Proceedings:
Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools
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Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools
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Abstract:
The widespread concern about the hazard to human health and the environment posed by chemicals has become over the past few years a priority issue, recognized by international organizations, governments and industry. Criteria for hazard and risk assessment of plant protection products (PPPs) for registration at EU level are established by Council Directive 91/414/EEC. The assessment of hazard for a substance is based on the comparison of the predicted exposure with the no effect-concentration of the compound to some suitable indicator species. Data on toxicity and ecotoxicity of the substance have to be provided, including data on mammalians (acute, subacute and chronic toxicity, teratogenicity, mutagenicity and carcinogenicity) and data on a wide range of non-target species in the environment (birds, wild mammals, fish, aquatic invertebrates, beneficial arthropods, earthworms and soil microorganisms). This huge amount of experimental data requested involves high costs for the PPP company, in terms of both time and money (7-10 years and 30-40 milion dollars). The interest of PPP companies for predictive tools is therefore high. Suggestions from the point of view of a PPP company on how predictive efforts could be addressed and on data sources that could be used are presented.
Spring
Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools