Abstract
Along with the development of computer and artificial intelligence technology, informatics research that utilizes a huge amount of accumulated data is also attracting attention in the medical and health fields. In the safety evaluation of various chemical substances such as pharmaceuticals, the development of new toxicity prediction approach is an important issue from the viewpoint of improving the efficiency of toxicity tests and animal welfare. Therefore, it is necessary to develop human resources who are familiar with handling in silico prediction models that combine toxicity-related big data and artificial intelligence technology. Our laboratory focuses on toxicity-related databases and machine learning from the perspective of regulatory science, and is working on in silico research to predict the toxicity of chemical substances and side effects in humans. In this symposium, based on my own experience, I will explain the development of in silico research using computational toxicology that incorporates chemical toxicity information and machine learning, based on the field of organic chemistry. In addition, I would like to introduce the education for students in our laboratory.
