“Reducing Development Costs and Risks” — K-Bio Bets on AI Teams and Platforms

AI-Discovered Drug Candidates Show 80–90% Phase 1 Clinical Success Rates
Drug Development Costs Fall Sharply from KRW 3 Trillion to KRW 600 Billion
Samsung Biologics Launches Company-Wide AI Training
Yuhan’s ‘Universe’ and Hanmi’s ‘HARP’
Korean Bio Companies Race to Gain Market Advantage with Proprietary AI Platforms

Reporter: Lee Yeon-su
Published: April 12, 2026, 5:20 PM
Updated: April 12, 2026, 11:43 PM
Print Edition: Page 14

Korea’s pharmaceutical and biotechnology industries are accelerating efforts to establish dedicated AI organizations and proprietary platforms, positioning artificial intelligence as a key driver of next-generation growth. As AI applications expand from drug discovery and clinical prediction to data analysis, companies are increasingly seeking to strengthen in-house capabilities rather than relying solely on external partnerships.

According to industry sources on the 12th, Samsung Bioepis recently conducted AI capability training for all employees, marking the company’s first company-wide AI education initiative. Going forward, Samsung Bioepis plans to form task forces led by its dedicated AI organization to develop AI agents tailored to the specific needs of each division and team, while continuing to apply AI to the discovery of new drug candidates.

Yuhan Corporation is also automating candidate design, screening, and optimization through its proprietary AI drug discovery platform, “Universe.” The company plans to unveil a fully integrated version of the system in the first quarter of 2027. Its strategy is to reduce trial and error from the earliest stages of candidate discovery and improve both the quality and probability of success of its preclinical pipeline.

A Yuhan representative said, “We are currently preparing to launch a dedicated AI platform organization this year,” adding that the company also plans to strengthen staffing through external recruitment and the reassignment of existing employees.

Hanmi Pharmaceutical is likewise generating drug development results through its in-house AI platform, HARP. A company representative said that HARP helped accelerate the development of the obesity treatment candidate HM17321, reducing development time by as much as 80% compared with conventional approaches.

HM17321 is being developed as a potential first-in-class therapy designed to reduce body fat while increasing muscle mass and is currently undergoing global Phase 1 clinical trials.

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Daewoong Pharmaceutical, the first company in Korea’s pharmaceutical industry to establish a dedicated AI organization, operates DAISY, an AI-powered drug discovery platform built on a database of approximately 800 million compounds, with a focus on shortening the time required to identify promising drug candidates. JW Pharmaceutical is also using its JWave platform, which contains data on more than 45,000 compounds, to support candidate discovery and preclinical development.

Korean pharmaceutical and biotechnology companies are strengthening their AI capabilities largely because of the potential to significantly reduce the cost of new drug development. Applying AI to the traditionally lengthy and expensive drug development process can accelerate candidate discovery while lowering the probability of failure. Industry observers increasingly view AI not simply as a research support tool, but as core infrastructure capable of improving the return on investment in drug development. At the J.P. Morgan Healthcare Conference (JPM) earlier this year, the use of AI in drug discovery was highlighted as one of seven key industry themes.

According to research by the Boston Consulting Group, AI-discovered drug candidates have achieved Phase 1 clinical trial success rates of approximately 80–90%, significantly higher than the conventional industry average of roughly 40–60%. The Korea Health Industry Development Institute (KHIDI) estimates that introducing AI into drug development could reduce development costs from KRW 3 trillion to KRW 600 billion and shorten development timelines from 12 years to seven years. Given the enormous cost of bringing a new drug to market, even modest reductions in development time and improvements in clinical success rates could translate into savings worth trillions of won.

The drive to build in-house AI capabilities is gaining further momentum alongside rapid market growth. In its brief, “Current Status and Outlook of the Global AI-Based Biotechnology Market,” the Korea Biotechnology Industry Organization projected that the global AI biotechnology market will grow 6.5-fold over the 11 years following 2024, reaching approximately KRW 34 trillion by 2035. The adoption of AI for drug development and biological data analysis is expected to continue expanding.

The securities industry also sees AI internalization as an increasingly important factor in determining the competitiveness of Korean pharmaceutical and biotechnology companies. Han Yong-hee, a researcher at Growth Research, said, “AI can dramatically reduce the time and cost required for drug development. In particular, customized AI models can accelerate the discovery of early-stage candidates optimized for specific targets and simulate hundreds of millions of combinations to identify candidates with a higher probability of success.”

Industry observers expect Korean pharmaceutical and biotechnology companies to continue accelerating investment in dedicated AI organizations, proprietary platforms, and other AI-based infrastructure.