Developing Methods to Predict Chemical Fate and Effect Endpoints for Use Within REACH


  • Kathrin Fenner
  • Silvio Canonic
  • Beate I. Escher
  • Lukas Gasser
  • Simon Spycher
  • Holger C. Tülp



Biodegradability prediction, Chemical property prediction, Indirect phototransformation, Mode-of-action classification, Polyparameter linear-free-energy relationships, Reach


With the pending implementation of REACH, both old and new chemicals will have to be registered and chemical safety reports will have to be compiled. Depending on the yearly tonnages produced or imported, (eco-) toxicological and chemical fate data of varying degrees of detail will have to be produced. It has been forecast that these new requirements will result in higher costs for registration and an increased need for animal testing. Some of this additional workload could be avoided by making use of in vitro or in silico prediction methods. At Eawag (Swiss Federal Institute of Aquatic Science and Technology) several research groups are working on the development and validation of quantitative structure–activity relationships (QSARs) and related methods to predict ecotoxicological and fate endpoints, such as reactivities in or partitioning between different environmental media, based on chemical structure or easily measurable physico-chemical properties. When developing such tools, special attention has to be paid to use only descriptors whose mechanistic significance for the modelled endpoint is well understood on a molecular level. In this article four examples of our work in the field of compound fate and effect predictions will be presented: i) the measurement of compound descriptors for use in linear-free-energy relationships to predict partition coefficients between environmental media; ii) the development of free-energy relationships for the prediction of indirect photolysis; iii) the evaluation of existing structure-biodegradability models to predict soil biodegradation half-lives; and iv) the application of mode-of-action-based test batteries to develop quantitative structure–activity relationships to classify chemicals according to their modes of toxic action.




How to Cite

K. Fenner, S. Canonic, B. I. Escher, L. Gasser, S. Spycher, H. C. Tülp, Chimia 2006, 60, 683, DOI: 10.2533/chimia.2006.683.