时代财经注意到，这已经是英矽智能2026年开年以来达成的第四笔交易。在此之前，英矽智能先后与施 维雅、衡泰生物、齐鲁制药达成合作，首付款、预付款及近期研发里程碑付款总计为4200万美元，总金 额累计超10亿美元，涉及抗肿瘤、中枢神经系统及自身免疫疾病领域。 除英矽智能外，国内AI制药领域的另一家明星企业晶泰科技（02228.HK）也在近期先后与甘李药业 （603087.SH）、维昇药业（02561.HK）达成合作，主要聚焦在代谢领域。 进入2026年，AI制药领域的合作签约明显提速。 2月10日，AI制药企业英矽智能（03696.HK）宣布与康哲药业（00867.HK）达成数千万港元AI药物研发 合作。 公告显示，双方将在中枢神经系统及自身免疫疾病领域的多个项目上达成一系列由AI赋能的创新药物 研发合作。根据协议条款，双方将结合英矽智能已验证的AI平台与AI赋能创新药研发能力，以及康哲 药业经验丰富的研发团队和对疾病领域的深度认知，共同推进不少于2个研发项目的合作开发。同时， 英矽智能有望就每个项目获得最高达数千万港元的研发费用支持。 或受此消息影响，2月10日，英矽智能盘中一度涨超11%，最终报收72.25 ...

编者按：英矽智能凭借生成式AI平台，提高了药物研发的效率，已开发出多个潜力管线，且与多家跨国制药巨头达成了合作，通过自主研发+对外授权构 筑了一定的护城河。 英矽智能成立于2014年2月10日，由Alex Zhavoronkov博士创立，是一家AI驱动药物发现及开发公司。 目前，公司已透过自主开发的生成式人工智能平台Pharma.AI产生逾20项临床或IND申报阶段的资产，其中三项资产已授权予国际制药及医疗保健公司， 合约总价值最高为21亿美元，以及一项处于自主开发阶段的II期资产，在业界中处于相对较为先进的阶段。 01、行业背景：AI可以提升药物发现流程中各阶段的效率 AI药物发现及开发(AIDD)正成为制药产业日益重要的趋势。 AI技术可以应用于药物开发的早期与后期阶段，有助于更高效率地识别靶点、设计分子并优化临床试验。 英矽智能招股书中预期，全球AIDD市场的规模将由2023年的119亿美元增加至2032年的746亿美元，复合年增长率为22.6%。 基于AI的药物发现的主要优势在于，AI可以提升流程中各阶段的效率，应对药物发现中的关键挑战。 AI可分析庞大且复杂的数据集，以识别潜在候选药物、发掘生物标志 ...

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]

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].

消息面上，开年仅一个月，英矽智能已达成三笔重磅合作。1月5日，公司与施维雅达成8.88亿美元研发 合作，聚焦创新抗肿瘤疗法；1月20日，与深圳衡泰生物就ISM8969项目达成合作，加速推进全球开 发，双方各持50%权益，英矽智能主导IND申报及I期临床试验；1月27日，与齐鲁制药达成超9.31亿港 元合作，关注代谢疾病领域新颖小分子药物设计与优化。 浙商证券发布研报称，AI制药核心价值在于大幅提升药物早研效率，以英矽智能Pharma.AI为例，其能 够使候选药物从靶点发现到临床前候选药物确认时间从4.5年大幅缩短到12至18个月，早研阶段的投入 产出比大幅提升。该行指出，国内多家AI制药平台服务能力全球领先，海外业务拓展持续高速已验 证，关注英矽智能等。 智通财经APP获悉，英矽智能(03696)早盘涨超11%，高见66.45港元，再创历史新高。截至发稿，涨 9.88%，报65.6港元，成交额5531.91万港元。 ...

