2026.01. 30 本文字数：3193，阅读时长大约5分钟 作者 | 第一财经 吴斯旻 随着AI制药渡过最初的技术可行性验证阶段，生物医药领域的技术和资本加速向这一赛道聚集，却 也加剧了不同研发方向的资源分化：相较于因AI加持而更加火热的肿瘤、自身免疫疾病的药物研 发，在结核、疟疾以及尼帕病毒等原本就较为冷清的传染病药物研发中，AI制药项目启动寥寥。 但AI驱动抗病毒新药研发虽然冷门却是刚需。当前，公共卫生领域创新药物研发面临研发投入远 超"双十周期"（指一款创新药物从启动研发到最终上市，平均研发周期超过10年，研发成本超过10 亿美元），商业回报不确定性更强，靶点稀缺，病毒易变异并产生耐药性，动物模型稀缺且预测性 差，药物毒性和安全性挑战高等诸多堵点，为此，在受访业界人士看来，AI大模型对于这一赛道的 赋能效益或会更加显著。 AI如何生成"千里马"新药分子 "从AI制药平台本身而言，它可以用来设计传染病药物的AI大分子模型，也可以用于肿瘤、神经退行 性疾病、罕见疾病等研发领域，关键在于投入的优先级。"全球健康药物研发中心（GHDDI）数据科 学部负责人郭晋疆在接受第一财经专访时说。 GHDDI是由北京市 ...

随着AI制药渡过最初的技术可行性验证阶段，生物医药领域的技术和资本加速向这一赛道聚集，却也 加剧了不同研发方向的资源分化：相较于因AI加持而更加火热的肿瘤、自身免疫疾病的药物研发，在 结核、疟疾以及尼帕病毒等原本就较为冷清的传染病药物研发中，AI制药项目启动寥寥。 在郭晋疆看来，尽管在数据和算力基础上，"AI孔明"平台与一些纯商业化的AI制药平台仍有差距，但足 以支撑主要传染病新药研发的科研工作。"目前已有一些大型跨国药企(MNC)和全球科研团队使用'AI孔 明'平台或表达合作意愿"。 但AI驱动抗病毒新药研发虽然冷门却是刚需。当前，公共卫生领域创新药物研发面临研发投入远超"双 十周期"（指一款创新药物从启动研发到最终上市，平均研发周期超过10年，研发成本超过10亿美 元），商业回报不确定性更强，靶点稀缺，病毒易变异并产生耐药性，动物模型稀缺且预测性差，药物 毒性和安全性挑战高等诸多堵点，为此，在受访业界人士看来，AI大模型对于这一赛道的赋能效益或 会更加显著。 AI如何生成"千里马"新药分子 "从AI制药平台本身而言，它可以用来设计传染病药物的AI大分子模型，也可以用于肿瘤、神经退行性 疾病、罕见疾病等研发 ...

Core Viewpoint - InSilico Medicine leverages its generative AI platform to enhance drug discovery efficiency, developing multiple promising pipelines and establishing collaborations with several multinational pharmaceutical giants, thereby creating a certain competitive moat through a combination of in-house development and external licensing [5][6]. Industry Background - AI-driven drug discovery and development (AIDD) is becoming an increasingly important trend in the pharmaceutical industry, with AI technology applicable in both early and late stages of drug development to improve efficiency in identifying targets, designing molecules, and optimizing clinical trials [10][11]. Market Potential - The global AIDD market is projected to grow from $11.9 billion in 2023 to $74.6 billion by 2032, representing a compound annual growth rate (CAGR) of 22.6% [12]. Advantages of AI in Drug Discovery - AI can significantly enhance efficiency across various stages of drug discovery, addressing key challenges by analyzing large and complex datasets to identify potential drug candidates, discover biomarkers and therapeutic targets, predict pharmacological properties, and optimize clinical trial outcomes [15][16]. Company Overview - Founded in February 2014 by Dr. Alex Zhavoronkov, InSilico Medicine is an AI-driven drug discovery and development company that has generated over 20 clinical or IND-stage assets through its Pharma.AI platform, with three assets licensed to international pharmaceutical and healthcare companies, totaling a contract value of up to $2.1 billion [6][24]. Business Model - The company operates under a dual CEO structure, integrating generative AI with drug discovery and development through a collaborative operational model. The business model includes drug discovery and pipeline development, software solutions, and other non-pharmaceutical discovery businesses, with primary revenue sources from licensing and collaboration agreements [23][25]. Pipeline Development - InSilico Medicine has developed a robust pipeline of 20 clinical or IND-stage assets across various therapeutic areas, including fibrosis, oncology, immunology, metabolism, and pain management [28][30]. Collaborations and Partnerships - The company has established collaborations with 13 of the top 20 global pharmaceutical companies, with significant agreements totaling over $2 billion, reflecting strong confidence in its platform and pipeline [33][34]. Financial Performance - InSilico Medicine's revenue has shown rapid growth through external licensing, with revenues of $30.15 million, $51.18 million, $85.83 million, and $27.46 million for the years 2022, 2023, 2024, and the first half of 2025, respectively. However, the company remains in a loss position [37][39]. Future Outlook - The company is expanding the application of its Pharma.AI platform to various industries, including advanced materials, agriculture, nutritional products, and veterinary medicine, indicating a broadening of its operational scope [26].

