证券代码：300583 证券简称：赛托生物 山东赛托生物科技股份有限公司 投资者关系活动记录表 编号：DY2025-001 投资者关系活 动类别 □特定对象调研 □分析师会议 □媒体采访 业绩说明会 □新闻发布会 □路演活动 □现场参观 □其他 参与单位名称 及人员姓名 参与公司 2024 年度业绩网上说明会活动的投资者 时间 2025 年 5 月 9 日 15:00-17:00 地点 "价值在线"平台（www.ir-online.cn） 上市公司接待 人员姓名 董事长米奇先生 财务总监李福文先生 董事、副总经理、董事会秘书李璐女士 独立董事康立女士 保荐代表人刘彦先生 投资者关系活 动主要内容介 绍 公司于 2025 年 5 月 9 日 15:00-17:00 在"价值在线"（www.ir- online.cn）举办 2024 年度业绩网上说明会，本次业绩说明会采用网络远 程的方式举行，问答环节主要内容如下： 1、问：过去一年，公司的经营策略是什么？ 回复：尊敬的投资者，您好！过去一年，公司董事会管理层确定的经 营策略主要可以用"稳份额、保现金、推注册、剥资产"十二字概括，在 董事会的领导下，公司在生产端严 ...

Core Insights - The article highlights the significant potential of AI in the healthcare sector, particularly in remote medical services and diagnostics, with a focus on the acquisition of Shanghai Siwei Medical Technology Co., Ltd. by Jingtai Holdings for 250 million yuan [1][2][3] Company Summary - Jingtai Holdings has acquired 90% of Shanghai Siwei Medical, the largest remote ECG diagnostic service provider in China, to enhance its AI healthcare business and support drug development [1][2] - The acquisition will enable Jingtai to integrate clinical, molecular, and imaging data to develop precise and efficient remote diagnostic tools for cardiovascular diseases [2][6] - Jingtai aims to leverage Siwei's extensive structured ECG data and clinical experience to create a high-efficiency remote medical and AI-assisted diagnostic platform [6][7] Industry Summary - Cardiovascular diseases are the leading cause of death in China, accounting for over 45% of total deaths, with a significant market for ECG monitoring, estimated at 21 billion yuan [3][4] - The remote ECG testing market is projected to reach 10 billion yuan by 2022, driven by the increasing demand for advanced healthcare solutions amid a shortage of specialized medical professionals [3][4] - Government policies, such as the "Healthy China 2030" initiative, are promoting the integration of AI in healthcare, encouraging the development of remote medical services [4][5]

Core Viewpoint - Insilico Medicine, an AI pharmaceutical company, has submitted its IPO application for the third time after previous attempts failed, indicating a prolonged journey of nearly two years towards going public [1] Group 1: Business Overview - Insilico Medicine operates in three main segments: drug discovery and pipeline development, software solutions, and other discoveries related to non-pharmaceutical fields [2] - The company utilizes its generative AI platform, Pharma.AI, to discover new drug targets related to diseases and to identify promising drug candidates for further development [2] - Currently, the company's drug candidates have not yet been commercialized, with revenue primarily generated from licensing agreements for three candidate drugs [2] Group 2: Financial Performance - Insilico Medicine's revenue for the years 2022 to 2024 was approximately $30.15 million, $51.18 million, and $85.83 million, respectively [3] - The company's net losses for the same years were approximately $222 million, $212 million, and $17 million, respectively [3] Group 3: Funding and Investment - The AI pharmaceutical sector is rapidly evolving, with Insilico Medicine completing multiple funding rounds since its establishment in 2014, attracting notable venture capital and industry investors [4] - The latest funding round, an E round, raised $110 million, led by Hillhouse Capital and involving several prominent investors [4] - The funds raised will accelerate the development of the company's drug pipeline and AI platform [4] Group 4: Industry Context - In 2024, global financing for AI-driven drug development reached $5.8 billion across 128 deals, highlighting the industry's attractiveness to investors despite the lack of profitable standalone AI pharmaceutical companies [5]

