MNCs Rush into China's AI-Driven Drug Discovery — The Beginning of a New Era

On March 30, 2026, a piece of news shook the biopharmaceutical industry—Eli Lilly and Insilico Medicine reached an agreement on aA drug discovery collaboration with a total potential value of up to approximately $2.75 billion, including an upfront payment of up to $115 million.

Under the agreement, Eli Lilly will obtain an exclusive global license to develop, manufacture, and commercialize a novel oral therapeutic agent currently in preclinical development for specific indications, with the potential to be “best-in-class.”

Furthermore, Insilico Medicine and Eli Lilly will collaborate on multiple R&D projects targeting indications selected by Eli Lilly, leveraging Insilico Medicine’s AI platform.

From XtalPi’s First Annual Profit to Insilico Medicine’s Blockbuster Partnership with Eli Lilly, the AI Drug Discovery IndustryTransitioning from "technological accumulation" to the critical stage of "commercial value validation."

Ren Feng, Co-CEO and Chief Scientific Officer of Insilico Medicine, stated in an interview with VCBeat that traditional innovative drug development is facing the dilemma of “having picked all the low-hanging fruit”—characterized by lengthened cycles, declining efficiency, soaring costs, and shrinking returns. Relying solely on human knowledge and experience is no longer sufficient to address increasingly complex targets and mechanisms. Consequently, an industry consensus is emerging: breakthroughs can only be achieved by leveraging algorithms, data, and artificial intelligence to overcome these bottlenecks.

“AI drug discovery has now moved from the phase of technological accumulation to that of industrial implementation,” emphasized Ren Feng.The AI drug discovery industry is at a critical juncture of clinical and commercial validation—the former assessing whether AI-discovered drugs can succeed in Phase III clinical trials or achieve market approval, and the latter evaluating whether the business model can deliver sustained profitability. Companies that fail to complete these validations will gradually become marginalized, while those that succeed are poised for a promising future.

Notably, beyond this collaboration, multinational pharmaceutical companies are intensifying their efforts to capture the Chinese AI drug discovery market.

Since 2025, AstraZeneca has partnered with CSPC Pharmaceutical Group, and Harbour BioMed has joined hands with Evinova, a subsidiary of AstraZeneca... Guotai Junan Securities pointed out that,2025–2026 is a critical window for multinational corporations (MNCs) to fully ramp up their AI investments.

In the view of Jin Chunlin, Director of the Shanghai Health and Development Research Center,The value of AI in innovative drug development is still evolving, and this collaborative trend has only just begun.

This collaboration, which has drawn significant attention from the industry, holds value far beyond the monetary figure itself. A closer analysis reveals at least four key aspects worthy of focus.

Highlight 1: The Strategic Layout Behind Weekly GLP-1 Formulations.

Although the specific collaborative drug was not disclosed in this announcement, a comparison between Insilico Medicine’s official website and the pipeline chart in its recent prospectus reveals that the rights status of a metabolic disease asset targeting GLP-1R has changed from “licensable” to “global rights granted to an undisclosed partner,” suggesting the possibility of acquisition by Eli Lilly.

Industry analysis indicates that, based on preclinical data disclosed in patents, this GLP-1R drug is poised to become“Long-acting agonists for once-weekly dosing”。

Is this indeed the drug in question? Why did Eli Lilly choose to collaborate on this particular agent? The decision likely stems from the increasingly cutthroat competition in the weight-loss medication market.

Current dual-target therapies are no longer sufficient; the race is now on for triple-target therapies:Hengrui Medicine’s triple-agonist HRS-4729 has advanced to Phase I clinical trials, while Eli Lilly’s triple-agonist drug Retatrutide has initiated multiple Phase III clinical trials.

Insufficient Injections, the Race Shifts to Oral Administration:Novo Nordisk’s oral weight-loss drug Wegovy was launched in the United States in January 2026; Hansoh Pharmaceutical’s oral small-molecule candidate HS-10535 has been licensed to Merck & Co.; and Hengrui Medicine’s oral tablet formulation of retatrutide is poised to enter Phase III clinical trials.

Even weekly formulations are no longer sufficient; the competition has shifted to monthly formulations:Zhitai Biologics’ core product, zoviglutide (ZT002), is currently undergoing Phase III clinical trials for weight loss in China and is poised to become the world’s first once-monthly GLP-1 peptide; Ascletis Pharma’s small-molecule GLP-1R agonist ASC30, formulated as a subcutaneous depot for once-monthly administration, has also yielded positive clinical results.

From this perspective, while accelerating the market launch of the oral small molecule orforglipron, Eli Lilly’s collaboration to reserve a weekly oral formulation may represent a strategic move to prepare for product iterations over the next three to five years.

At a deeper level, the GLP-1 field is being regarded by the industry as“World’s First Anti-Aging Drug May Be Developed”the forefront, which injects greater long-term potential into the collaboration with Insilico Medicine.

Highlight 2: Structural “Inversion” of Upfront Payments and Milestones.

Jin Chunlin told VCBeat that the key to this collaboration lies not only in the total amount of $2.75 billion, but more importantly in the structural “inversion” of the upfront payment and milestones.

Traditional biopharmaceutical collaborations typically feature low upfront payments and high milestone-based compensation, whereas Eli Lilly directly offered a substantial $115 million upfront payment, underscoring its strong recognition of Insilico Medicine’s value.This means that AI-driven drug discovery has moved from “storytelling” to “tangible implementation”—Eli Lilly’s trust in AI-generated molecules is now translating into substantial, hard-cash endorsements.

Key Point 3: The Collaboration Model Shifts from “Tool Outsourcing” to “Strategic Synergy.”

