Orient: Where is the AI pharmaceutical trend heading?

Orient released a research report stating that with the accumulation of factors 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 long cycles, high costs, and high failure rates in innovative drug R&D. Specifically, frontier fields such as automated wet labs and virtual cells have become focal points for overseas large-model giants, while domestic AI pharmaceutical companies have taken the lead in deploying related facilities and possess global competitiveness. Meanwhile, forward-looking indicators such as pipelines and financing of global AI pharmaceutical companies continue to improve. As an indispensable part of the global innovative drug industry chain, domestic life science upstream and CXO players are also expected to fully benefit from the entirely new incremental demand brought by AI. Orient's main viewpoints are as follows: Competing in protein design, automated wet labs are emerging In recent years, models represented by AlphaFold and Claude have achieved technological breakthroughs in the field of protein design, providing important tools for early-stage structural design and screening in drug development and generating substantial demand for wet experiments such as protein synthesis and affinity testing. Considering that existing biological data is far from sufficient to meet AI4S's requirements for data scale and quality, as the paradigm shifts from using AI to analyze existing biological data to organized, large-scale production of high-quality datasets, AI will participate in and accelerate the production of biological knowledge. Therefore, automated wet labs capable of producing high-quality data at high throughput and low cost will be scarce resources and core barriers in the AI4S era. As AI applications extend across the entire new drug R&D chain, this will drive a leap in related demand. Betting on virtual cells, opening a new infrastructure for AI pharma The real bottleneck in new drug R&D lies in finding a biological mechanism whose intervention can alter the disease progression of patients. AI represented by virtual cells and virtual humans is expected to solve this problem. Specifically, virtual humans use dozens of specialized models to extract signals from specialized data and transform them into a form understandable by general models, after which a reasoning layer connects and integrates these insights into mechanisms and targets. AI identifies mechanisms that hold true in both human and cellular data, achieving a correct closed loop in drug development and growing stronger through iteration, ultimately bringing about a systemic reconstruction of R&D productivitytransforming drug discovery from a craft highly dependent on scientists' personal intuition into a scalable, iterable, and predictable industrial process. Recently, large-model giants such as Google and Meta, together with U.S. government departments, announced an investment of USD 1.8 billion in the virtual cell field, which is expected to launch a new global infrastructure for AI pharma. Financing and pipelines improving, upstream and CXO to benefit Financing and pipelines are important forward-looking indicators of demand for the life science upstream and CXO industries. From a financing perspective, in 26Q2, venture capital financing for AI pharmaceutical companies reached USD 5 billion, already accounting for about 1/3 of healthcare industry financing but only about 1/30 of AI company financing. AI pharmaceutical financing has become an important source of funding for global new drug R&D and still has substantial room for growth. From a pipeline perspective, some companies such as INSILICO have made rapid pipeline progress and are expected to continue reading out key clinical data over the next four years, bringing important catalysts to the industry. With the advancement of pipelines under development and the diffusion of demand for automated wet labs and other needs across the entire new drug R&D chain, domestic life science upstream and CXO companies will also benefit from the incremental demand brought by AI pharma, with prosperity rising further. Related tickers: INSILICO, GenScript Biotech, Acrobiosystems, Joinn Laboratories, Shanghai InnoStar Bio-tech, WuXi AppTec, METIS TECHBIO-P. Risk warnings Risks related to data, technology, clinical trials, regulation, and geopolitics.