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Nation's AI-backed drug market hits global stride

By LI JING | China Daily | Updated: 2025-08-16 00:00
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China's artificial intelligence-driven drug discovery is accelerating its role as a prominent player in global biotech. Experts and industry insiders said the sector is drawing unprecedented international attention, even though no AI-discovered drug has yet reached the market.

According to SDIC Securities, the global AI-driven drug market has more than doubled since 2021, hitting $1.76 billion in 2024, with a compound annual growth rate of more than 30 percent.

In China, the pace is even faster from 70 million yuan ($9.74 million) in 2019 to 410 million yuan in 2023, with a CAGR of 57.4 percent. Lead-Leo Research Institute projects nearly 70 percent annual growth from 2024 to 2028, when the market could top 5.86 billion yuan.

China's AI drug sector has also been striking deals with Big Pharma. This year alone, Syneron Bio inked a $3.4 billion agreement with AstraZeneca, while Helixon signed a $1.72 billion partnership with Sanofi, among others.

"These collaborations show Chinese AI drug-discovery capabilities are gaining global recognition," said Fang Yang, executive director for healthcare and biotech at CEC Capital. "The industry is entering a new phase of going global and proving it can deliver results."

The most recent deal capturing attention is China's XtalPi Holdings Ltd's $6 billion partnership with US biotech firm DoveTree. It ranks among the largest license-out deals in China's biopharma history.

Under the deal, announced on Aug 5, XtalPi will deploy its AI platforms to run preclinical research on a mix of large — and small-molecule programs, including several targets picked by DoveTree. The US partner will hold exclusive worldwide rights to develop and commercialize the resulting drug candidates.

XtalPi has already pocketed $51 million upfront, far exceeding its total 2024 revenue of 266 million yuan and is in line for another $49 million in near-term payments and as much as $5.89 billion in milestones and royalties.

"AI can optimize molecular structures and streamline the earliest stages of drug research and development," said Chu Lei, a researcher at the Healthcare Executive Institute. "XtalPi's role is to deliver ready-to-test clinical candidates straight to DoveTree's labs."

Still, the potential of AI in biotech is promising. Traditional drug development can take more than a decade and cost more than $1 billion. AI, particularly deep-learning models, can speed up target screening, molecular design, and even trial planning. Consultancy McKinsey experts estimated that AI could shrink the time from lab to patient to a tenth of current timelines.

Ren Feng, co-CEO of Insilico Medicine, described the global AI-driven biotech sector as moving into its 2.0 phase. The first wave dating back three decades relied on physics-based computer-aided design. The arrival of generative AI around 2013 marked a turning point, allowing algorithms to create novel molecules from scratch by drawing on vast troves of historical data.

The next stage, Ren said, will see AI embedded in every step of drug R&D, from target discovery to clinical management — ushering in what he calls the "3.0 era" of fully integrated, intelligent drug development.

Policy tailwinds are reinforcing the trend. In November 2024, the National Health Commission and two other ministries issued a blueprint for AI in healthcare, naming intelligent drug discovery and development and AI-assisted clinical trials as priority areas.

Local governments are following suit. On Aug 12, Zhejiang province laid out a plan to build a national AI medical application base by 2027, aimed at fostering homegrown innovators, attracting composite talent, and building a complete AI healthcare industry chain.

Despite the surge in dealmaking and investment, industry experts stress most AI-driven agreements today, including XtalPi's, focus on preclinical work. "No AI-discovered drug has yet been approved anywhere in the world, meaning the commercial loop remains incomplete," Chu noted.

 

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