从巨头布局到全场景渗透,AI+医药迈入竞争新阶段
2 1 Shi Ji Jing Ji Bao Dao·2026-01-30 11:34

Group 1 - The global pharmaceutical industry is experiencing a surge in AI initiatives, with major companies like Eli Lilly and NVIDIA collaborating to establish an AI innovation lab, and AstraZeneca acquiring Modella AI to enhance its capabilities in biomedical AI [1][4] - AI's role in drug development is evolving from a supportive tool to a core innovation engine, as evidenced by its prominence at the 2026 JPM Healthcare Conference [1][4] - The AI wave is impacting not only drug development but also permeating various sectors within the healthcare industry, with hospitals and tech giants entering the AI healthcare space [1][2] Group 2 - Deloitte's report indicates that the innovation return on investment (IRR) for the top 20 global pharmaceutical companies is only 5.9%, with the average cost of drug development rising from $2.12 billion in 2023 to $2.229 billion in 2024 [4] - AstraZeneca's AI initiatives include the AIDA system aimed at reducing development time by 50%, while Eli Lilly and NVIDIA plan to invest $1 billion over five years in their AI lab [4][5] - Domestic AI pharmaceutical companies are also making strides, with companies like InSilico Medicine and CrystalClear Technology forming significant partnerships to enhance drug development using AI [5] Group 3 - The global AI healthcare market is projected to grow at a compound annual growth rate (CAGR) of 43% from 2024 to 2032, with generative AI in healthcare expected to grow at an even higher CAGR of 85% [6][7] - AI is anticipated to save the U.S. healthcare system approximately $150 billion annually by 2026, with long-term investment returns in AI healthcare reaching 10%-15% [7] - Companies are increasingly integrating AI across the entire pharmaceutical value chain, from drug discovery to marketing and patient services, enhancing operational efficiency [7][8] Group 4 - Innovative companies are focusing on specific scenarios to launch AI products, gaining attention from the capital market, with examples including Hangzhou Quanzhen Medical Technology and its AI application "Quanzhen Tong" [8][9] - Many domestic AI healthcare products are still in the data accumulation phase, with those that can effectively integrate into real medical processes and address industry pain points emerging as the future mainstream [9]