Prediction of Complex Systemic Toxicity Without Use of Experimental Animals

Predictive Toxicology

For providing safe and secure products to consumers, it is vital to determine in detail the safety of the materials to be used. On the other hand, it is also important to minimize the burden of safety testing. In an effort to improve the lifestyle of consumers through elaborate safety assessments, Kao has been advancing development of evaluation methods for products and raw materials without use of experimental animals.

It is considered difficult to predict the various systemic effects of chemical substances on the human body using only in vitro testing, as it is also necessary to examine the effects on multiple organs. We have utilized various approaches, such as a computer-assisted technique for examining toxicity on the basis of the chemical structure of a material and existing toxicological information, as well as in vitro techniques for detailed analysis of the effects on organs using biological samples and cultured cells. In order to solve these difficult problems, understanding of the systemic effects from micro to macro levels is key.

Currently, a predictive technique for assessing the systemic toxicity of these technologies combines the “read-across” toxicity prediction method, which infers the toxicity of a substance from existing toxicological information of chemically and biologically similar substances, with simulation methods that predict the physiological kinetics of substances exposed to the body. These integrated approaches are being utilized for risk assessment based on a comprehensive understanding of toxicity.

The knowledge and research findings obtained from this research have contributing to create a new framework for international next-generation risk assessment through discussions with toxicology experts, various industry associations, and regulatory authorities.

This is a conceptual diagram of integrated understanding to predict systemic toxicity. By combining in vitro techniques and data science, it aims to predict toxicological effects related to organs, cells, and constituent molecules.

This is a figure explaining the representative toxicity prediction method known as read-across. When toxicity is unknown for a substance, if toxicity information is known for substances with similar chemical structures, toxicity can be inferred without conducting animal experiments by extrapolating known toxicity values.

This is a figure explaining the predictive methods for systemic substance dynamics. Dynamic parameters based on physicochemical indicators such as absorption and metabolism are combined with dynamic modeling reflecting the characteristics of each organ to simulate blood concentration profiles.

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