Key Read Across Framework Components and Biology Based Improvements

At the 2019 annual meeting of the European Environmental Mutagen and Genomics Society a workshop session related to the use of read across concepts in toxicology was held. The goal of this session was to provide the audience an overview of general read-across concepts. From ECHA’s read across assessment framework, the starting point is chemical similarity. There are several approaches and algorithms available for calculating chemical similarity based on molecular descriptors, distance/similarity measures and weighting schemata for specific endpoints. Therefore, algorithm that “adapts itself” to the data (endpoint/s) and provide a good ability to distinguish between structural similar and not similar molecules regarding specific endpoints are needed and their use discussed. Toxico-dynamic end point are usually in the focus of read across cases. However, without appropriate attention to kinetics and metabolism such cases are unlikely to be successful. To further enhance the quality of read across cases new approach methods can be very useful. Examples based on a biological approach using plasma metabolomics in rats are given. Finally, with the availability of large data sets of structure activity relationships, in silico tools have been developed which provide hitherto undiscovered information. Automated process is now able to assess the chemical – activity space around the molecule target substance and examples are given demonstrating a high predictivity for certain endpoints of toxicity. Thus, this session provides not only current state of the art criteria for good read across, but also indicates how read-across can be further developed in the near future.

BALL Nicholas;  MADDEN Judith;  PAINI Alicia;  MATHEA Miriam;  PALMER Andrew D.;  SPERBER Saskia;  HARTUNG Thomas;  VAN RAVENZWAAY Bennard; 

2020-04-21

ELSEVIER SCIENCE BV

JRC118949

1383-5718 (online),   

https://publications.jrc.ec.europa.eu/repository/handle/JRC118949,   

10.1016/j.mrgentox.2020.503172 (online),