1月5日在上海浦东举行的引领区2026年抓投资优环境促发展大会上，浦东新区区长吴金城在做推介时讲 述了两家企业的上市故事，让人们对于浦东的创新逻辑和创新生态有了更清晰的了解。 在本轮资本周期的低谷中，浦东创投集团凭借专业的产业认知，洞见了英矽智能AI平台大幅压缩传统 药物研发周期的颠覆性潜力，预判了英矽智能核心管线在临床试验中取得的突破性进展。 2025年初，浦东创投集团以联合领投的身份，向英矽智能战略投资3000万美元，同时围绕投融资、产业 升级、园区合作等领域签署多项战略合作协议。 从上海虹 口区北外滩空中俯瞰中国(上海)自由贸易试验区陆家嘴片区（2023年1月10日摄）。新华社记者 方喆摄 两家企业，一家是在科创板上市的沐曦股份，一家是在港股上市的英矽智能。 沐曦股份是国内高性能通用GPU产品的领军企业之一。2025年12月17日，沐曦股份在上海证券交易所科 创板挂牌上市，发行价格为104.66元/股，募集资金总额41.97亿元。上市首日股价大幅高开，盘中最高 涨幅超过700%，市值一度突破3000亿元。 沐曦股份2020年在浦东成立，依托区域优越的产业生态与创新土壤，仅用3年时间，便推出两颗高性能 G ...

Core Insights - InSilico Medicine has become the first artificial intelligence biopharmaceutical company to list on the Hong Kong Stock Exchange under the main board listing rule 8.05, raising a total of HKD 2.277 billion, making it the highest fundraising biopharmaceutical IPO in Hong Kong for the year [1] - The IPO was co-sponsored by Morgan Stanley, CICC, and GF Securities, with a total issuance of 94.6905 million shares, of which 10% was allocated for public offering in Hong Kong, achieving an oversubscription rate of approximately 1,427.37 times, locking in subscription funds exceeding HKD 32.8349 billion [1] - The company plans to increase investment in its AI platform and innovative pipeline to accelerate the entry of more globally differentiated innovative projects into clinical trials [1] Company Collaborations - InSilico Medicine has established software licensing collaborations with 13 of the top 20 global pharmaceutical companies [2] - The company has also secured three pipeline licensing collaborations with Exelixis and Menarini, with a total collaboration potential of up to USD 2.1 billion, and has engaged in joint research collaborations with renowned pharmaceutical companies such as Fosun Pharma, Sanofi, and Eli Lilly [2] Key Asset - The core asset of InSilico Medicine is Rentosertib, a drug for treating idiopathic pulmonary fibrosis, which is the industry's most advanced first-in-class AI drug, having completed Phase IIa clinical trials domestically, marking a significant milestone in AI-driven drug development [1]

经济观察报记者张铃 此次英矽智能引入包括礼来、腾讯、淡马锡、施罗德、瑞银、橡树资本、易方达、泰康人寿等在内的15 家基石投资者，涵盖全球制药龙头、互联网巨头、国际主权基金与大型资管机构以及国内头部公募与险 资。这也是礼来与腾讯首次认购生物医药企业基石投资。 值得注意的是，英矽智能是第一家通过联交所主板上市规则8.05条上市的AI制药公司，该规则要求企业 既要有未来的管线预期，也要通过严格的盈利或收入测试，具备商业化落地的实证。 英矽智能的核心资产为一款治疗特发性肺纤维化的药物Rentosertib，这是业界进展最领先的全球首创 (first-in-class)AI药物，目前已在国内完成IIa期临床研究，标志着AI驱动药物开发的重要里程碑。 迄今，英矽智能已与全球前20大制药公司中的13家达成软件授权合作。另外，英矽智能已与Exelixis、 美纳里尼等全球制药企业达成了3项管线对外授权合作，合作总额最高可达21亿美元，并与复星医药 （600196）(600196.SH，02196.HK)、赛诺菲、礼来等全球知名制药企业达成了共同研发合作。 2025年12月30日，明星AI制药公司英矽智能(03696.HK)在 ...

