Novo Nordisk Partners with OpenAI, MNC Enters AI Ecosystem Competition

On April 14, the century-old pharmaceutical giant Novo Nordisk announced its collaboration with GeneralAI Leader OpenAI Establishes Strategic Partnership to Fully Deploy AI Technology in Every Aspect from Drug Discovery to Business Operations, "Joining Hands to Transform the Way Drugs Are Discovered and Delivered."

This partnership took place at a crossroads for this century-old Danish company — balancing traditional growth models with the pressures of future competition. In the long term, it is also...Novo Nordisk's "Efficiency" Initiative to Win the Competition for the Next DecadeIteration".

On March 20, the statutory protection period for the core compound patent of Semaglutide officially expired in China. This means that pharmaceutical companies in China can now use the molecular structure of Semaglutide for production. The previously stalled marketing applications for domestically produced generic versions of Semaglutide, which were blocked by patent protection, have now collectively entered the formal review and approval process.

On April 1, Eli Lilly announced that its oral small-molecule GLP-1 receptor agonist Orforglipron has been approved by the U.S. FDA for marketing. It is the world's first approved oral small-molecule non-peptide GLP-1 receptor agonist (GLP-1 RA) for the treatment of adult obesity or overweight.

As cracks appear in the patent wall of semaglutide and Eli Lilly launches a close pursuit across its entire pipeline, the urgency to find "the next semaglutide" has never been stronger. Simple molecular iterations (such as dual-target or triple-target agonists) have become an open race, making it difficult to build long-term barriers.

What Novo Nordisk needs is not just new drugs, but a new paradigm for discovering them.

According to the joint statement by Novo Nordisk and OpenAI, the core objective of this collaboration is "to utilize AI tools more efficiently."With capabilities,"Analyze complex datasets, identify promising new drug candidates, and shorten the time for drugs to advance from the R&D stage to clinical application," while improving the efficiency of production, supply chain, and commercial operations.

Novo Nordisk President and CEO Maziar Mike Doustdar mentioned, "Integrating artificial intelligence into our daily work,(AI will help employees) analyze data sets on a scale previously unimaginable and discover patterns that were previously unseen,"And test hypotheses faster than ever before."

Choosing OpenAI, Based on Threefold Business and Technology Logic：

First,Deeply Explore the Value of Exclusive Data。Novo Nordisk has the world's richest real-world data on GLP-1 class drugs.It is a complex system that surpasses the short-term analytical capabilities of current human teams.Combined with the advanced model capabilities of OpenAI,Both parties are expected to deeply explore large-scale, high-quality wet lab experiments and real-world data in pharmaceutical R&D, identify hidden correlations within such high-dimensional, cross-scale data, and thereby enter niche markets that have yet to be broken through and clinical gaps with no excellent solutions currently available.

Secondly, address systemic efficiency challenges.Currently, many AI companies are collaborating to focus on optimizing established processes (such as faster molecular screening),Propose cutting-edge pipelines and empower AI-driven iteration through small-scale approaches such as drug discovery/early screening.And Novo Nordisk and OpenAIThe cooperation modalities are obviously not limited to this — OpenAI will assist Novo Nordisk in upskilling its global workforce, enhancing AI literacy capabilities; improving the efficiency of manufacturing, supply chain and distribution, as well as corporate operations; pilot projects will be launched in the fields of R&D, manufacturing, and commercial operations, with full integration expected by the end of 2026.

"Integrating into daily work" and "enhancing the efficiency of manufacturing, supply chain, distribution, and enterprise operations" – implying a more thorough process reengineering.Can be regarded as ""Install a brand-new underlying system", making AI an integral part of scientific research thinking and workflow, rather than just a plugin to accelerate a specific process. By co-building a unified capability foundation with OpenAI, Novo NordiskIt is expected to打通从实验室到药房的端到端数据流，突破过往点状合作、阶段式合作的协同瓶颈。

Finally, reshape the innovation paradigm and control long-term costs，InResponding to UrgentStrategyTimeWindow。As the patent exclusivity period diminishes and competitive pipelines intensify, the probability of success through incremental improvements is decreasing. This collaborationThe essence is to use technology leverage to shift the innovation model from "capital and labor-intensive" to "data and algorithm-driven," fundamentally.Reconfigure the efficiency of resource allocation,Pin hopes on——AI can transcend traditional experiential boundaries, discovering novel molecular entities, therapeutic mechanisms, and feasibility validations beyond densely targeted competitors.

