The global outsourced drug R&D services market is projected to expand from $151.2 billion in 2023 to $363.2 billion by 2030, achieving a compound annual growth rate (CAGR) of 13.3%. Artificial intelligence has become a powerful "acceleration engine" for novel drug discovery, enabling the rapid virtual screening, optimization, and even de novo design of promising candidate molecules or new materials by predicting critical parameters such as binding energy, solubility, and toxicity, which holds the potential to significantly shorten drug discovery timelines.
By 2026, leading companies in the AI+pharmaceutical sector, exemplified by XTALPI and TEMPUS, are expected to achieve positive EBITDA for the first time, signaling an impending industry-wide valuation reassessment period. The primary viewpoints of China Post Securities are outlined as follows.
Analyzing the case of PLTR, which surged 25-fold over three years, reveals that promising AI application sectors typically share key characteristics: 1) Vast reserves of real-world data: In North America, aside from coding, the medical field possesses significant barriers built on proprietary, real-world data; 2) Complex processes and accumulated expert knowledge: Medical diagnostics and treatment practices involve intricate disease classifications and highly depend on specialist judgment; 3) Substantial potential market size: The global outsourced drug R&D services market is set to grow from $151.2 billion in 2023 to $363.2 billion by 2030, with a CAGR of 13.3%.
On the international front, North American tech giants have been intensively rolling out substantive AI+healthcare products and features early in 2026. On January 8, OpenAI launched the significant ChatGPT Health to provide customer health consultation services, addressing over 230 million health-related inquiries weekly. On January 12, NVIDIA and Eli Lilly announced a plan to invest $1 billion over five years to establish a new joint research lab in the San Francisco Bay Area aimed at accelerating AI-driven drug discovery. Also on January 12, Anthropic introduced its healthcare and life sciences service, allowing users of its Claude AI platform to share access to their health records for better medical insights. On January 14, OpenAI announced the $100 million acquisition of Torch, an online medical data integration startup with just four employees.
From a capital markets perspective, 2026 is poised to witness a potential dual catalyst of improving performance and valuation re-ratings for leaders in the AI+pharmaceutical sector. Leading firms like XTALPI and TEMPUS are anticipated to achieve positive EBITDA for the first time in 2026, marking the onset of an industry valuation recalibration phase. Taking XTALPI as an example, in August 2025, the company announced a HKD 47 billion (USD 5.99 billion) pipeline collaboration with DoveTree, setting a new record for the scale of outbound AI drug discovery orders and supporting its anticipated significant revenue growth in 2026. In the first half of 2025, XTALPI's drug discovery solutions business revenue reached RMB 435 million (year-on-year growth of 616%), and it established partnerships with multiple multinational pharmaceutical companies (such as Johnson & Johnson, Eli Lilly, and Pfizer), reflecting its growing international recognition and providing solid footing for future development.
At the fundamental level, within the rule-based molecular world, AI has become an "acceleration engine" for new drug discovery. China Post Securities posits that AI models, particularly deep learning and generative models, can efficiently learn the complex mapping relationships between vast molecular structures, chemical bonds, physicochemical properties, and biological activity. By predicting key parameters like binding energy, solubility, and toxicity, AI enables high-speed virtual screening, optimization, and even the de novo design of promising candidate molecules or novel materials. This approach promises to shorten drug discovery timelines, directly enhance the success rate and efficiency of identifying new drugs, and potentially create entirely new compounds beyond human intuitive cognition, thereby driving a fundamental paradigm shift and technological leap forward for the entire pharmaceutical industry.
Regarding national support, XTALPI has successively secured two major national key projects, positioning it at the forefront of AI for Science (AI4S) and new materials industrial upgrades. The first is the "New Generation Artificial Intelligence National Science and Technology Major Project," focused on building scientific knowledge graphs around AI4S, creating an AI experimentation platform to empower R&D in new drugs and materials. The second is the "Key New Materials R&D and Application National Science and Technology Major Project," addressing the critical need for efficient material data acquisition and intelligent processing by developing foundational algorithm platforms and infrastructure.
For investment targets, it is recommended to focus on the AI4S and AI+pharmaceutical sectors, including companies such as XTALPI (02228), Insilico (03696), Tempus AI (TEM.US), Wuxi AppTec (02359), and Hengrui Pharma (01276).
Investors should be mindful of risks including macroeconomic shocks, domestic and international situations, geopolitical tensions, potential delays in key technological advancements, intensified market competition, cross-market valuation discrepancies, pressure from high R&D expenditures, and the risk of key orders or products underperforming expectations.
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