12月30日上午，香港证券交易所交易大厅内掌声雷动， 国内AI制药领军企业、宜兴赴港上市公司——英矽智能 （股票代码：03696.HK）InSilico Medicine Cayman TopCo（以下简称"英矽智能"）正式在香港联交所挂牌交易，标志着这家深耕AI制药技术的硬科技企业迈入资本市场新阶段，也展示了宜兴通过 战略性股权投资带动新兴产业和未来产业发展的最新成果。 此次上市后，英矽智能将成为宜兴市第8家港交所上市企业，宜兴港交所上市企业数量位居无锡首位，全市上市企业总数也增至20家。 此次，英矽智能发行定价24.05港元/股，计划发行9469.05万股，预计募资约22.77亿港，将是2025年港股市场最大规模的生物科技IPO。发行募集的资金将 用于加大AI平台升级与自动化实验室建设，加速新分子、新机制、新靶点在多个疾病领域的研发推进，助力全球医药工业数智化转型。 今年初，英矽智能AI制药项目在市国控集团举行投资及落地签约活动，由市国控集团与锡创投联合设立的锡创兴宜健康产业基金，共同领投英矽智能E轮 1.23亿美元融资。此次合作不仅局限于资本层面，更在宜搭建了"基金+企业+项目"的平台，通过资本撬动创新 ...

Core Insights - The article discusses the significance of AlphaFold2, an AI tool developed by DeepMind, in predicting protein structures, particularly the giant protein titin, which has eluded complete structural analysis for over 70 years [1][3][4] Group 1: AlphaFold2 and Protein Structure Prediction - AlphaFold2 has revolutionized the field of protein structure prediction, achieving over 90% accuracy in predicting protein structures from amino acid sequences during the global protein structure prediction competition (CASP) in 2020 [6][4] - The database created by AlphaFold now contains over 200 million predicted protein structures, covering 98.5% of the human proteome, enabling researchers worldwide to explore protein functions more efficiently [6][4] - AlphaFold2 was utilized during the early stages of the COVID-19 pandemic to predict the structures of viral proteins, aiding in understanding the virus's mechanisms and potential treatments [8][10] Group 2: Applications in Disease Research - Researchers are using AlphaFold to study the impact of genetic mutations on diseases, such as osteoporosis, by comparing the structures of normal and mutated proteins [11][13] - The introduction of AlphaMissense allows scientists to assess the pathogenic potential of missense mutations, successfully categorizing 89% of human missense mutations and creating a directory for further research [13][11] Group 3: Environmental and Pharmaceutical Innovations - AlphaFold2 is also being applied to address environmental issues, such as plastic pollution, by helping scientists design enzymes that can efficiently degrade single-use plastics [14][17] - The integration of AlphaFold2 into drug discovery platforms, like Insilico Medicine's Pharma.AI, has led to the identification of a candidate drug for idiopathic pulmonary fibrosis, Rentosertib, which is currently in Phase II clinical trials [18][20] Group 4: Future Developments - The article highlights ongoing advancements in protein research, including the discovery of a new protein larger than titin and the release of AlphaFold3 and AlphaProteo, which enhance predictions of protein interactions and custom protein design [23][21] - Other AI models, such as RoseTTAFold and I-TASSER, are also contributing to solving long-standing challenges in protein folding, indicating a collaborative effort in the field [23]

