The artificial intelligence (AI) alliance between SK Group and Nvidia is showing signs of expanding beyond semiconductors into the pharmaceutical and biotech arena.

Lee Dong-hoon, CEO of SK Biopharmaceuticals, directly said on the 22nd (local time) at the site of Bio USA about the possibility of a partnership with Nvidia, "It is true we have various considerations regarding the use of graphics processing units (GPUs), and we are breaking down the boundaries of thinking and keeping a range of innovation possibilities open."

On this day, SK Biopharmaceuticals also presented a blueprint to transform AI into a core "operating system" that leads the entire new drug research and development (R&D) process.

Lee Dong-hoon, CEO of SK Biopharmaceuticals, takes questions from Korean reporters at the BioUSA venue in San Diego, California, on the 22nd (local time)./Courtesy of Park Soo-hyun

◇ SK Biopharmaceuticals' AI strategy mirrors the Nvidia-Lilly model

The core of the "borderless innovation" hinted at by Lee is to elevate AI from a tool that assists specific tasks to an operating system that governs the research and development ecosystem itself.

In the short term, the company will create an environment where researchers collaborate with AI agents, and in the long term, it aims to establish a system in which multiple AI agents autonomously support the entire new drug development process, including candidate design, research planning, analysis, and operational optimization.

The goal is to improve research productivity by deploying AI across the entire new drug development process, including candidate design and analysis, research planning, development strategy, and operational optimization.

The industry is paying attention to the fact that this strategy aligns with the direction Nvidia recently laid out for its pharmaceutical and biotech business.

In January this year, Nvidia announced it would invest up to $1 billion (about 1.5 trillion won) over the next five years with Lilly to establish a joint AI innovation lab, setting a goal to build a "Continuous Learning System" in which laboratory data and AI hypothesis testing operate in tandem around the clock. This matches SK Biopharmaceuticals' plan to maximize productivity by automating repetitive research processes.

SK Biopharmaceuticals accumulated more than 2,000 compound synthesis data points and central nervous system (CNS) data amounting to 2.3 million pages of FDA filing materials during the development of the epilepsy treatment "Cenobamate (U.S. brand name Xcopri)." Nvidia, in its collaboration with Lilly, has evaluated vast research data and new drug development know-how as core assets.

The close partnership between SK Group and Nvidia further strengthens this view.

At a recent meeting in Korea between Chey Tae-won, chairman of SK Group, and Jensen Huang, CEO of Nvidia, Chey's eldest daughter, Chey Yoon-chung, head of business development at SK Biopharmaceuticals, and Huang's daughter, Madison Huang, senior director at Nvidia, were also present, drawing attention.

Lee Dong-hoon was also effectively the only Korean CEO invited to and to network at Nvidia's reception for global pharmaceutical companies hosted by Huang earlier this year.

◇ First step with Insilico collaboration… "Asia technology, U.S. commercialization" gains momentum

The first partner in the "innovation that breaks the mold" mentioned by Lee is Insilico Medicine, a Chinese Generative AI new drug development company.

SK Biopharmaceuticals signed a joint research contract worth up to $2.57 billion (about 4 trillion won) with Insilico to discover innovative new drug candidates in the central nervous system (CNS) neuroimmunology field. This is the first AI drug discovery (AIDD) case realized through the Open Innovation Center (OIC) launched by SK Biopharmaceuticals.

The deal structure is also differentiated from previous ones. SK Biopharmaceuticals will lead the entire development process from target selection, while deploying Insilico's advanced platform "Pharma.AI" for early discovery. The plan is to shorten the candidate derivation period by nearly 50% compared with the past.

In particular, all core assets generated during the collaboration—such as molecular design data, AI prediction validation data, and structure-activity relationship (SAR) data—will be accumulated at SK Biopharmaceuticals and used to internalize its own AI capabilities.

Lee said, "Insilico is an excellent partner that achieved the world's first human clinical proof of concept (Human PoC) for an AI-based new drug," adding, "Combined with the AI infrastructure capabilities held by SK Group, it is a structure that can fully 'win-win.'"

Insilico is also a case of the "East-West Bridge" model that SK Biopharmaceuticals is pursuing. Based on its experience as the only domestic company to develop a new drug on its own and succeed in directly commercializing it in the U.S. (Xcopri), the vision is to serve as a bridge that discovers outstanding technologies and pipelines in Asia (East) and makes them successful in the United States (West).

Lee said, "We spent nearly 30 years directly developing and commercializing Xcopri, but now we have a solid infrastructure with U.S. operations running at 100%," emphasizing, "If we stick only to internal R&D, it will take another 10 years, but we will make open innovation and AI the two pillars to dramatically increase speed and the probability of success."

As part of this strategy, SK Biopharmaceuticals recently opened a global innovation space, LinX, at its local subsidiary in New Jersey, SK Life Science. In cooperation with the Korea Trade-Investment Promotion Agency (KOTRA), the Korea Health Industry Development Institute, and others, it plans to use the site as a forward base for Korean and Asian biotech corporations to enter the U.S. market and exchange information.

Lee added, "This agreement, where Insilico's AI platform technology and SK Biopharmaceuticals' U.S. clinical and commercialization infrastructure create synergy, is a powerful proof of the 'East-West Bridge,'" and "We will evolve the 'Extended R&D Lab' model—organically using external top-tier technologies as if they were our own R&D infrastructure—into a growth platform that can be repeatedly applied whenever we discover new targets going forward."

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