Mokam Life Science Institute, a nonprofit research foundation under GC Biopharma, said on the 12th it was selected as a participating research institution for the government's national research and development (R&D) project, "Building and validating an end-to-end multi-agent AI platform for AI-Medicine drug discovery."
The project, led by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF), aims to build a multi-agent AI platform that spans the entire drug discovery process from target identification to preclinical candidate selection.
Mokam Institute said it is focusing on building a system in which AI agents based on large language models (LLMs) collaborate to autonomously carry out key decision-making across the drug discovery process.
A security framework tailored to the characteristics of the pharmaceutical industry will also be applied. The plan is to implement a hybrid system that combines an on-premises secure AI agent handling sensitive data with a commercial LLM.
In this project, Mokam Institute will develop a preclinical-stage AI agent and an artificial intelligence model for target identification. Beyond a simple participating role, it will also design the autonomy of the end-to-end decision-making structure for AI-based drug discovery.
In collaboration with researchers at the Korea Research Institute of Bioscience and Biotechnology (KRIBB), it also plans to develop AI agents based on preclinical pharmacokinetics and drug property data and a system to support regulatory responses.
It also plans to build a multi-agent-based coordination system to reduce the limitations of conventional AI drug discovery that were segmented by stage and contribute to building an end-to-end integrated platform.
Shin Hyeon-jin, head of Mokam Institute, said, "This project will serve as an opportunity to reorganize data use and decision-making methods across the end-to-end drug discovery process," adding, "We will help strengthen the competitiveness of Korea's pharmaceutical and biotech industries by advancing the AI-based drug discovery platform."