“Artificial intelligence (AI)” emerged as the most dominant keyword of 2025, appearing 524 times across Hit News coverage. More than a buzzword, AI firmly established itself as a mega-trend reshaping the biotech industry’s structure.

Momentum accelerated as expectations moved closer to reality: for the first time, an AI-designed drug candidate demonstrated meaningful efficacy in clinical trials. As global big pharma and Korean drugmakers expanded AI adoption, government support followed—laying the groundwork through AI-based drug review systems and large-scale consortia.

AI’s rise reshaped both regulation and investment. Early this year, the U.S. Food and Drug Administration (FDA) formalized AI-driven New Approach Methodologies (NAMs) and unveiled a roadmap to gradually phase out animal testing in drug development. The move signaled a regulatory shift toward enabling clinical entry using tools such as AI-based toxicity prediction.

At the same time, experts cautioned that NAMs are unlikely to fully replace animal testing in the near term, instead serving as complementary tools—underscoring the practical hurdles ahead.

Investment activity mirrored regulatory change. Global drugmakers including AstraZeneca, Merck, and Pfizer signed multi-billion-dollar partnerships with AI drug-discovery firms, aiming to shorten timelines and improve R&D success rates.

Regulatory momentum gained substance with clinical proof. Insilico Medicine published Phase 2a results for rentosertib—an AI-designed treatment for pulmonary fibrosis—in Nature Medicine.

The study marked the first case in which an AI-designed drug candidate demonstrated both safety and meaningful efficacy in humans, including improvements in forced vital capacity (FVC). AI led the entire process, from target discovery to molecule design.

By compressing discovery timelines from the traditional 4–6 years to 18 months and reaching early clinical development within 30 months, the results highlighted the disruptive speed of AI-driven drug development—and fueled discussion of a coming “pharmaceutical superintelligence” era.

Korean pharmaceutical companies moved quickly to deepen AI collaborations, pursuing a dual strategy: improving R&D efficiency while generating new revenue through AI-based digital healthcare.

Companies including Yuhan, JW Pharmaceutical, and Dong-A ST signed joint R&D agreements with AI startups and platform providers. Yuhan is applying AI to biomarker discovery and patient stratification in oncology, while Dong-A ST is leveraging AI-based organoid and genomic analysis in early research to overcome the limits of animal testing. Boryung is also expanding AI use to identify new indications for approved drugs such as Kanarb.

Daewoong Pharmaceutical stood out by translating AI into commercial results. Its smart hospital bed-monitoring solution thynC, launched after establishing a digital healthcare division last October, has secured more than 8,000 beds. Combining lightweight wearables with AI, thynC enhances monitoring of critically ill and bedridden patients while improving workflow efficiency for medical staff.

Policy support further reinforced the AI biotech ecosystem. In August, the Jae-myung Lee administration unveiled its “AI Economic Transformation” agenda, positioning biohealth as a strategic priority. A key initiative is the development of an AI-based drug review system to automate tasks such as data verification and draft preparation, improving regulatory efficiency.

Large-scale national projects are also advancing. The Ministry of Science and ICT selected a Lunit-led consortium to develop an AI-specialized foundation model. The group—comprising 23 partners from industry, academia, research institutes, and hospitals, including Lunit, Kakao Healthcare, and SK Biopharm—will be equipped with 256 NVIDIA B200 GPUs.

The medical-science-focused foundation model is expected to support clinical decision-making systems (CDSS) and collaborative drug discovery, positioning Korea to compete for global leadership in medical AI.

This year marked a clear inflection point. FDA regulatory innovation, aggressive global investment, expanded AI collaborations among Korean drugmakers, and government backing for AI-based review systems converged to form a robust foundation for AI-driven biotech innovation.

With technology and policy reinforcing each other, the era of AI-powered drug development—defined by unprecedented speed and efficiency—has already begun. The remaining question is whether this foundation will deliver the first true “AI blockbuster” drug.