however, between the in vivo and in vitro data on estrogenic activity. For the 56 chemicals represented in both databases, lowest effect doses in vivo correlated well with the estrogenic activity in vitro. These results suggest that a panel of assays covering relevant AOPs and data on metabolism and toxicokinetics may allow prediction of relative reproductive or development toxicity potency within the identified chemical structure groups.
Author(s)
Lewin, Geertje
Escher, Sylvia E.
Burg, Bart van der
Simetska, Nelly  
Mangelsdorf, Inge
Journal
Reproductive toxicology  
DOI
10.1016/j.reprotox.2014.10.009
Language
English
Fraunhofer-Institut für Toxikologie und Experimentelle Medizin ITEM  
Keyword(s)
  • category approach

  • estrogen receptor

  • reproductive toxicity

  • predictive screening

  • toxicological databases

  • structural features

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