百图生科技术副总裁张晓明（图片来源：受访者提供） 新药研发是人类发展中极具风险和复杂度、耗时最漫长的技术研究领域之ー。 今年1月，英国《自然》杂志子刊《自然医学》（Nature Medicine）发表的一篇论文显示，平均而言， 新药的研发投入约26亿美元，可能需要耗时12-15年，但不幸的是，即使在临床试验阶段，新药的成功 率也低于10%。 上述论文认为，新药研发复杂的原因在于，传统药物研发依赖于药物开发人员的经验和反复试验，尤其 寻找潜在候选药物需要探索的化学空间之大，而且监管要求非常严格，满足安全性、有效性和质量标准 可能是一项耗时且成本高昂的工作。因此，为了克服这些挑战，科学家们一直在积极探索新技术和新方 法，以改进药物开发流程。 如今，AI 技术的出现，尤其是大模型在内的生成式AI技术，融入药物开发流程——靶点识别、药物发 现、临床研究等，有望重塑传统药物研发模式，从而有效提升药物研发效率。 最新数据显示，目前全球已经有3800家企业、4900家投资机构入局AI生物领域，相比四年前笔者发表 的《AI何以成"药神"》深度文章中提到入局的300家企业、880家投资机构，分别增长了1166.7%、 456. ...

Core Viewpoint - Insilico Medicine is attempting to go public on the Hong Kong Stock Exchange for the third time, having previously failed to pass hearings within the required timeframe. The company is a drug discovery firm driven by generative artificial intelligence, with a focus on developing innovative therapies for diseases like idiopathic pulmonary fibrosis (IPF) [1][2]. Company Overview - Insilico Medicine was founded in 2014, initially in the United States, and established its headquarters in Hong Kong in 2019 [1]. - The company has developed over 20 clinical or IND (Investigational New Drug) stage assets using its Pharma.AI platform, with three assets licensed to international pharmaceutical companies, generating contracts worth over $2 billion [1][2]. Product Pipeline - The core product, ISM001-055, is a potent selective inhibitor of TNIK, currently in Phase II clinical trials for the treatment of IPF. It received orphan drug designation from the FDA in February 2023. The company plans to submit IND applications for kidney fibrosis treatment in the first half of 2025 and for inhaled ISM001-055 for IPF in the second half of 2025 [1][2]. Market Context - Currently, only two drugs, Pirfenidone and Nintedanib, are approved for IPF treatment, with limited clinical efficacy. Pirfenidone's patent has expired, leading to the introduction of generics, while Nintedanib generics are expected to launch in 2026 and 2029 in the US and China, respectively. Nearly 300 IPF candidates are in clinical stages, with ISM001-055 still in Phase II, indicating a competitive landscape [3]. Financial Performance - Insilico Medicine has not yet achieved profitability, reporting losses of $222 million, $212 million, and $17.1 million from 2022 to 2024, with losses gradually narrowing. Cash and cash equivalents at the end of these years were $208 million, $177 million, and $126 million, respectively [4]. - The company’s revenue has been growing, with figures of $30.147 million, $51.18 million, and $85.834 million from 2022 to 2024. The primary revenue source is drug discovery and pipeline development services, accounting for approximately 95% of total revenue in 2022, declining slightly to 92.9% in 2024 [2][4]. Funding and Valuation - Insilico Medicine has completed nine rounds of financing, raising over $500 million, with the latest E round in early 2023 bringing in $110 million and valuing the company at $1.3305 billion [5]. - The funds from the potential Hong Kong IPO will be allocated to further clinical development of pipeline candidates, developing new generative AI models, and expanding automated laboratories [5]. Competitive Landscape - Insilico Medicine and Crystal Clear Technologies represent two distinct business models in the AI drug discovery sector. Insilico focuses on developing innovative drugs, while Crystal Clear operates as a contract research organization (CRO), providing drug development services using AI technology [6].