From the initial agreement on Pharma.AI software collaboration in 2023, to the formal launch of a $100 million drug R&D partnership in 2025, and further to Eli Lilly’s participation as a cornerstone investor in Insilico Medicine’s Hong Kong IPO at the end of 2025, the collaboration between Eli Lilly and Insilico Medicine has continued to intensify. This partnership marks a strategic upgrade: shifting from “tool-based outsourcing” to “strategic synergy.” The announcement specifies that, in addition to existing asset licensing, both parties will engage in multiple R&D collaborations focused on targets selected by Eli Lilly.

“This means that Insilico Medicine is not merely an asset provider, but a core partner deeply embedded in Eli Lilly’s future exploration of novel mechanisms—elevating the collaboration from ‘off-the-shelf transactions’ to ‘co-creating the future,’” emphasized Jin Chunlin.

Highlight 4: AI’s Systematic Capability to Discover “Multi-Purpose Targets”

Alex Zhavoronkov, Founder and CEO of Insilico Medicine, stated that by deploying cutting-edge AI technologies capable of extending from biomarker identification to the construction of complex biological organism models, Insilico Medicine can identify multi-purpose targets that simultaneously drive multiple diseases. The collaboration with Eli Lilly will help deliver transformative therapies addressing significant unmet medical needs.

From Jin Chunlin’s perspective, the Insilico Medicine platform can identify targets that simultaneously drive multiple diseases. As a giant in the fields of metabolism and oncology, Eli Lilly has chosen to collaborate in this direction.What is valued is by no means a single molecule, but rather the underlying capability of AI to decipher complex biological mechanisms.

This leap in efficiency is poised to spawn blockbuster drugs with cross-indication potential, propelling AI-driven R&D from “conceptual narrative” to a new business dimension of “value realization.”

In addition to the four major highlights mentioned above, it is worth noting that multinational pharmaceutical companies have been intensively partnering with Chinese AI-driven drug discovery firms in recent years, and more collaborations are likely to emerge in the future.

In June 2025, AstraZeneca and CSPC Pharmaceutical Group entered into a strategic research collaboration focused on AI-driven drug discovery, with an upfront payment of $110 million and a total potential deal value of up to $5.33 billion.

In November 2025, Harbour BioMed partnered with Evinova China (an independent medical technology enterprise under AstraZeneca) to jointly apply AI and digital technologies to enhance the development efficiency of innovative biological therapies.

In 2026, AstraZeneca and Tsinghua University signed a university-level research collaboration agreement, focusing on core areas such as AI-driven drug discovery, translational medicine, and clinical development.

Guotai Haitong Securities research report points out,2025–2026: A Critical Window for MNCs to Fully Scale Up AI Investments, multinational pharmaceutical companies are upgrading AI from a standalone tool to the underlying infrastructure of their R&D and production systems, through strategies such as acquiring foundational model companies, co-establishing computing power laboratories, and collaborating on multi-project platforms.

In Ren Feng’s view, this signifies that AI-driven drug discovery has transitioned from a phase of technological accumulation to one of industrial implementation.The next milestone is achieving clinical success and commercial profitability.

Moreover, these intensive collaborations further underscore the strength of China’s AI-driven drug discovery enterprises.

Ren Feng further pointed out to VCBeat that China's biopharmaceutical industry has emerged as a global source of innovation. China holds significant advantages in R&D efficiency and cost: preclinical CRO costs are low, clinical development proceeds at two to three times the speed of overseas markets, and costs amount to only one-half to one-third of those abroad.This engineering capability has made China a major source of global innovation in pharmaceuticals.

“Focusing on the field of AI-driven drug discovery, Chinese companies are on par with their overseas counterparts in terms of algorithms and technology, even holding a slight edge in certain areas. More importantly, China’s unique advantages in engineering capabilities and cost efficiency further amplify the benefits of cost reduction and operational efficiency.”Therefore, China's AI-driven drug discovery sector holds a leading position globally—offering greater speed and lower costs.”

“This is a key reason why Chinese AI drug discovery companies are frequently able to secure substantial orders from multinational pharmaceutical firms and achieve out-licensing of their projects. In this sector, Insilico Medicine, as one of the earliest global pioneers, holds a leading position,” said Ren Feng.

It is also worth noting that, despite the numerous collaboration cases already in place, this trend may only just be beginning.

Jin Chunlin told VCBeat that the future focus is no longer on whether AI can empower drug R&D, but rather on how it will reshape industry rules—Is it merely an auxiliary tool for enhancing efficiency, or has it become the core engine disrupting traditional R&D paradigms?

“The answer is still evolving, but one thing is certain: AI is moving from the vision of ‘storytelling’ to the practice of ‘reducing uncertainty.’ The path to systematically enhancing R&D efficiency is becoming clearer, making this a trend worth continuously tracking and anticipating.”

Zhao Yu, a researcher at the Western Institute of Computing Technology of the Chinese Academy of Sciences and Deputy Director of the Turing-Darwin Laboratory, recently published an article pointing out that in the field of innovative drugs, AI is currently primarily positioned as an efficiency tool to accelerate the screening and optimization of compounds against known targets, with the aim of realizing commercial value as soon as possible. He noted that greater future potential lies in applications that enhance the understanding of diseases.

“Viewing AI merely as an efficiency tool may secure short-term competitive advantages, but it fails to address the fundamental challenges at the source of innovative drug R&D, ultimately leading to involution.”

“Viewing AI as a ‘scientific partner in disease understanding’ is more challenging, but it is also the fundamental path to unlocking novel therapeutic targets and conquering intractable diseases,” pointed out Zhao Yu.