In the history of AI pharmaceuticals in China, Huashen Zhiyao cannot be considered an "old cannon". It was founded by Dr. Peng Jian in June 2021 and has been established for less than 5 years. But this does not prevent it from catching up with hard core strength and becoming a "new AI pharmaceutical tycoon".

In addition to breaking the financing record, there is a key change in the investment camp of Huashen Zhiyao in this financing event.

Unlike previous rounds of financing, this time there are not only more investors like Dimension Capital、DST Global、INCE Capital Top overseas investment institutions, including Sanofi and Pfizer, have entered the market as strategic investors.

AI pharmaceutical companies gaining recognition from MNCs have become commonplace in China's frequent asset boom. But getting real gold and silver bets is still rare.

Direct investment means that both parties form an alliance at the capital level. Sanofi and Pfizer are willing to consider Huashen Intelligent Pharmaceutical as future core productivity partners, and their shareholding gives them priority matching rights for future technologies.

And cooperative authorization is a project level commercial transaction. Up to now, Huashen Zhiyao has reached pipeline authorization cooperation with Sanofi twice in a row, with a cumulative potential value of over 4.4 billion US dollars in the two transactions. From authorization cooperation to strategic investment, it fully proves Huashen Zhiyao's practical ability.

In the eyes of industry insiders, this is closely related to the technological route of Huashen Intelligent Pharmaceutical - the original intention is to break the "pain point curse" of traditional innovative drug research and development.

Traditional innovative drug development is constrained by the "anti Moore's Law", with high costs, long cycles, and low success rates, which has led many drugs to aspire but fail. In 2021, once AlphaFold2 was launched, it sparked a craze for AI pharmaceuticals, but most companies are clustering in shallow applications and lack core algorithm capabilities.

According to the understanding, the Huashen Intelligent Pharmaceutical team has accurately identified the limitations of models such as AlphaFold2, which highly rely on MSA technology and rely on natural homologous sequences to predict protein structures. This has significant limitations in the design of new proteins and research on novel viral proteins.

A pharmaceutical R&D expert familiar with MSA technology pointed out to Xieyi Jun, "For proteins, the vast majority of the three-dimensional structures of proteins in the world have not been captured by electron microscopy. Currently, a small number of proteins whose three-dimensional structures have been obtained have become the benchmark for multiple sequence alignment. Tradition is traditional, but with the increase of computational depth, the results obtained through the same technology will inevitably be different

In other words, there are currently very few known protein structures that can serve as references for MSA technology, and traditional MSA dependent techniques have significant limitations. But 'computing depth enhancement' can break this dilemma.

Unlike AlphaFold2's reliance on MSA, the algorithm of Huashen Zhiyao breaks away from the simple sequence alignment framework, deepens computational depth, and achieves the ability to predict protein 3D structure using a single protein sequence. It also greatly improves the training and prediction speed of AI algorithms, and the protein structure prediction time can be compressed to a few seconds.

According to Bloomberg, Earendil Labs is preparing for an IPO on the Hong Kong Stock Exchange, with a maximum fundraising amount of $500 million.

A cooperation order worth 4.4 billion US dollars proves technological leadership; The real gold and silver of top pharmaceutical companies, locking in the future - the financing event of Huashen Intelligent Pharmaceutical is undoubtedly the strongest evidence of China's AI pharmaceutical industry moving from technology verification to dual recognition by capital and industry.

Since 2026, AI pharmaceuticals have shown acceleration in both financing and cooperation.

As early as the first week of the new year, the AI pharmaceutical industry welcomed two remarkable collaborations: Sanofi and Earendil Labs once again joined forces, pushing the total value of their strategic partnership to $2.56 billion; Shiweiya and Yingsi Intelligence signed a $888 million research and development cooperation agreement, focusing on challenging tumor targets.

Recently, since March alone, Tianwu Technology and DeepMind have announced financing. The former has completed an A+round financing of over 200 million yuan, while the latter has raised nearly 200 million US dollars in a D round.

In terms of IPO, including Huashen Zhiyao, Baidu Robin Lee led the establishment of Baitu Biotech and Jintai Technology, which participated in the investment of Jintai Technology, and also announced to rush into Hong Kong shares.

The cooperation between multinational pharmaceutical companies and relevant domestic institutions is also deepening, moving from "single point cooperation" to "ecological co construction".

Recently, AstraZeneca signed a school level research cooperation agreement with Tsinghua University and jointly established the "Tsinghua University (Intelligent Industry Research Institute) - AstraZeneca Artificial Intelligence Drug Research and Development Joint Research Center", focusing on deep cooperation in core areas such as AI drug discovery, translational medicine, and clinical development, to accelerate the clinical application of research results.

Behind the vigorous development, there are multiple unique development supports, especially at the policy level.

Various national industrial policies and the latest "15th Five Year Plan" have listed artificial intelligence and biomanufacturing as core development areas, with AI for Drug Discovery becoming a crucial development direction. Since AI for Science (AI driven scientific research) was listed as a key guiding direction by the Ministry of Science and Technology, the National Natural Science Foundation of China, and others, the country has continued to provide comprehensive policy and resource support.

Local governments have also followed suit and introduced targeted support policies to safeguard the AI pharmaceutical industry.

Jiangsu launches the "Artificial Intelligence+" action plan to promote the application of AI in drug target screening, molecular design, and other scenarios, and to build a public service platform that opens up toolchains to small and medium-sized enterprises; Hunan explicitly supports the integration and application of medical and pharmaceutical public data, promotes the standardization of clinical data, and helps empower drug research and development with AI; Guangxi is focusing on "AI+natural medicine", accelerating the construction of benchmark application platforms, and accelerating the research and development verification of new products.

At the same time, multiple regions are cultivating biopharmaceutical industry clusters, exploring the cooperation model of "park+enterprise+research-oriented hospital", breaking through the bottlenecks in the industrial chain, providing comprehensive support such as venues, funds, and talents for AI pharmaceutical enterprises, and forming an industry development pattern of top-down linkage and collaborative efforts.

From Tsinghua University laboratory to the global pharmaceutical industry; From the initial technological prototype to the commercial leap that secured $787 million in financing, every step taken by Earendil Labs reflects the strong pulse of China's AI pharmaceutical industry.

In this global wave of innovation, AI pharmaceuticals are ushering in their own 'Chinese moment'. In the future, with the continuous overcoming of technological barriers and the deep integration of industry, academia, research, and medicine, China's strength will occupy a more central position in the world pharmaceutical innovation map, continuing to write the pharmaceutical legend of Eastern wisdom.