Host: The Japanese Society of Toxicology
Name : The 47th Annual Meeting of the Japanese Society of Toxicology
Date : 2020 -
The safety of pharmaceuticals, general chemicals, and food materials has been evaluated in an integrated manner mainly by combining in vitro and in vivo experimental data, in silico toxicity predictions, knowledge of experts in various fields, and cases reported in the literature.
For safety assessments using in silico systems, both the AI system that outputs the final results and the use of scientifically explainable AI techniques and computer systems based on the mechanism of action are useful.
Pathway ontology and experimental information considering each hierarchy of molecular, cellular, organelle, and organ levels is useful as data on the mechanism of toxicity. This information includes the molecular initiating event involving the binding of a compound to biomolecules based on the adverse outcome pathway concept. This information also includes the key event connected to the mechanism of toxicity and adverse outcomes comprising adverse events such as toxicity.
In addition, to evaluate in vivo safety in humans and rats, it is necessary to incorporate information on the mechanism of action of based on the ADME concept (absorption, distribution, metabolism, and elimination) in the body, the mechanism of drug metabolism, and kinetics such as the formation, conjugation, and production of reactive metabolites. Because the onset of the toxicity of compounds distributed to organs is largely influenced by the amount and duration of exposure in the organs, it is important to consider a range of action mechanisms from pharmacokinetics to toxicity by utilizing information including the concentration profiles of each organ based on physiological models.
The current status and future prospects of computer systems and AI technologies for safety assessments based on the mechanism of action from pharmacokinetics to toxicity and experimental information are presented together with examples of current activities.
Some R & D in this presentation was supported by the Ministry of Economy, Trade and Industry "Development of evaluation technology for energy-saving electronic device materials" (Development of high-speed, high-efficiency safety evaluation technology to support social implementation of functional materials and development of next-generation safety prediction methods using artificial intelligence using toxicological big data).
