Mokam Life Science Research Institute Holds AI Drug Development Symposium

Kim Seon, Director of Mokam Life Science Research Institute, Shin Jin-woo, Professor at Korea Advanced Institute of Science and Technology (KAIST), Kang Jae-woo, Professor at Korea University, Jung Jae-wook, Head of GC Green Cross RED Division, and Shin Hyun-jin, Deputy Director of Mokam Research Department (from left), are discussing at the 'Artificial Intelligence for New Drug Development' symposium held on the 27th.

[Asia Economy Reporter Chunhee Lee] The Mokam Life Science Research Institute announced on the 29th that it held a symposium on "Artificial Intelligence for Drug Discovery" on the 27th. The event was organized to bring together leading domestic AI experts and drug development specialists to share various AI technologies for efficient drug development and to promote industry-academia collaboration.

The symposium began with a presentation by Jaewook Jung, Head of Research and Early Development (RED) at GC Green Cross, who shared the latest trends in discovering new drug candidates and developing various modalities (therapeutic approaches), and explained ways to utilize AI in drug development.

Following this, AI experts including Jinwoo Shin, Professor of Electrical and Electronic Engineering at the Korea Advanced Institute of Science and Technology (KAIST) College of Engineering, and Jaewoo Kang, Professor of Computer Science at Korea University College of Informatics, participated as speakers. They mainly presented research on predicting the characteristics of substances with high drug potential using AI technologies, designing and optimizing drugs, and discovering synergistic drug combinations.

During a one-hour panel discussion led by Hyunjin Shin, Deputy Director of the Mokam Research Institute, the speakers discussed what AI is that enables success in drug development, the current status of AI-based drug development, and the desirable future outlook.

Seon Kim, Director of the Mokam Research Institute, stated, "AI will be widely used to analyze the chemical properties of drugs, protein structures, and genetic characteristics," adding, "We plan to utilize AI in drug development by establishing cell modeling strategies that integrate multiomics data."