Investment Rating - The industry investment rating is "Strong Buy" [2]. Core Insights - The investment value of the AI+pharmaceutical industry lies in analyzing the current status and future potential of AI's role in drug development, focusing on efficiency and innovation [4]. - AI enhances drug development by reducing costs and increasing efficiency, particularly in the preclinical phase, where AI virtual screening significantly lowers the number of compounds needed for real trials, thus shortening development cycles and costs [5]. - The global market for AI-enabled drug development is projected to grow from $11.9 billion in 2023 to $74.6 billion by 2032, with a CAGR of 22.6% [5]. - The industry is experiencing a structural differentiation trend in financing, with a total of $24.6 billion raised globally for AI+drug development since 2015, although there has been a decline in financing activity in 2022 due to economic downturns [48]. Summary by Sections AI's Role in Pharmaceuticals - AI in drug development combines technologies like NLP and deep learning to enhance efficiency and expand innovation space across the entire drug development process [9]. - AI's most mature applications are in preclinical research, where it can reduce costs by over 90% and significantly shorten development timelines [22]. High-Quality Data Production as Core Competitiveness - The ability to produce high-quality data is identified as a core competitive advantage in the industry, as it enables effective algorithm iteration and data accumulation [6]. - The industry faces challenges with "data silos," where high-quality data is scarce and not shared, making data production capabilities crucial for long-term competitiveness [6]. Market Size and Commercialization Focus - The AI+pharmaceutical financing landscape has seen rapid growth, with significant investments concentrated in the US and China, although the latter's share has decreased recently [48]. - The commercial focus is shifting towards molecular entities, with AI+CRO and AI+Biotech models emerging as dominant trends for revenue generation [58]. Business Models - The industry features three main business models: SaaS, AI+CRO, and AI+Biotech, with the latter two being more prevalent due to their higher revenue potential and lower risk exposure [63][67]. - SaaS models face challenges due to limited market size and high competition, suggesting that they may not be suitable for new entrants in the industry [67].