bIdentifying numbers used in the Registry of Toxic Effects of Chemical Substances (RTECS) database of toxicity information.
This paper documents the development of a database on Mn toxicity designed to support the application of categorical regression techniques.
In the database, EWG checks product ingredients against available studies and government databases on chemical toxicity, then assigns a score of one to 10 to each product based on more than a dozen criteria related to its relative hazard and how much information is available about the product and its ingredients.
An improved database on individual chemical toxicity developed using new techniques or end points (e.g., genetics, endocrine testing) may improve the assessment of individual chemicals and aid in the development of computer models.
Because toxicogenomics data will be most valuable for predictive toxicology and elucidating toxicologically relevant MOAs for additional chemicals, a future database should be based on toxicity testing and monitoring protocols commonly used for regulatory purposes (e.g., global pesticide registrations), as well as chemicals with well-known MOAs such as 17β-estradiol and dioxin.
Conclusions based on structure activity relationships and the detailed toxicity database on the parent AI should be included.
The Dutch National Institute for Public Health and the Environment (RIVM) e-toxBase is a database containing aquatic toxicity, terrestrial toxicity, and BCF data.
For example, users can retrieve the information on toxicity, risk assessment, and environmental properties of the chemicals using chemical databases.
Since we are looking for borderline chemicals within the REACH database which are, in the first case, not SVHC, all vPvB substances can already be excluded from further investigations on toxicity.
The levels permitted vary among substances, depending on toxicity tests in animals.
