UK Establishes National-Level AI Biosecurity Laboratory, with OpenAI, Anthropic, and Google DeepMind Participating

The UK will establish the world's first national-level AI biosecurity laboratory, with companies such as OpenAI and Anthropic participating. The AI pharmaceutical track is accelerating from technical validation toward commercial realization.

The UK Cabinet Office said in an announcement on Saturday that the UK will establish a national-level artificial intelligence biosecurity laboratory to help strengthen its defenses against emerging biological threats. The laboratory will be jointly supported by OpenAI, Anthropic and Google DeepMind, and is one of a package of key measures introduced by the UK to improve understanding of and mitigate the potential risks of AI technology.

As part of Wednesday's budget, the UK government will spend 100 million pounds, with the support of leading AI companies, to build this globally first-of-its-kind institution. The official statement said the laboratory will become the world's first institution dedicated to AI biosecurity work, using AI technology to detect and monitor biosecurity threats; in addition to direct government funding, the laboratory will also receive AI model invocation credits worth up to 200 million pounds from OpenAI and Anthropic, and will cooperate deeply with Google DeepMind and life sciences innovation company Basecamp Research.

Domestic policy is also continuing to step up. The implementation opinions on promoting and regulating the development of "AI + healthcare" applications issued by five departments including the National Health Commission clearly state that by 2027 a batch of vertical large models and agent applications for clinical specialties and diseases will be formed, and by 2030 intelligent auxiliary applications for primary-level diagnosis and treatment will basically achieve full coverage, and hospitals at level II and above will generally carry out intelligent auxiliary diagnosis of medical imaging. The project approval guidelines for pathology medical service price items issued by the National Healthcare Security Administration have already listed "AI-assisted diagnosis" as an extension item of pathology diagnosis and included it in the composition of price items.

Project implementation on the industry side is also accelerating. ACROBiosystems has built a dual-wheel-driven protein development model of "AI prediction - experimental validation," completing AI-optimized modifications on multiple industrial-grade products such as high-salt-tolerant universal nuclease and highly stable CD19 protein. In the first half of 2026, it achieved operating revenue of 499.6 million yuan, a year-on-year increase of 28.97%, of which recombinant protein revenue was 401.5 million yuan, a year-on-year increase of 26.00%, and newly signed orders increased by more than 30% year on year; Hongbo Pharmaceutical's self-developed AI drug design platform DiOrion has cumulatively provided technical support for more than 100 new drug projects, with clients including multinational pharmaceutical companies such as Eli Lilly.

AI drug discovery refers to the application of machine learning, deep learning and generative models to drug R&D, using processing of compound structures, protein structures, multi-omics and clinical research data to assist in target identification, candidate molecule screening, drug property prediction and clinical research design. At present, AI has penetrated deeply into links such as protein structure prediction, virtual screening, molecular design and lead optimization, and the industry is moving from technical validation to a key stage of clinical realization and commercial implementation.

AI is expected to continue expanding the number of projects entering the R&D funnel, with the speed and output of molecular design significantly improved, but the validation link has not accelerated in sync, and the R&D bottleneck is shifting backward from the design end to wet experiments and in vivo evidence generation. Guotai Haitong pointed out that AIDD is expected to improve the druggability of candidate molecules and expand the space of biological hypotheses, and the incremental downstream R&D services will mainly be realized from 2026 to 2028.

Against the background of continued penetration of AI technology, CICC further pointed out that AI has gradually penetrated links such as protein structure prediction, virtual screening, molecular design and lead optimization, and is expected to reduce experimental trial and error and shorten R&D cycles. Leading pipelines entering the mid-to-late clinical stage also provide more basis for evaluating their R&D value.

From the funding side, AI drug discovery has become one of the most important sources of incremental funding for global innovative drug R&D. Orient Securities believes that in the second quarter of 2026, venture capital financing for AI pharmaceutical companies reached 5 billion US dollars, already accounting for about one-third of financing in the healthcare industry, but still only about one-thirtieth of financing for AI companies, leaving large room for improvement; Google, Meta and others, together with US government departments, announced an investment of 1.8 billion US dollars in the virtual cell field, which is expected to launch new global AI pharmaceutical infrastructure.