ReviewNovo NordiskThe previous AI layout has shown obvious characteristics of "point breakthrough."。These collaborations cover multiple frontiers, including target discovery, molecular design, and clinical development.Field,ButRelatively independent, with a focus on solving bottlenecks in specific areas.：

In January 2025, Novo Nordisk and Valo deepened their collaboration, significantly expanding the scope from cardiovascular diseases to obesity and type 2 diabetes, with a potential total transaction value.Approximately 4.6 billion US dollars, aimed at leveragingIts Opal computing platform discovers new targets and designs molecules.

In June of the same year, Novo Nordisk partnered with NVIDIA and the Danish AI Innovation Center (DCAI) to develop customized AI models and agents using the Gefion AI supercomputer, which is based on NVIDIA's technology. This collaboration aims to accelerate early-stage research and clinical development, as well as construct large biomedical language models for drug discovery.

But observe thatOld Rival、The World's First Trillion-Dollar Pharmaceutical EnterpriseEli Lilly，Has been further constructedAggressive Eco-AI Layout——By building a systematic AI infrastructure, attempting to rewrite the rules of the game.

In 2025, Eli LillyLaunch of "Lilly TuneLab" AI/ML Platform Open to External Biotech Companies, and Announcement of Building an Industry-Leading Autonomous AI Computing Power Factory. Its first released AI drug discovery model possesses proprietary data worth over $1 billion—accumulated from Lilly's years of valuable drug research, development, and experimental efforts.

Lilly TuneLab to Open for Early Biotech Companies, Leveraging Innovative "Federated Learning" Technology (a method for training AI models without anyone seeing or accessing the data) to allow users to share AI capabilities without sharing core data. This means that Lilly is attempting to transform its own data and algorithmic capabilities into a "public utility" that attracts innovation resources across the industry, thereby establishing a lasting advantage at the source of innovation.

In other words, AI is pushing pharmaceutical capabilities to a broader range of participants – including Biotech, AI startups, LLM developers, and those companies with the strongest computing power and the most advanced algorithms.

Compared to Novo Nordisk's previous point-based collaborations,In responding to Lilly's highly integrated "Central AI Factory + Open Platform" model, integration challenges such as inconsistent data standards, fragmented technology stacks, and high collaboration costs may arise.Therefore, the full-chain cooperation with OpenAI,Not Only Novo Nordisk"Passive Response" should be regarded as a fundamental upgrade to its AI strategy andLong-term Strategic Integration.

To assess the value of this collaboration, one should avoid over-interpreting short-term stock prices or grand narratives, and instead focus on several solid, verifiable, and substantive outcomes in the future:

The first observation point is the pipeline advancement proof, namely, the first candidate drug independently driven by this joint platform into clinical research and its clear timeline. The second is the efficiency quantification report, such as the publication of quantified reports on efficiency improvements in specific R&D stages. The third is the public validation of scientific capabilities, like peer-reviewed papers. The fourth is evidence of platform scalability — how the AI operating system integrates internal company resources and demonstrates adaptability across therapeutic areas, thereby proving that it is not merely a customized tool for a single target (e.g., GLP-1) but a strategic foundation with versatility.

From a broader perspective, compared to past MNCsAI+ Layout: Novo Nordisk and Eli Lilly Have Entered "Ecosystem-Level" Competition.For top pharmaceutical companies, AI has completely transformed from "a tool that adds icing to the cake" to "a strategic infrastructure crucial for survival."

The "open platform" model advocated by Eli Lilly and the "vertical integration" model chosen by Novo Nordisk,Represent two completely different approaches to ecosystem building in the AI era. The formerLogicThe key lies in whether they can attract and invigorate the entire innovation ecosystem, becoming the "basic service provider" of the industry; the latter's key lies in the depth of internal integration and closed-loop efficiency. The parallel existence and competition of these two models will redefine the roles of giants and startups in future pharmaceutical innovation., as well as the collaborative patterns among giants.

At the same time, AI software service companies/AI Biotechs that provide single algorithm tools and are caught in the middle will face tremendous pressure, and industry value will further shift towards those with unique data generation capabilities or"Deep Tech" Companies Capable of Solving Specific Complex Scientific ProblemsAggregation.