Investment Rating - The report does not explicitly state an investment rating for the pharmaceutical industry. Core Insights - The advent of the AI infrastructure era is expected to transform the pharmaceutical landscape, shifting research from traditional laboratories to AI platforms, which will significantly alter the industry structure [3][5][8]. - Major pharmaceutical companies are increasingly investing in AI technologies, with significant capital being directed towards AI infrastructure, indicating a fundamental change in the innovation environment [11][12]. - Regulatory developments include China's support for the internationalization of pharmaceutical devices and the FDA's focus on food allergies, highlighting evolving regulatory landscapes [13][14]. Industry Frontiers - AI Infrastructure Era: The emergence of a multi-layer AI system is driving the largest infrastructure buildout in human history, requiring trillions in investment to fully realize its potential [8][11]. - Shift in R&D: Pharmaceutical research is transitioning from laboratory-based methods to AI-driven platforms, with companies like Eli Lilly leading the charge by reallocating R&D budgets towards AI technologies [11][12]. - Changing Industry Dynamics: The integration of AI into pharmaceutical companies is expected to reshape organizational structures, talent allocation, and capital distribution, enhancing efficiency and competitive advantages [11][14]. Capital Trends - Notable Developments: Corvus Pharmaceuticals' ITK inhibitor showed impressive clinical data, leading to a 212% stock price increase, indicating a growing focus on T-cell signaling pathways in atopic dermatitis [20][21]. - Accelerated AI Drug Development: Insilico Medicine has rapidly secured multiple strategic partnerships for drug development, showcasing the increasing effectiveness of AI in biopharmaceuticals [27][28]. Weekly Perspective - The report emphasizes that the AI infrastructure era will bring disruptive changes to the pharmaceutical industry, with the degree of AI integration determining future growth potential [5][36]. - The report highlights the importance of the CXO sector in benefiting from increased R&D demands and identifies untapped disease areas in the autoimmune sector as potential blue ocean opportunities for innovative drug companies [5][36]. Industry Chain Data Updates - The report provides updates on new drug approvals and applications in China, reflecting ongoing developments in the pharmaceutical landscape [38][39][42].

Investment Rating - The investment rating for the company is "Buy" (首次) [1] Core Insights - The company is a leading small molecule CDMO with over 25 years of experience, currently transitioning from a single small molecule business to a dual-driven model of "small molecule + emerging business" [5][17] - The new business segment is experiencing rapid growth, contributing significantly to revenue, while traditional business remains resilient [5][6] - The company is expected to achieve net profits of 1.16 billion, 1.30 billion, and 1.51 billion yuan for 2025, 2026, and 2027 respectively, with corresponding EPS of 3.23, 3.59, and 4.18 yuan [5] Financial Summary and Valuation Metrics - Revenue projections for 2025, 2026, and 2027 are 6.66 billion, 7.69 billion, and 8.94 billion yuan respectively, with year-over-year growth rates of 14.7%, 15.4%, and 16.3% [8] - The company’s gross margin is projected to be around 42% for 2025, with a net margin of 17.5% [8] - The current P/E ratios are 31.0, 27.8, and 23.9 for 2025, 2026, and 2027 respectively [8] Business Development and Strategy - The company is focusing on expanding its capabilities in the peptide and small nucleic acid sectors, with significant investments in production capacity [6][79] - As of H1 2025, the new business segment generated 756 million yuan in revenue, a 51.22% increase year-over-year, accounting for 23.71% of total revenue [6] - The company has established partnerships with major pharmaceutical companies, enhancing its market presence and customer base [44] Industry Trends - The global healthcare investment environment is gradually recovering, with a total investment of 63.88 billion USD in 2025, marking a 10.13% increase year-over-year [47] - The domestic healthcare investment market is also improving, with a total of 73.78 billion yuan in 2025, a 39.05% increase year-over-year [53] - The global CDMO market is expected to grow significantly, with the small molecule CDMO/CMO market projected to reach 112 billion USD by 2029, growing at a CAGR of 16.6% [65]

