Is Korea's Counterattack Beginning as a Latecomer in 'AI Drugs'? Focus on Clinical and Big Data Strengths

Samsung Bioepis, Hanmi Pharmaceutical, GC Green Cross, and Others
Securing Government AI R&D Projects in Succession

The South Korean industry, previously considered a latecomer in the field of artificial intelligence (AI)-based drug development, is signaling a counterattack. As the government launches the 'K-AI Drug Development Research and Development (R&D)' project in earnest, major companies and institutions such as Samsung Bioepis, Hanmi Pharmaceutical, GC Green Cross, and Lunit are successively participating in key projects. The industry expects that this government-led R&D initiative will serve as a catalyst for building an AI-based ecosystem that spans from the discovery of new drug candidates to clinical validation.

According to industry sources on November 10, the consortium of Samsung Bioepis, Proteina, and Seoul National University’s project, 'Development and Demonstration of Antibody Biopharmaceuticals Using AI Models,' is drawing particular attention among the national projects, as it aims to bring AI-developed drug candidates into clinical trials within two years. The consortium plans to combine AI antibody design technology with an antibody validation platform to develop ten antibody drug candidates and advance at least one of them to the clinical stage by 2027. For AI-based antibody design to progress to actual clinical trials, expertise in CMC (chemistry, manufacturing, and controls) processes and experience with global regulatory requirements are essential. Samsung Bioepis’s accumulated experience in global clinical trials and regulatory approvals is seen as a stabilizing factor for the project.

GC Green Cross and the Mogam Institute for Biomedical Research are developing a joint disease prediction model for domestic hemophilia patients based on real-world patient data. Patient data accumulated over more than 20 years is considered a core asset in AI drug development. Building this model will serve as a testbed to confirm that AI can enhance predictive accuracy in real clinical settings.

Hanmi Pharmaceutical is taking on a key role as a partner institution in the 'Development of AI Software for Reverse Translational Research Design' project led by Samsung Medical Center. Reverse translational research refers to an approach that feeds data obtained from clinical trials back into the preclinical stage to improve the accuracy and efficiency of drug development. In this project, Hanmi Pharmaceutical will provide data accumulated through long-term new drug research in oncology and metabolic diseases and will also generate new preclinical multimodal data. The plan is to establish a virtuous cycle structure in which experimental results are validated by comparing them with AI-generated hypotheses and new candidate substances. Lunit, a leader in AI-based medical technology, is also developing a foundation model (generative AI) that connects molecular, protein, pharmaceutical, and clinical knowledge.

The industry views the current collaboration among government, corporations, and academia as the beginning of the 'demonstration and commercialization phase of AI drug development.' Unlike the past, when efforts were limited to building technology-based platforms, AI drug development is now entering a phase where actual data generation, model validation, and clinical application are taking place, spurred by national projects. In particular, the multi-institutional joint research structure aligns with the government’s strategy to integrate the entire drug development process with AI, accelerating the reorganization of the domestic ecosystem.

Chinese companies are securing a leading position in the AI drug market by signing a series of large-scale AI-based drug technology transfer and cooperation agreements with global big pharma, each worth over 10 trillion won. The United States and Europe are also intensifying their competition to advance these technologies. Global companies are making large-scale investments across all areas, including AI-based candidate design, toxicity prediction, indication expansion, and clinical design.

Although South Korea is a latecomer in AI drug development, its bioindustry has rapidly accumulated global clinical experience in the CDMO (Contract Development and Manufacturing Organization) and biosimilar sectors. In addition, world-class hospitals and medical institutions possess vast patient big data. An industry insider commented, "In the future, AI drug development will become a competition based on the speed at which pipelines enter clinical trials," adding, "I believe Korea’s AI drug development ecosystem is now on the threshold of a full-fledged growth phase."