Core Viewpoint - Insilico Medicine, known as the "first stock" in AI drug development, has submitted its application for a Hong Kong IPO after previous setbacks, reflecting both opportunities and challenges in the AI pharmaceutical industry [1][2]. Company Overview - Insilico Medicine was founded in 2014 and established its presence in Shanghai in 2019, leveraging generative AI technology to develop a complete industry chain from target discovery to clinical validation [1]. - The company has undergone eight rounds of financing since 2018, with a post-money valuation of approximately $1.331 billion after a $100 million Series E round in February 2025 [2]. Financial Performance - Insilico Medicine's revenue has shown consistent growth, with figures of approximately $30.1 million, $51.2 million, and $85.8 million for the fiscal years 2022, 2023, and 2024, respectively, representing a revenue growth rate of 185% from 2022 to 2024 [2]. - The gross profit margins have improved significantly, recorded at 63.4%, 75.4%, and 90.4% for the same years [2]. - The adjusted losses have decreased from 70.8 million to 22.7 million over the same period [2]. Use of IPO Proceeds - The funds raised from the IPO are intended for further clinical development of key pipeline candidates, development of new generative AI models, expansion of automated laboratories, and general corporate purposes [2]. Industry Context - The AI-driven pharmaceutical sector is experiencing significant growth, with AI applications potentially increasing the success rate of new drug development from 12% to approximately 14%, saving the biopharmaceutical industry around $1 billion in R&D costs [4]. - In 2022, there were 144 financing events in the AI drug development sector, totaling $6.202 billion, indicating strong market interest, although 2023 saw a decline in financing events and amounts [4]. Challenges in AI Drug Development - Despite the rapid development of AI in pharmaceuticals, challenges remain in commercialization due to technical, data, regulatory, and market acceptance barriers [3]. - The domestic AI pharmaceutical sector is still in early financing stages, with most companies not yet reaching Series C funding [5]. - The reliance on incomplete and inconsistent external data may affect the accuracy of AI models used by Insilico Medicine [10]. Future Prospects - Insilico Medicine's ISM001-055, a selective TNIK small molecule inhibitor, is progressing rapidly through clinical trials, with plans for further studies in China and the U.S. [6][7]. - The overall market for AI in drug development is projected to reach $530 billion by 2030, contingent on successful integration of AI technologies and regulatory cooperation [11].

Group 1 - The emergence of young entrepreneurs in the AI sector is reshaping wealth creation, with notable figures like Alexandr Wang and Lucy Guo becoming billionaires through their company Scale AI, which is valued at over $25 billion [2][5][19] - The AI industry is witnessing a generational shift, with 90s-born entrepreneurs leading the charge, as seen with companies like Manus and Zhiyuan Robotics, which are valued at over 15 billion yuan and are focusing on AI agents and robotics [2][9][19] - The current technological landscape is transitioning from a focus on internet-based business models to a deeper emphasis on technological innovation and practical applications in AI, as evidenced by the strategies of companies like Manus and Yushu Technology [10][11][19] Group 2 - The AI data annotation sector is rapidly growing, with several Chinese companies emerging as leaders, including Yunce Data and Telecom Xinghai, reflecting a significant talent pool and investment in AI capabilities [6][7][19] - The investment landscape is shifting, with major tech companies like Amazon and Google increasing capital expenditures on AI and cloud services, which is expected to enhance the investment sentiment in Hong Kong's AI industry [17][19] - The Chinese AI industry is poised for long-term growth, supported by favorable policies and a robust manufacturing base, which positions companies like Yushu Technology to capitalize on the demand for AI solutions [19][20]

证券代码：300199 证券简称：翰宇药业 深圳翰宇药业股份有限公司 投资者关系活动记录表 编号：2025-001 | | ☐特定对象调研 ☐分析师会议 | | --- | --- | | | ☐媒体采访 业绩说明会 | | 投资者关系活动类别 | ☐新闻发布会 ☐路演活动 | | | ☐现场参观 | | | ☐其他（请文字说明其他活动内容） 个人投资者：线上参与公司2024年度暨2025第一季度网上业绩说明 | | | 会的投资者 | | | 机构投资者（排名不分先后）：中信建投、国盛证券、民生证券、方 | | 参与单位名称及人员姓名 | 正证券、华福证券、中泰证券、招商证券、国联民生证券、信达证券、 | | | 兴业证券、财通证券、东方证券、国投证券、浙商证券、申万宏源研 | | | 究、华创证券、华安证券、Citi等多家机构 | | 时间 | 2025年05月08日 15:30-17:00 | | 地点 | 东方财富路演（https://roadshow.eastmoney.com/）网络互动 | | 上市公司接待人员姓名 | 董事长、总裁 曾少贵 | | | 董事、执行总裁 PINXIANG YU ...

