AI-Powered Drug Discovery Accelerates: Lilly Leads Industry-Wide Race with Launch of Proprietary AI Factory

　　【Pharmaceutical Network Industry DynamicsRecently, Eli Lilly announced that its AI pharmaceutical factory, LillyPod, has been put into operation. The factory was assembled in just four months and is equipped with over a thousand NVIDIA Blackwell Ultra GPUs, making it an AI pharmaceutical factory independently operated by a pharmaceutical company.
 

It is reported that the facility aims to help its team achieve meaningful medical advances more quickly, accurately, and on a larger scale, accelerating the drug discovery and development process. The assembly was completed in just four months, demonstrating the efficiency of modern AI infrastructure construction. In the future, with powerful computing capabilities, LillyPod will handle complex tasks such as molecular modeling, drug interaction analysis, and clinical data processing, providing solid technical support for developing new drugs and optimizing treatment plans.
 

In fact, in recent years, against the backdrop of AI and digitalization driving the upgrading of research and development, an increasing number of pharmaceutical companies have started to utilize AI for simulating molecular design, toxicity prediction, pharmacokinetics, and more, accelerating the shortening of the cycle from drug discovery to candidate selection while reducing early failure rates. Among them, many large pharmaceutical companies, like Eli Lilly, are also further accelerating drug discovery and scientific innovation by building or investing in AI factories / supercomputing centers.
 

Merck and Meirui Chemical Sign Cooperation Memorandum: Strategic Collaboration to Enhance R&D Efficiency, Build Localized AI and Automation Capabilities, and Expand Business Synergy. According to the memorandum, Meirui Chemical will leverage its high-throughput automation laboratory and AI technology platform to provide chemical synthesis and related services to Merck China, accelerating molecular synthesis and shortening product development cycles. Additionally, Meirui Chemical will assist Merck China in establishing localized AI and automation laboratory capabilities.
 

Sanofi Plans to Acquire AI-empowered Drug R&D Capabilities Through External Collaboration, Building an Open AI Innovation Ecosystem. In 2025, Sanofi Collaborated Twice with Helixon (Earendil Labs): The first collaboration involved an upfront payment of $125 million for the rights to two bispecific antibodies, and the second integrated the latter's AI platform into multiple early-stage projects, with a total value exceeding $2.6 billion. Reportedly, Helixon’s bispecific antibody design system — the Helixon Design platform — can simulate molecular interactions on a large scale and efficiently design multi-target antibodies.
 

Novartis' End-to-End AI Platform Built for 2025 Integrates Palantir AIP and the MELLODDY Federated Learning Framework, Covering Target Discovery, Clinical Trial Optimization, and Safety Prediction.
 

BMS Collaborates with AI Pharma Company insitro to Deploy for ALS New Drug Small Molecule Discovery and Optimization. Renewed in 2025, with Potential Milestones Exceeding $2 Billion.
 

In addition to multinational pharmaceutical companies, many pharmaceutical companies in China are also shifting from "experimenting with AI" to "heavily investing in AI." Among them, Hengrui Pharma has elevated AI to a strategic level, while Fosun Pharmaceutical launched the decision-making intelligence platform PharmAID to integrate global clinical information and pipeline databases. Meanwhile, Dongyangguang Pharmaceutical and XtalPi have established a joint venture, planning to invest hundreds of millions of yuan to jointly build “AI+Robot"Joint Laboratory."
 

Overall, as the value of artificial intelligence in drug research and development shifts from concept validation to substantive implementation, leading pharmaceutical companies worldwide are engaged in an arms race to build AI factories and supercomputing centers. Currently, these pharmaceutical enterprises can be categorized into two types: one is multinational self-built, such as Eli Lilly's self-operated AI factory; the other is co-built by leading Chinese and foreign companies or Chinese pharmaceutical enterprises, such as Eli Lilly + NVIDIA, and Dongyang Guangyao + XtalPi.
 

In the future, with the operation of Eli Lilly's AI pharmaceutical factory and the advancement of numerous corporate collaborations, the R&D paradigm in the pharmaceuticals industry is expected to undergo a fundamental transformation from "labor-intensive" to "computing power-intensive."
 

　　Disclaimer: Under no circumstances shall the information or opinions expressed in this article constitute investment advice to any person.