Korean pharmaceutical and biotech companies are accelerating the adoption of artificial intelligence (AI) across the entire drug development process, including discovering new drug candidates, expanding indications, and automating production. Given that drug development takes an average of more than 10 years with high clinical failure rates, reducing trial and error from the early stages of target discovery and candidate screening has emerged as a key factor determining corporate competitiveness.
Celltrion (068270.KS) announced on the 26th that it will fully introduce customized AI across three major business areas: drug development, manufacturing, and administration. The company aims to accelerate AI transformation (AX) to reduce time and costs while improving work efficiency. Last year, Celltrion established a dedicated organization for AI-based drug development and has been gradually applying AI to the discovery, validation, and optimization of new drug target candidates. To support this, the company is conducting "reskilling" training for in-house researchers to enhance their data analysis and AI utilization capabilities, while also pursuing open innovation with external AI specialist firms to accelerate pipeline construction.
In the manufacturing sector, the company will apply physical AI to its new active pharmaceutical ingredient plants No. 4 and No. 5, which are scheduled to be built in Songdo. It plans to raise the level of factory automation by introducing autonomous mobile robots (AMR), automated logistics warehouses, intelligent robotic arms, and collaborative robots. In the long term, the company is also reviewing the deployment of humanoids to unmanned operations for high-difficulty tasks. In the administrative area, the company expects, based on simulation results, that time spent on simple tasks such as document searches and document comparisons will decrease by 80 to 90 percent compared to the current level.
Traditional pharmaceutical companies that have previously built their own AI platforms are actively utilizing AI for candidate discovery and producing tangible results. Hanmi Pharmaceutical (128940.KS) is accelerating drug development using its in-house AI platform "HARP." Notably, the company is reported to have shortened the candidate discovery period for "HM17321," an obesity treatment currently in Phase 1 clinical trials, to as little as 80 percent of the previous timeline. JW Pharmaceutical (001060.KS) is also using "JWave," an AI-based drug development platform with data on more than 45,000 compounds, to support candidate exploration and preclinical stages. The company recently confirmed the potential to restore impaired signal transduction function in preclinical research on "DDC-02," a candidate drug for a rare pediatric brain disease discovered through JWave.
Daewoong Pharmaceutical (069620.KS), the first in the pharmaceutical industry to form a dedicated AI organization, operates "DAISY," an AI drug development platform based on a compound database of 800 million substances. Yuhan Corporation (000100.KS) has also been automating candidate design, screening, and optimization processes through its in-house platform "Universe" since this year. The company aims to unveil a complete system in the first quarter of 2027.
In addition to building proprietary platforms, collaborations with external AI specialist firms are also active. GC Biopharma (006280.KS) last month launched a joint development project with AI drug development firm Galux for an antibody drug to treat autoimmune diseases. Olix (226950.KQ) also signed a memorandum of understanding (MOU) with Galux for the joint development of an AI-based next-generation small interfering RNA (siRNA) delivery platform. Chong Kun Dang (185750.KS) has built an automated system for preparing Annual Product Quality Review (APQR) reports using "AgenticWorks," LG CNS's enterprise agentic AI platform. The scope of AI utilization is thus expanding from candidate discovery to manufacturing and management areas such as quality control and document automation.
Pharmaceutical and biotech companies are accelerating AI adoption to ease the burden of cost and time pressures. Drug development takes an average of 10 to 15 years and enormous costs, but the clinical failure rate reaches 90 percent. However, deploying AI can significantly reduce the time. The Korea Health Industry Development Institute previously estimated that introducing AI to drug development could reduce development costs from 3 trillion won to 600 billion won, and the development period from 12 years to 7 years. Accordingly, as AI demand expands across drug development and overall research and development (R&D), the market is also growing. The Korea Biotechnology Industry Organization forecasts that the global AI-based biotechnology market will grow 6.5-fold over 11 years from 2024, reaching 34 trillion won by 2035.
However, some assessments note that AI utilization by domestic pharmaceutical and biotech companies is still in its early stages. Lee Seung-kyu, vice chairman of the Korea Biotechnology Industry Organization, said, "There is a lot of R&D approaches such as drug screening for candidate discovery," but added, "Compared to AI drug development in the global market, which is at Phase 2 and Phase 3 clinical stages, it is still at a rudimentary level." He stressed, "For the domestic AI drug development ecosystem to develop, the establishment of data collection and processing systems must come first."
