AI-Powered Drug Discovery: XtalPi Files IPO Prospectus to Tackle Traditional Pharma Challenges

China News Service, Beijing, October 12th, by reporter Liu Liang (记者 刘亮) — The pharmaceutical industry has a "Double Ten Rule": the average cost for developing an innovative drug from the start of research to market launch exceeds 1 billion US dollars, with a development time of over 10 years, and about 90% of drugs fail during the clinical trial phase.

In response to the bottlenecks of high investment, long cycles, and low success rates in traditional pharmaceuticals, Wen Shuhao, co-founder and chairman of XtalPi, recently stated in an exclusive interview with China News Service that AI (artificial intelligence) is expected to help resolve these challenges and become a "valuable assistant."

Unscrewing test tubes, weighing powders, precise material addition, liquid pipetting, magnetic stirring... A white robotic arm can perform experiments and record data 7×24 hours a day, assisting or even replacing manual experimentation. This rather sci-fi-like scene comes from XtalPi's creation of the world’s largest biopharmaceuticalRobotThe cluster of automated workstations is also a microcosm of AI empowering the biopharmaceutical industry today.

Wen Shuhao pointed out that AI pharmaceuticals greatly enhance the speed and efficiency of research and development. Compared with the traditional new drug R&D model, AI has obvious advantages in target discovery, confirmation, validation, and the speed of discovering new molecular structures. At the same time, the combination of AI and robotics, with their precision and ability to operate around the clock, not only shortens the drug R&D cycle but also generates standardized data to drive model evolution and iteration.

Currently, "AI + Pharmaceutical" has become a key direction supported by industrial policies in multiple countries. In April this year, seven departments, including China's Ministry of Industry and Information Technology, issued the "Digital and Intelligent Transformation Implementation Plan for the Pharmaceutical Industry (2025–2030)," further providing guidance for industry development. Meanwhile, European and American countries are also enhancing policy support and guidance.

China Merchants BankThe industry research of the institute shows that, driven by demand and policies, investment in AI pharmaceuticals continues to grow. It is expected that the global AI pharmaceuticals market size will reach 5.62 billion US dollars by 2028. According to McKinsey's prediction, in the long term, the market size is expected to reach 28 billion to 53 billion US dollars.

"AI drug discovery is an inevitable trend globally," said Shuhaohao Wen. He introduced that currently, the world's top pharmaceutical companies are promoting the development of AI pharmaceutical technologies and actively laying out related fields.

In China, multiple companies are also actively exploring. According to incomplete statistics from industry organizations, as of July this year, the number of AI pharmaceutical enterprises in China has exceeded 100, mainly clustered in Beijing, the Yangtze River Delta region, and the Guangdong-Hong Kong-Macao Greater Bay Area.

Research from CRI shows that China's AI pharmaceuticals industry is at a critical window of rapid development. It is predicted that from 2025 to 2030, China’s intelligent pharmaceuticals industry will enter a high-speed growth phase, with the market size expected to exceed 500 billion RMB, maintaining an annual compound growth rate of over 15%.

Wen Shuhao believes that China has a very complete supply chain for high-flexibility and high-precision robots, which has formed China's scale and cost advantages in this field. This allows China to be on the same starting line as the rest of the world in AI drug research and development, and even have some unique advantages. Domestic companies should take advantage of China’s complete robot supply chain. He stated that robots are a very important entry point for generating data, and could be a key factor in drug research and development applications.

However, like many emerging industries, the rise of AI pharmaceuticals also faces some voices. In the view of Shuhao Wen, AI empowering pharmaceutical innovation also requires a process of data accumulation. "Data is crucial, including the accumulation of standardized positive and negative data in the pharmaceutical industry."

Wen Shuhao admitted that with the arrival of new technologies, the industry will undoubtedly face pressure. At this time, a more unified understanding and action within the industry is needed, including professionals, investors, as well as national policy support, etc., to jointly promote the development of the entire AI-driven drug discovery system. (END)