Core Viewpoint - The article discusses how AI is revolutionizing the pharmaceutical industry, significantly reducing the time and cost associated with drug development, traditionally estimated at "10 years and $1 billion" for original innovative drugs [3][4]. Group 1: AI in Drug Development - By utilizing AI, companies like Insilico Medicine can reduce the number of molecules synthesized from hundreds to a few dozen, lowering trial costs to one-tenth of traditional methods [4]. - The time required to identify a clinical candidate has been shortened from 2.5-4.5 years to just 9-18 months, representing a reduction to one-third of the original timeline [4]. - The cost of developing a preclinical candidate has decreased from over $10 million to between $2 million and $3 million, which is one-fifth of the traditional cost [4]. Group 2: Competitive Advantages of Chinese AI Pharmaceutical Companies - Chinese AI pharmaceutical companies benefit from strong clinical resources, which enhance the speed and quality of clinical trials [4]. - For instance, Insilico Medicine's clinical trial for Rentosertib in China enrolled 71 patients in just over a year, compared to only 8 patients in the U.S. during the same period [4]. Group 3: Milestones and Challenges in AI Drug Development - Insilico Medicine's Rentosertib achieved a significant milestone by having its Phase IIa clinical trial results published in the prestigious journal Nature Medicine, marking a turning point for AI-driven drug discovery [6][7]. - Despite over 300 AI drug pipelines globally, many projects fail at early clinical stages, raising concerns about the future of AI in pharmaceuticals [6]. Group 4: Business Development and Financing - Insilico Medicine has completed 11 rounds of financing, totaling over $530 million, allowing it to navigate the challenges of the innovation drug sector [11]. - The company is actively pursuing business development (BD) opportunities, having secured a $550 million collaboration for a potential best-in-class oncology candidate [12]. - Insilico Medicine aims to generate cash flow through BD, with expectations of achieving 1-2 successful licensing agreements annually [13]. Group 5: Strategic Collaborations and Future Directions - Insilico Medicine has entered a strategic collaboration in the ADC (Antibody-Drug Conjugate) space, partnering with companies experienced in ADC development to establish a technology platform [16][17]. - The company is also exploring other cutting-edge fields such as aging research, sustainable chemistry, and agricultural innovation, while focusing primarily on its core biopharmaceutical domain [18].

Core Insights - The article highlights the emergence of innovative drug development as a dynamic and breakthrough industry, particularly focusing on Chinese pharmaceutical companies that are shifting from rapid follow-up to original research and development [2] Group 1: AI Drug Development - In 2025, the AI pharmaceutical company InSilico Medicine is advancing its clinical pipeline and increasing business development efforts to establish broader commercial collaborations [3] - The transition from traditional drug development to AI-driven methods has significantly reduced the time and cost associated with developing clinical candidates, with InSilico requiring only 9 to 18 months and $200,000 to $300,000 compared to traditional methods that take 2.5 to 4.5 years and over $10 million [4] - InSilico's drug Rentosertib has shown promising results in clinical trials, with faster patient enrollment in China compared to the U.S., demonstrating the advantages of China's clinical resources [5] Group 2: Clinical Milestones - Rentosertib's IIa clinical trial results were published in a leading journal, marking a significant milestone in AI-driven drug discovery [6] - The development timeline for Rentosertib from candidate nomination to clinical trial initiation was only 18 months, making it one of the fastest AI drugs in progress [7] - The successful IIa trial results for Rentosertib are seen as a turning point for AI in drug development, indicating that AI can not only expedite the process but also reduce risks [6][7] Group 3: Business Development and Financing - InSilico has completed 11 rounds of financing totaling over $530 million, with recent funding rounds providing sufficient capital for ongoing clinical development [9] - The company is actively creating cash flow through business development, having secured multiple licensing agreements that could yield over $2 billion in revenue [10] - InSilico's business development strategy involves a dedicated team that directly engages with clients to optimize drug pipeline selection based on market needs [11] Group 4: Strategic Collaborations - InSilico has entered a strategic collaboration in the ADC (Antibody-Drug Conjugate) space, partnering with companies that have expertise in ADC development to establish a technology platform [12][13] - The collaboration aims to leverage the strengths of each partner to accelerate ADC drug development, representing a new cooperative model in the Chinese biopharmaceutical industry [14] Group 5: Broader Exploration - Beyond pharmaceuticals, InSilico is exploring applications in aging research, sustainable chemistry, and agricultural innovation, indicating a strategic focus on diversifying its technological capabilities [15]

Group 1 - The core theme of the news is the rapid evolution of the AI industry in Pudong, showcasing advancements in humanoid robots, AI drugs, and vertical models that empower various industries [1][2]. - The 2025 World Artificial Intelligence Conference highlighted Pudong's AI industry development, with companies like Zhiyuan Robotics achieving significant milestones, including the mass production of humanoid robots [1][2]. - Zhiyuan Robotics launched its versatile exploration robot Lingxi X2 and introduced the "Zhiyuan Qiyuan" general embodiment model at the conference, marking a significant step in humanoid robotics [1]. Group 2 - Pudong is recognized as a fertile ground for innovation and entrepreneurship in the field of embodied intelligence, with companies like Zhiyuan Robotics and Yingsi Intelligence making notable progress [2]. - Yingsi Intelligence reported a revenue of 350 million RMB in 2024, reflecting a year-on-year growth of 108%, and has ten clinical pipelines, including the AI drug Rentosertib, which is the fastest progressing AI drug globally [2]. - The Pudong Moli Community has been instrumental in fostering innovation by focusing on embodied intelligence, scientific intelligence, and application intelligence, creating a unique ecosystem for entrepreneurs [3].