Group 1 - The core viewpoint of the news is that the investment landscape in China is showing positive trends, with significant fund inflows and new fund launches indicating confidence in the market [1][2][4]. Group 2 - On May 6, 2023, Fortune Fund announced a commitment to invest at least 25 million yuan in the Fortune Balanced Investment Mixed Securities Investment Fund, with senior management contributing a minimum of 20 million yuan and the proposed fund manager contributing at least 5 million yuan [1]. - In April 2023, the new fund issuance reached 901.56 million units, with 119 new funds launched, of which 84 were stock funds raising 435.53 million units, accounting for 48.31% of the total [2]. - As of April 30, 2023, over 2.7 billion yuan has been funneled into the market through ETFs, with a net subscription of 1.72 billion yuan in equity ETFs since early 2023 [3][4]. - The North Exchange market has seen a surge, with several funds achieving over 50% growth this year, indicating strong interest from public funds [5]. - On May 1, 2023, E Fund announced the sale of 3 million shares of China Merchants Bank due to regulatory limits, highlighting the challenges faced by fund managers in maintaining compliance [6][7]. - Investment manager Zhou Sicong emphasized that the focus of AI in pharmaceuticals should be on drug development rather than the AI technology itself, indicating a cautious approach to AI-driven investments in the pharmaceutical sector [8].

Core Insights - The integration of AI in drug development is transforming the pharmaceutical industry, significantly reducing the time and cost associated with bringing new drugs to market [2][3][11] - AI technologies have demonstrated the ability to shorten the drug development timeline from an average of 10-15 years and costs of $1-2 billion to approximately 1.5 years and $2.6 million [3][4] - The potential market for AI in drug development is projected to reach between $280 billion and $530 billion by 2030, with a compound annual growth rate exceeding 30% [7][11] AI in Drug Discovery - AI has enabled pharmaceutical companies to enhance drug discovery efficiency, with examples including the identification of lead compounds from millions of candidates using AI-driven high-throughput screening [4][6] - Companies like Pfizer have successfully utilized AI to reduce the development cycle of innovative drugs for rare genetic diseases to one-third of traditional methods, with costs reduced to 1/200 [4][6] - AI models such as AlphaFold have revolutionized protein structure prediction, significantly accelerating drug development processes [6][10] Clinical Trials and Applications - AI is being used to optimize clinical trial designs, resulting in a 30% reduction in ineffective trial periods [6] - The Mayo Clinic has leveraged AI to predict early-stage cancers and generate personalized treatment plans, improving cure rates by 20% [6] - AI is also facilitating the discovery of new indications for existing drugs and enhancing synthetic planning, with some cases showing a 50% increase in synthesis efficiency [6][10] Market Trends and Investment - The AI healthcare market is expected to reach $15 billion by 2025, with drug development being one of the core areas of growth [7] - AI-driven pharmaceutical stocks have seen significant increases, indicating strong market interest and investment potential [7] - Despite the promising outlook, the commercialization of AI in drug development faces challenges, including high capital expenditure requirements and data fragmentation [8][9] Future Directions - The future of AI in drug development lies in integrating AI design capabilities with intelligent experimentation to create a closed-loop system for data accumulation and model iteration [10] - The industry is transitioning from experience-driven to data-driven approaches, with AI becoming a central engine in drug development [11] - Experts predict that as the costs of large models decrease and their performance improves, AI will reshape the global pharmaceutical landscape, creating trillion-dollar market opportunities [11]