Huawei Pharma Team States "Huawei Does Not Make Drugs," Positions Itself as an AI Enabler for the Pharmaceutical Industry; Netizens Ask: When Will There Be Fast-Acting Drugs?

Huawei Pharma Team President Fan Jie Makes Clear That "Huawei Does Not Make Drugs" and Hopes to Become the Technical Foundation of the AI Pharmaceutical Industry

On October 24, the 11th Pharmaceutical Innovation and Investment Conference, co-hosted by the association and Hong Kong Exchanges and Clearing, was held in Nanjing. Fan Jie, President of the Huawei Pharma Team, attended the conference and was interviewed by the media.

Regarding outside interest in whether Huawei will directly enter drug R&D, Fan Jie made it clear: "Huawei does not make drugs, nor does it develop pipelines." Huawei hopes to leverage its strengths in computing, communications, and artificial intelligence to provide pharmaceutical companies, research institutions, and AI drug discovery companies with computing power, storage, networking, toolchains, and data governance capabilities, becoming the technical foundation and ecosystem supporter of the AI pharmaceutical industry.

In Fan Jie's view, AI drug discovery is still in a stage of rapid development with high market expectations. Some technologies, such as protein structure prediction and molecular simulation, have already entered practical application, but the entire drug R&D chain has not yet been connected end to end. In the next stage, the industry needs to answer not just how large the models are, but whether the models can enter real R&D processes and form a closed loop with experimental data and R&D decisions.

Fan Jie said that Chinese pharmaceutical companies still have an obvious gap in revenue scale compared with large international pharmaceutical companies. Whether AI can improve R&D efficiency and help companies achieve sustained product output will ultimately still need to be verified through specific pipelines and commercialization results. He revealed that some cooperative projects have begun to deploy computing clusters at the hundred-card scale for training, deployment, and optimization of drug R&D models.

Fan Jie believes that, compared with other companies, Huawei has three major advantages in participating in AI drug discovery:

First, Huawei has computing power and storage capacity, especially the ability to provide advanced computing power that many companies do not have;

Second is the cluster capability of computing power, which relates to how to fully leverage computing power and how to use large computing power plus large data to produce better results. Training models requires at least 64 cards, and often even hundred-card and thousand-card scales. However, hundreds of cards cannot be used individually one by one; they need to be connected to form a cluster. Huawei has unique advantages in clustering and super nodes. Currently, Huawei has a 1,024-card super node solution, the largest in the world;

Third is ecosystem advantage. Huawei has cooperated with DP Technology, Stonewise, Molecular Heart, and others to form integrated supporting solutions. Huawei handles the coordination and adaptation of computing power, storage capacity, and network capacity, while other companies handle models.