浙商证券（601878）发布研报称，AI制药核心价值在于大幅提升药物早研效率，以英矽智能Pharma.AI 为例，其能够使候选药物从靶点发现到临床前候选药物确认时间从4.5年大幅缩短到12至18个月，早研 阶段的投入产出比大幅提升。该行指出，国内多家AI制药平台服务能力全球领先，海外业务拓展持续 高速已验证，关注英矽智能等。 消息面上，开年仅一个月，英矽智能已达成三笔重磅合作。1月5日，公司与施维雅达成8.88亿美元研发 合作，聚焦创新抗肿瘤疗法；1月20日，与深圳衡泰生物就ISM8969项目达成合作，加速推进全球开 发，双方各持50%权益，英矽智能主导IND申报及I期临床试验；1月27日，与齐鲁制药达成超9.31亿港 元合作，关注代谢疾病领域新颖小分子药物设计与优化。 英矽智能(03696)早盘涨超11%，高见66.45港元，再创历史新高。截至发稿，涨9.88%，报65.6港元，成 交额5531.91万港元。 ...

Core Insights - The emergence of AI technology is expected to significantly enhance the efficiency of drug development in the biopharmaceutical industry, potentially leading to a transformative impact on investment returns in the sector [1][3][4] Industry Overview - The global AI-enabled drug development market has grown from $5.37 billion in 2019 to $11.9 billion in 2023, with a compound annual growth rate (CAGR) of 22%. It is projected to reach $74.6 billion by 2032, with a CAGR of 22.6% [4] - AI is increasingly integrated into the entire drug development process, from target discovery to clinical trial design and even production and sales [3][4] Company Insights - Insilico Medicine is a leading company in the AI drug development field, focusing on validating the commercial viability of AI in drug discovery. It has made significant progress in clinical trials compared to its peers in the AI+Biotech sector [1][4] - The company has developed an integrated AI drug discovery platform, Pharma.AI, which covers the entire drug development process and has produced 27 preclinical candidate compounds and 13 drug pipelines that have received clinical trial approval [7] - Insilico Medicine's typical pipeline products can advance from discovery to preclinical stages in 12-18 months, compared to the traditional 3-6 years, showcasing a clear efficiency advantage [7] Challenges and Future Directions - Despite advancements, no drug designed by AI has yet been approved for commercialization, which remains a significant challenge for the AI drug development industry [8] - Insilico Medicine is actively working to accelerate drug development processes and is exploring collaborations to expedite the approval of its drug candidates [8] - The competition among AI drug companies is expected to shift from algorithm superiority to data resource advantages, emphasizing the need for extensive data accumulation for model training [10][11] Data Utilization - Data is crucial for AI technology, and the ability to leverage real-world medical data from hospitals is seen as highly valuable for both traditional and AI drug companies [11] - There are regulatory challenges in accessing and utilizing medical data in China, which limits its commercial potential [12] - Suggestions have been made to separate data ownership and usage rights to facilitate the flow of medical data for pharmaceutical use, drawing on examples from the U.S. [12]

Core Viewpoint - The article discusses the volatility and potential of AI application stocks, highlighting the recent surge and subsequent decline in their prices, emphasizing the need for logical investment rather than speculative trading [3][4][6]. Group 1: AI Application Market Dynamics - The AI application market saw a significant surge starting January 9, driven by the IPO of MiniMax, which rose over 90%, boosting market confidence in AI commercialization [3][4]. - Following the initial excitement, many AI companies issued announcements clarifying their limited revenue from AI, leading to a sharp price correction in the sector [4][5]. - The article suggests that while the current market may present opportunities, investors should focus on companies with genuine value and sustainable business models [4][7]. Group 2: GEO Model in Advertising - The article introduces the GEO (Generative Engine Optimization) model as a transformative approach in advertising, allowing users to input specific demands and receive optimized product recommendations directly from AI [9][11]. - The GEO market is projected to grow significantly, with estimates of $2.9 billion in China and $11.2 billion globally by 2025, indicating a shift from traditional SEO to AI-driven marketing strategies [11][12]. - Companies that own AI models and user behavior data are expected to be the primary beneficiaries of the GEO model, similar to how Google and Baidu benefited during the SEO era [12][13]. Group 3: AI in Healthcare - The AI healthcare sector has shown strong performance, with companies like 泓博医药 and 迪安诊断 seeing over 50% gains year-to-date, driven by increasing market interest [22][24]. - Government policies are increasingly supportive of AI in healthcare, with initiatives aimed at integrating AI into medical services and diagnostics [24][25]. - The article notes that advancements in AI healthcare applications, such as OpenAI's ChatGPT Health, are enhancing market sentiment and could lead to further growth in the sector [26][29]. Group 4: AI in Financial Technology - The financial technology sector has also experienced growth, with a 14% increase in the financial technology ETF as of January 14, 2026 [37]. - AI is expected to enhance the capabilities of both internet finance companies and financial IT firms, improving customer engagement and operational efficiency [38][39]. - However, the article cautions that while AI can improve operational efficiencies, it may not fundamentally change the poor business models prevalent in financial IT companies [40].

