Risk assessment of xenobiotics is a qualitative and quantitative assessment of toxic properties conventionally based on data resulting from tests in animals exposed to the substance. The assessment of dose-effect relationship includes evaluation of exposure at the site of action. More recently, emphasis is put on understanding the relationship between exposure at the site of action and the resulting effect, i.e. toxicodynamic. In this respect, results from genotoxicity studies may be a measure for exposure and at the same time of an effect. Results of toxicodynamic endpoints such as binding to receptors or release of hormones have been used when replacing default values for interspecies extrapolation. It may also be envisaged to use toxicodynamic endpoints in order to get an estimate of intraspecies variability. It was demonstrated that this approach may be helpful only if the relationship between the toxicodynamic endpoint and the definite endpoint is known by using the example of bisphenol A. Whereas there are clear effects of bisphenol A in in vitro and ex vivo studies, the classical two generation study has not been able to detect an effect on reproduction and/or fertility. Looking in the future development of toxicodynamic endpoints, gene profiling and the analysis of proteins ('proteomics') may be helpful tools employed in screening and being related to the mode of action are explored for their suitability in terms of toxicodynamic endpoints.
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http://dx.doi.org/10.1016/s0378-4274(01)00291-0 | DOI Listing |
Environ Sci Technol
December 2024
Osnabrück University, Barbarastr. 12, 49076 Osnabrück, Germany.
The immense production of the chemical industry requires an improved predictive risk assessment that can handle constantly evolving challenges while reducing the dependency of risk assessment on animal testing. Integrating omics data into mechanistic models offers a promising solution by linking cellular processes triggered after chemical exposure with observed effects in the organism. With the emerging availability of time-resolved RNA data, the goal of integrating gene expression data into mechanistic models can be approached.
View Article and Find Full Text PDFEnviron Res
December 2024
Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Pesticide and Environmental Toxicology, Zhejiang University, Hangzhou, 310058, China. Electronic address:
Pyrethroid insecticides are a class of endocrine disruptors and are believed to exhibit reproductive toxicity to aquatic organisms. Pyrethroids are widely detected in aquatic environments and can accumulate in aquatic organisms, but studies on their accumulation and the associated reproductive toxicity in aquatic organisms are still limited. We utilized Carassius auratus and Xenopus laevis as models for fish and amphibians, respectively, and developed and validated a physiologically based toxicokinetic and toxicodynamic (PBTK-TD) model for adult fish and frogs exposed to typical pyrethroid pesticides cis-bifenthrin (cis-BF).
View Article and Find Full Text PDFEcotoxicology
December 2024
National Centre for Coastal Research, NIOT Campus, Ministry of Earth Sciences, Govt. of India, Chennai, India.
Toxicol In Vitro
December 2024
University of York, Dept. Environment & Geography, York, YO10 5NG, UK; Syngenta Crop Protection AG, Rosentalstrasse 67, 4058 Basel, Switzerland.
Repeated dietary dose testing is used to assess longer term toxicity of chemicals, such as pesticides, to mammals. However, the internal pesticide concentration varies significantly as feeding rate relative to body size fluctuates over time. Toxicokinetic-toxicodynamic (TK-TD) models can estimate internal toxicant concentration over time and link this directly to observed effects on endpoints such as the growth rate of laboratory rats.
View Article and Find Full Text PDFEnviron Toxicol Chem
November 2024
Syngenta Crop Protection, Basel, Switzerland.
Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g.
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