Core Viewpoint - The stock of Insilico Medicine (03696) has surged over 11% in early trading, reaching a new historical high of 66.45 HKD, driven by significant collaborations and advancements in AI-driven drug development [1] Group 1: Collaborations - Insilico Medicine has secured three major collaborations within the first month of the year, including an 888 million USD R&D partnership with Schwabe focused on innovative anti-tumor therapies [1] - On January 20, the company partnered with Shenzhen Hengtai Biopharmaceutical on the ISM8969 project to accelerate global development, with both parties holding 50% equity, and Insilico leading the IND application and Phase I clinical trials [1] - A collaboration with Qilu Pharmaceutical was established on January 27, valued at over 931 million HKD, focusing on novel small molecule drug design and optimization in the metabolic disease sector [1] Group 2: AI Drug Development - According to a report from Zheshang Securities, the core value of AI in drug development lies in significantly enhancing early-stage research efficiency, exemplified by Insilico's Pharma.AI, which reduces the time from target discovery to clinical candidate confirmation from 4.5 years to 12-18 months [1] - The report highlights that the return on investment during the early research phase has greatly improved, indicating a strong potential for growth in the AI pharmaceutical sector [1] - Domestic AI pharmaceutical platforms are noted to have globally leading service capabilities, with ongoing rapid expansion in overseas markets, emphasizing the importance of companies like Insilico Medicine [1]

Core Viewpoint - The stock of Insilico Medicine (03696) surged over 11% in early trading, reaching a historic high of 66.45 HKD, driven by significant collaborations and advancements in AI-driven drug development [1] Group 1: Collaborations - Insilico Medicine has secured three major collaborations within the first month of the year: - On January 5, a partnership with Schwabe was established for an 888 million USD R&D collaboration focused on innovative anti-cancer therapies [1] - On January 20, a collaboration with Shenzhen Hengtai Biotech was formed for the ISM8969 project, aimed at accelerating global development, with both parties holding 50% equity, while Insilico leads the IND application and Phase I clinical trials [1] - On January 27, a partnership with Qilu Pharmaceutical was announced, valued at over 931 million HKD, focusing on novel small molecule drug design and optimization in the metabolic disease sector [1] Group 2: AI Drug Development - According to a report by Zheshang Securities (601878), the core value of AI in drug development lies in significantly enhancing early-stage research efficiency. For instance, Insilico's Pharma.AI can reduce the time from target discovery to clinical candidate confirmation from 4.5 years to 12-18 months, greatly improving the return on investment during the early research phase [1] - The report highlights that several domestic AI drug development platforms possess globally leading service capabilities, with ongoing rapid expansion in overseas markets, emphasizing the potential of companies like Insilico Medicine [1]

【天风医药杨松团队】英矽智能调研要点：AI制药重塑产业生态，全面拥抱研发新浪潮，重点推荐 AI倍增研发效率 英矽智能是一家由生成式人工智能驱动的生物医药科技公司，公司成立于2014年，高管团队具备AI及生物科技背 景，利用AI工具推进药物研发。 与传统药物研发通常需要 2.5-4 年的时间周期相比，英矽智能在 2021 至 2024 年间的自研项目，从立项到提名临床 前候选药物 （PCC） 的 平均耗时 BD合作快速推进 公司最主要的商业模式为BD合作，自2021年开展药物研发以来，公司已陆续达成9个重要BD交易，交易总计签约 金额超过40亿美金。 仅2026年开年公司分别与施维雅（总金额 8.88 亿美元）、衡泰生物（总金额 5 亿港币）及齐鲁制药（总金额9.31 亿港元）达成三项BD。 第二个商业模式为SaaS软件服务，软件服务收入占比约5%-10%。 公司与礼来、英伟达等大公司有持续合作。 【天风医药杨松团队】英矽智能调研要点：AI制药重塑产业生态，全面拥抱研发新浪潮，重点推荐 AI倍增研发效率 英矽智能是一家由生成式人工智能驱动的生物医药科技公司，公司成立于2014年，高管团队具备AI及生物科技背 景 ...