Core Viewpoint - The AI healthcare sector is experiencing significant growth and interest in 2026, with the AI healthcare index rising over 11% in just 14 trading days, indicating a clear trend in capital market enthusiasm for this sector [1][2]. Market Performance - As of January 22, 2026, the AI healthcare index increased by over 11%, while the CSI Medical Index and Hang Seng Healthcare Index rose by 7.68% and 10.65%, respectively [1]. - Companies like Di'an Diagnostics and Baolait have seen their stock prices surge over 60%, with others like Weining Health and Chengdu Xian Dao also experiencing gains exceeding 30% [1]. Industry Growth Projections - According to Frost & Sullivan, the AI healthcare market in China is projected to grow from 8.8 billion yuan in 2023 to 315.7 billion yuan by 2033, with a compound annual growth rate (CAGR) of 43.1% [1]. Technological Advancements - Major tech companies are actively entering the AI healthcare space, with OpenAI launching a healthcare version of ChatGPT and other firms like Ant Group, Tencent, JD, and ByteDance developing AI healthcare models and applications [5][6]. - AI drug development is identified as the fastest-growing segment within AI healthcare, with companies like Insilico Medicine and WuXi AppTec significantly reducing drug development timelines [6][7]. Commercialization Challenges - Despite the enthusiasm, the commercialization of AI healthcare products is facing challenges, with many companies reporting losses. For instance, 24 out of 47 biomedicine companies forecasted losses or reduced profits for 2025 [10]. - Companies like KingMed Diagnostics and Anbiping are experiencing significant revenue declines, with Anbiping reporting a 28.29% drop in revenue year-on-year [10][11]. Regulatory Developments - Recent government policies are seen as a positive signal for the AI healthcare sector, with initiatives aimed at promoting and standardizing AI applications in healthcare [15][16]. - The National Healthcare Security Administration has clarified pricing for AI-assisted diagnostic services, which is expected to facilitate the integration of AI into routine clinical practice [15][16]. Future Outlook - Industry experts predict that 2026 will be a pivotal year for AI healthcare, with clearer payment structures and stronger financial backing expected to enhance commercialization prospects [16].

如果要问2026年开年来最火爆的板块，AI 医疗一定占据一席之地。 2026年开年仅13个交易日，医疗板块强势崛起，截至1月21日收盘，AI医疗指数大涨逾 11%，中证医疗 指数、恒生医疗保健指数也分别上涨了 8%、11.67%。期间，迪安诊断（300244）、宝莱特（300246） 年内暴涨超过 60%，卫宁健康（300253）、成都先导等涨幅也超过了20%。 一批踏空2025年行情的另类医疗主题基金，纷纷迎来业绩红包，AI医疗概念的资本热度已在资本市场 形成明确趋势。 然而，随着AI医疗主题的全面爆发，市场争议也随之而来。 一方面，技术突破、政策利好与市场需求多重驱动下，AI医疗从实验室走向临床，应用场景也从辅助 诊断向全流程管理深度渗透。据弗若斯特沙利文预测，从2023年至2033年，中国AI医疗市场规模将从 88亿元飙升至3157亿元，年复合增长率高达43.1%。 细分赛道来看，AI制药作为AI医疗领域增长最快的细分赛道，正在掀起一场新药研发的"效率革命"。 如英矽智能旗下的Pharma.AI，能够使候选药物从靶点发现到临床前候选药物确认时间从4.5年大幅缩短 到12至18个月；药明康德（603259 ...