Calculations of market space also point to high growth. Industrial Securities pointed out that the global AI4S market is expected to reach 5.85 billion US dollars in 2026 and is expected to reach 34.78 billion US dollars by 2035, with a compound growth rate of 21.9% from 2026 to 2035, among which biopharmaceuticals account for the highest share.

This judgment echoes the view of Haitong International, which believes that AI is expected to break through the pharmaceutical industry's "reverse Moore's law," with a decline in the cost of generating a single molecule driving growth in the total number of generated molecules. Because AI-generated molecules need to be validated through wet experiments, wet experiment platforms are expected to benefit first.

Performance of multiple concept stocks is expected to double this year

According to the East Money concept sector, there are currently 81 stocks in the A-share market involved in the AI pharmaceutical (medical) concept, with a total market value of about 1.34 trillion yuan.

Mindray Medical ranks first with a size of 214.852 billion yuan, Xiechuang Data ranks second with 95.338 billion yuan, and Unisplendour follows with 74.305 billion yuan. Pharmaron, Shanghai Pharmaceuticals and Huadong Medicine all have market values exceeding 46 billion yuan.

Over the past month, the AI pharmaceutical (medical) concept sector has generally trended weakly, with 22 stocks rising and 59 falling. Hisun Pharmaceutical rose more than 19% to rank first, Mindray Medical rose more than 14% to rank second, Guoxin Health and Liuzhou Pharmaceutical rose 11%, and Laobaixing and Meinian Onehealth both rose more than 9%. On the decline side, Biocytogen, Hualan, ACROBiosystems and many other stocks fell more than 32%.

From the funding perspective, East Money Choice data shows that over the past month, a total of 17 AI pharmaceutical (medical) concept stocks received contrarian bets from margin traders. Among them, Haoyuan Pharmaceutical received 131 million yuan in additional leverage funds, Hanyu Pharmaceutical and MediTech were respectively snapped up with 91 million and 53 million yuan, and KingMed Diagnostics, Baicheng Pharmaceutical and Dian Diagnostics all received more than 24 million yuan in net margin purchases.

In terms of future growth potential, according to consensus institutional forecasts, a total of 14 AI pharmaceutical (medical) concept stocks are expected to achieve doubled performance growth this year. Among them, institutions expect Kaile Shares' net profit to surge 28.7 times year on year, Dian Diagnostics' net profit to grow more than 10 times, and Wondfo Biotech and Changchun High-Tech's forecast net profit growth rates to both exceed 5.9 times. The performance of Zelgen Pharmaceuticals-U, KingMed Diagnostics and other stocks is also expected to multiply.

Pharmaron achieved operating revenue of 7.596 billion yuan in the first half of 2026, a year-on-year increase of 17.9%, and adjusted non-IFRS net profit attributable to shareholders of 909 million yuan, a year-on-year increase of 20.3%. Newly signed orders increased by more than 30% year on year, among which newly signed orders for small-molecule CDMO increased by more than 50% year on year. The company has participated in 887 drug discovery projects and continues to advance the integration of AI and automation technology, improving R&D efficiency through the iterative closed loop of "scenario - data - model - revalidation."

Haoyuan Pharmaceutical achieved operating revenue of 1.648 billion yuan in the first half of the year, a year-on-year increase of 25.71%, and has cumulatively undertaken more than 1,100 innovative drug R&D and production (CRDMO) projects, of which 160 have entered the late clinical and commercialization stages. Back-end business orders on hand exceeded 1 billion yuan, a year-on-year increase of 72.6%. Centering on the strategy of "drug R&D + AI technology," the company combines its own compound data with the MedChemAI intelligent platform and bioactivity testing platform to form an R&D closed loop covering design, screening, experimental validation and data feedback.

(Source: East Money Research Center) Middle of the main text Embedded advertisement