AI has become a new "acceleration engine" for drug discovery. It is recommended to focus on the AI4S and AI + pharmaceutical tracks.

Postal Securities released a research report stating that the global drug research and development outsourcing service market size is expected to increase from $151.2 billion in 2023 to $363.2 billion in 2030, with a CAGR of 13.3%. AI has become the "accelerator" for new drug discovery, and by predicting and combining key parameters such as binding energy, solubility, and toxicity, AI can rapidly screen, optimize, and even design potential candidate molecules or new materials in virtual space, potentially shortening the drug discovery process. Looking ahead to 2026, leading companies in the AI+ pharmaceutical industry such as Xtalpi and Tempus are expected to achieve positive EBITDA for the first time, leading to a period of valuation reconstruction in the industry. The main points of Postal Securities are as follows: 1) Reviewing the 25x growth of PLTR in 3 years, a good AI application track should have the following characteristics: 1) Massive real data: In North America, besides coding, the medical field has more private real data barriers. 2) Complex processes and accumulation of expert experience: Medical diseases and treatments are complex, highly dependent on expert judgment. 3) Huge market potential: The global drug research and development outsourcing service market size is expected to increase from $151.2 billion in 2023 to $363.2 billion in 2030, with a CAGR of 13.3%. On an overseas level, North American giants have been intensively promoting the substantial products and functions of AI+ healthcare since the beginning of 2026. From a capital level, 2026 is expected to see leading companies in the AI+ pharmaceutical industry achieve positive EBITDA for the first time, leading to a period of valuation reconstruction in the industry. For example, in August 2025, Xtalpi announced a pipeline cooperation agreement with DoveTree worth 47 billion Hong Kong dollars ($5.9 billion), setting a new record for AI pharmaceutical orders, supporting its business growth. At the theoretical level, in the clear rules of the molecular world, AI has become the "accelerator" for new drug discovery. Postal Securities believes that AI models, especially deep learning and generative models, can efficiently learn the complex mapping relationship between molecular structure, chemical bonds, physical and chemical properties, and biological activities. By predicting key parameters such as binding energy, solubility, and toxicity, AI can rapidly screen, optimize, or even design potential candidate molecules or new materials in a virtual space, potentially shortening the time for drug discovery, directly improving the success rate and efficiency of new drug discovery, and possibly creating new compounds beyond human intuition, driving the paradigm shift and technological leap of the entire pharmaceutical industry from the ground level up. On a national support level, Xtalpi has won two national major research topics, leading the upgrade of AI for Science and the new material industry. 1) "New Generation Artificial Intelligence National Major Research Project": Building a scientific knowledge map around AI4S, creating an artificial intelligence experimental platform, empowering research and development in the field of new drugs and new materials. 2) "Key Research and Development and Application of New Materials National Major Research Project": Building a platform and infrastructure for foundational algorithms around the efficient acquisition and intelligent processing of material data. In terms of investment targets, it is recommended to focus on AI for Science, AI+ pharmaceutical industry tracks such as Xtalpi (02228), INSILICO (03696), TempusAI (TEM.US), WuXi AppTec (02359), Jiangsu Hengrui Pharmaceuticals (01276), etc. Risk factors include macro-environmental impact risks, domestic and international situations, GEO Group Inc. political risks, slower than expected progress in key technologies, increased market competition risks, cross-market valuation differences, high research and development expenditure pressures, unexpected key orders or products, etc.