Core Insights - The core advantage of AI in pharmaceuticals is speed, significantly accelerating the discovery-validation-optimization cycle [3] - AI pharmaceutical collaborations and investments have surged, indicating a milestone in innovative drug development [3][4] - Despite advancements, AI pharmaceuticals face commercialization challenges that require time to resolve [3] Group 1: Industry Collaborations and Investments - Recent large-scale collaborations in the AI pharmaceutical sector include an $8.12 billion deal between Novo Nordisk and Deep Apple Therapeutics, a $6.5 billion agreement between Eli Lilly and Juvena Therapeutics, and a partnership worth up to $5.45 billion between Formation Bio and Sanofi [4] - Domestic collaborations are also accelerating, exemplified by HanYue Pharmaceutical's agreement with Carbon Cloud Peptide to develop innovative peptide drugs using AI technology [5] - The influx of nearly $10 billion into the AI pharmaceutical industry within a month highlights the sector's growing importance [4] Group 2: Market Growth and Development - The AI pharmaceutical market in China is rapidly expanding, with a projected growth from 0.07 billion yuan in 2019 to 0.73 billion yuan in 2024, reflecting a compound annual growth rate (CAGR) of 47.8% [9] - The market is expected to grow from 1.21 billion yuan in 2025 to 5.86 billion yuan by 2028, with a CAGR of 68.3% [9] - Companies like Zhenhua Tianqing and Haoyuan Pharmaceutical are leveraging AI to enhance drug development processes, demonstrating significant advancements in the industry [9][10] Group 3: Technological Advancements - AI technology is increasingly integrated into the entire drug manufacturing chain, improving efficiency and reducing costs [10] - For instance, Shiyao Group's AI platform has reduced early drug discovery time by over 30% and cut development costs by nearly half [10] - AI's role in clinical trials is also evolving, with companies like Kanglong Chemical utilizing AI to optimize patient recruitment and data monitoring, significantly enhancing trial efficiency [10] Group 4: Commercialization Challenges - Despite rapid growth, AI pharmaceutical companies like InSilico Medicine and JingTai Technology continue to face profitability challenges, with significant net losses reported [11] - AI drugs have not yet reached the market, and their commercial value remains uncertain, as many are still in clinical trial phases [11] - The industry is grappling with data quality issues, which hinder AI model training and effectiveness, particularly in rare diseases and new target research [12]

Group 1 - The core viewpoint is that drug molecular design is transitioning from "probabilistic collisions" to "atomic-level precision engineering," ushering in a faster, more accurate, and smarter era of molecular design [1][2] - AI-driven drug discovery has made significant advancements, with Chai Discovery's AI model Chai-2 achieving a historic success rate of 16% in "de novo" antibody design, which is over 100 times more effective than previous methods [1][2] - The success of Chai-2 is attributed to its multimodal generative architecture, which integrates full-atom structure prediction and generative models, addressing the low success rates of traditional methods that often rely on extensive experimental screening [1] Group 2 - Despite the advancements, AI-discovered drugs entering late-stage clinical trials remain limited, primarily due to the early development stage of AI in drug discovery and the presence of misleading claims about AI capabilities [2] - A recent study published in Nature Medicine highlights a significant milestone, showing that an AI-discovered drug for idiopathic pulmonary fibrosis demonstrated safety and efficacy in a randomized phase II clinical trial [2][3] - The AI-powered drug Rentosertib, developed by Insilico Medicine, showed good safety and tolerability, with dose-dependent efficacy observed in patients, marking a successful demonstration of the company's generative AI platform [3]