Market Performance - The pharmaceutical sector increased by +0.29% on January 26, 2025, outperforming the CSI 300 index by 0.19 percentage points, ranking 8th among 31 sub-industries in the Shenwan classification [1] - Among sub-industries, vaccines (+7.99%), in vitro diagnostics (+3.73%), and blood products (+3.47%) showed the best performance, while hospitals (-2.01%), medical R&D outsourcing (-1.36%), and offline pharmacies (-1.18%) lagged behind [1] - Top three individual stock gainers were Maike Biological (+20.03%), Cap Bio (+20.03%), and Zhijiang Biological (+20.01%), while the biggest losers were Weikang Pharmaceutical (-8.50%), Medisi (-7.28%), and Meinian Health (-6.08%) [1] Industry News - Recently, InSilico Medicine announced that its self-developed oral NLRP3 inhibitor ISM8969 has received IND approval from the FDA for the treatment of Parkinson's disease [2] - The upcoming Phase 1 clinical trial will assess the safety, tolerability, and pharmacokinetic characteristics of ISM8969 in healthy volunteers, aiming to determine the recommended dosage for subsequent studies [2] - ISM8969 is an innovative NLRP3 inhibitor with ideal blood-brain barrier penetration characteristics, targeting pathological inflammatory responses to support neuronal survival and function in neurodegenerative disease patients [2] - The drug candidate was discovered and optimized using InSilico Medicine's AI platform, Chemistry42 [2] Company News - Jiuan Medical (002432) expects to achieve a net profit attributable to shareholders of 2.02-2.35 billion yuan in 2025, representing a year-on-year growth of 21.05%-40.83%, with a non-recurring net profit forecast of 2.07-2.40 billion yuan, up 23.18%-42.81% [3] - Sanofi Guojian (688336) anticipates a revenue of 4.20 billion yuan in 2025, a significant year-on-year increase of 251.76%, with a net profit of 2.90 billion yuan, up 311.35%, and a non-recurring net profit of 2.80 billion yuan, reflecting a staggering growth of 1038.21% [3] - Dabo Medical (002901) forecasts a net profit of 580-610 million yuan in 2025, a growth of 62.55%-70.96%, with a non-recurring net profit of 455-485 million yuan, up 59.42%-69.93% [3] - Microchip Biotech (688321) expects a revenue of 910 million yuan in 2025, a year-on-year increase of 38.32%, with a net profit of 53 million yuan, marking a return to profitability, and a non-recurring net profit of 38 million yuan, also indicating a return to profitability compared to the previous year [3]

Core Viewpoint - The strategic partnership between Dongyangguang Pharmaceutical and Jingtai Technology aims to create an industry-leading AI drug development engine, addressing the global R&D efficiency bottleneck in the pharmaceutical industry through a collaborative model of "pipeline co-creation + technology win-win" [1][2] Group 1: Partnership Details - Dongyangguang Pharmaceutical plans to invest several hundred million yuan in the joint venture with Jingtai Technology [1] - The collaboration will focus on the field of autoimmune diseases, combining Dongyangguang's expertise with Jingtai's AI capabilities to accelerate drug discovery and clinical translation [3] - Jingtai Technology will deploy a large-scale robotic experimental workstation cluster at Dongyangguang to establish an AI-driven automated drug development laboratory [2] Group 2: Technological Innovations - The partnership will develop a leading physiologically-based pharmacokinetic (PB-PK) model to optimize R&D decisions and reduce risks, enhancing the success rates of subsequent in vivo and clinical trials [2] - A comprehensive AI drug development engine will be co-built, targeting challenges in drug targets, molecular synthesis, structure-activity relationships, and pharmacokinetics [2][3] - The collaboration aims to create a "bottom-layer operating system" for AI drug development, leveraging Chinese data, algorithms, and manufacturing capabilities to enhance competitiveness in international markets [3] Group 3: Business Model and Ecosystem - The partnership will establish an AI supercomputing platform based on "computing power support + data development + ecological sharing," transforming data assets and AI products into a "Model as a Service" (MaaS) business model [3] - The collaboration is expected to generate a dual-flywheel effect of "new drug pipeline generation" and "monetization of technological foundations," allowing both companies to share in the commercial outcomes [3]