The Zhitong Finance App learned that Orient Securities released a research report saying that with the accumulation of various elements such as models, data, and computing power, AI is expected to become a new infrastructure for the global innovative drug industry in the future, disrupting the “anti-Moore's law” of the long cycle, high cost, and high failure rate of innovative drug development. Specifically, cutting-edge fields such as automated wet laboratories and virtual cells have become the focus of attention of major overseas model giants, and domestic AI pharmaceutical companies have taken the lead in laying out related facilities and are globally competitive. At the same time, forward-looking indicators such as pipelines and financing of global AI pharmaceutical companies continue to improve. Domestic life science upstream and CXO, as an indispensable part of the global innovative drug industry chain, are also expected to fully benefit from all new volume demand brought about by AI.
Orient Securities's main views are as follows:
Keratin design, automated wet laboratory wind
In recent years, models such as AlphaFold and Claude have taken the lead in technological breakthroughs in the field of protein design, providing important tools for early structural design and screening of drugs, bringing about a large number of wet experiments such as protein synthesis and affinity testing. Considering that existing biological data is far from meeting AI4S's requirements for data scale and quality, AI will participate in and accelerate the production of biological knowledge as the paradigm shift from using AI to analyze existing biological data sets on an organized scale, so automated wet laboratories that can produce high-quality data at high throughput and low cost will be a scarce resource and core barrier in the AI4S era. As AI applications extend to the entire chain of new drug development, it will drive a shift in the level of related demand.
Betting on virtual cells to launch a new infrastructure for AI pharmaceuticals
The real bottleneck in developing new drugs is finding a biological mechanism, and intervention in it can change the course of a patient's disease. AI represented by virtual cells and virtual humans is expected to solve this problem. Specifically, virtual humans use dozens of professional models to extract signals from professional data and transform them into a form that the general model can understand, and then the inference layer integrates these insight connections into mechanisms and targets. AI finds mechanisms established in both human and cellular data, enables the proper closure of pharmaceuticals, and continues to strengthen with iteration, eventually bringing about a systematic restructuring of R&D productivity, transforming drug discovery from a craft that is highly dependent on scientists' individual intuition to a large-scale, iterable, and predictable industrial process. Recently, big model giants such as Google and Meta joined forces with US government departments to announce an investment of 1.8 billion US dollars in the virtual cell field, which is expected to launch a new global AI pharmaceutical infrastructure.
The financing pipeline is improving, and upstream and CXO will benefit
Financing and pipelines are important forward-looking indicators of demand in the upstream life sciences and CXO industries. From a financing perspective, in 26Q2, AI pharmaceutical companies' venture capital financing amount was 5 billion US dollars, accounting for about 1/3 of healthcare industry financing, but only about 1/30 of AI companies' financing. AI pharmaceutical financing has become an important source of funding for global new drug research and development, and there is still plenty of room for improvement. From a pipeline perspective, the pipelines of some companies, such as Insilix Intelligence, are progressing rapidly, and it is expected that they will continue to read key clinical data over the next 4 years, bringing important catalysts to the industry. With the advancement of research pipelines and the spread of demand for automated wet laboratories to the entire new drug development chain, domestic upstream life science and CXO companies will also benefit from the incremental demand brought about by AI pharmaceuticals, and the boom will rise further.
Related targets: Insili Intelligence, Kingsley Biotech, Bepsis, Zhaoyan New Pharmaceutical, Innox, PharmacomingKangde, and Jetai Technology-P.
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