Nvidia CEO Jensen Huang is expanding his company's influence far beyond graphics processors into pharmaceutical research, with SK Biopharmaceuticals emerging as a key partner in a strategy that could reshape how new drugs are discovered and developed. The South Korean biotech firm is pursuing a $2.57 billion collaboration with Insilico Medicine, a generative AI drug discovery company, while simultaneously deepening ties with Nvidia to build artificial intelligence systems that govern entire drug development pipelines rather than simply assist individual tasks.

What Is Nvidia's New Strategy in Pharmaceutical AI?

Nvidia's pharmaceutical ambitions became clearer earlier this year when the company announced plans to invest up to $1 billion over five years with Eli Lilly to establish a joint AI innovation lab. The goal is to create what Nvidia calls a "Continuous Learning System" where laboratory data and AI hypothesis testing operate around the clock in tandem. This model treats AI not as a tool that assists researchers with specific tasks, but as a foundational operating system that governs the entire research and development ecosystem.

SK Biopharmaceuticals CEO Lee Dong-hoon directly acknowledged the company's considerations regarding partnerships with Nvidia, stating that the firm is "breaking down the boundaries of thinking and keeping a range of innovation possibilities open" regarding the use of graphics processing units (GPUs), the specialized computing chips that power AI systems.

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

Lee Dong-hoon, CEO of SK Biopharmaceuticals

How Does SK Biopharmaceuticals Plan to Accelerate Drug Discovery?

SK Biopharmaceuticals' strategy involves three key phases that demonstrate how deeply AI will be embedded into biotech operations. In the short term, the company will create environments where researchers collaborate directly with AI agents. Over the longer horizon, the firm aims to establish a system where multiple AI agents autonomously support the entire new drug development process, including candidate design, research planning, analysis, and operational optimization.

The partnership with Insilico Medicine represents the first concrete step in this vision. Under the deal structure, SK Biopharmaceuticals will lead the entire development process from target selection while deploying Insilico's advanced platform called "Pharma.AI" for early discovery phases. The collaboration is designed to shorten the candidate derivation period by nearly 50 percent compared with traditional approaches.

• Data Accumulation: All core assets generated during the collaboration, including molecular design data, AI prediction validation data, and structure-activity relationship data, will be accumulated at SK Biopharmaceuticals to internalize its own AI capabilities.
• Speed Improvement: The partnership aims to reduce the time required to derive drug candidates by approximately 50 percent, a dramatic acceleration compared to conventional drug development timelines.
• Research Scope: The initial focus targets the central nervous system and neuroimmunology field, where SK Biopharmaceuticals has existing expertise from developing its epilepsy treatment Cenobamate.

Why Does SK Biopharmaceuticals' Track Record Matter?

SK Biopharmaceuticals is not a newcomer to drug development. The company spent nearly 30 years directly developing and commercializing Cenobamate, marketed in the United States as Xcopri, making it the only domestic Korean company to develop a new drug independently and successfully commercialize it in the U.S. market. During that process, the company accumulated more than 2,000 compound synthesis data points and central nervous system data amounting to 2.3 million pages of FDA filing materials.

This historical success positions SK Biopharmaceuticals as a bridge between Asian biotech innovation and U.S. commercialization expertise. Lee emphasized this advantage, noting that "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".

Lee

What Is the "East-West Bridge" Model?

SK Biopharmaceuticals is pursuing what executives call an "East-West Bridge" strategy, designed to discover outstanding technologies and pipelines in Asia and make them successful in the United States. The company recently opened a global innovation space called LinX at its New Jersey subsidiary, SK Life Science, in cooperation with the Korea Trade-Investment Promotion Agency and the Korea Health Industry Development Institute. This facility will serve as a forward base for Korean and Asian biotech corporations seeking to enter the U.S. market.

"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,'" Lee stated, adding that the company will "evolve the 'Extended R&D Lab' model into a growth platform that can be repeatedly applied whenever we discover new targets going forward."

Lee Dong-hoon, CEO of SK Biopharmaceuticals

How Does This Reflect Huang's Broader Vision?

The deepening relationship between SK Group and Nvidia extends beyond corporate partnerships. At a recent meeting in Korea between SK Group Chairman Chey Tae-won and Jensen Huang, the executives brought their adult children into the discussions: Chey Yoon-chung, head of business development at SK Biopharmaceuticals, and Madison Huang, senior director at Nvidia. Additionally, Lee Dong-hoon was effectively the only Korean CEO invited to and to network at Nvidia's reception for global pharmaceutical companies hosted by Huang earlier this year.

These personal and professional connections signal that Huang views the pharmaceutical sector as a critical frontier for AI expansion. By positioning Nvidia's GPU infrastructure and AI expertise as foundational to drug discovery workflows, Huang is creating a new revenue stream and deepening Nvidia's integration into industries far beyond gaming and data centers. SK Biopharmaceuticals' willingness to embrace this model suggests that biotech companies increasingly see AI-driven drug discovery not as a supplementary tool but as essential infrastructure for competitive survival.

The convergence of Nvidia's computing power, SK Biopharmaceuticals' regulatory and commercialization expertise, and Insilico's generative AI drug discovery platform represents a significant shift in how pharmaceutical innovation may unfold over the next decade. Rather than relying solely on traditional laboratory research, companies are building AI systems that can autonomously generate, test, and optimize drug candidates at scales and speeds previously impossible.