【钛媒体综合】据央行官网，2025年9月11日，中国人民银行与印度尼西亚央行共同启动双边交易本币 结算（LCT）框架和二维码互联互通合作项目。本次活动设有北京主会场和雅加达分会场，中国人民银 行行长潘功胜、印尼央行行长佩里·瓦吉约、印尼驻中国大使周浩黎在北京主会场，中国驻印尼大使王 鲁彤在雅加达分会场出席活动并致辞。中国外交部、商务部、印尼驻华使领馆人员，两国商业银行、支 付机构、实业企业等机构代表应邀参加。 两国央行行长共同宣布LCT框架正式启用。2025年5月，在李强总理和印尼普拉博沃总统见证下，两国 央行签署合作备忘录，将2020年建立的促进经常账户交易和直接投资本币结算框架升级为LCT框架，将 本币结算范围拓展至国际收支全部项目，以进一步便利本币在双边贸易和投资中的使用。 中国—印尼跨境二维码互联互通项目正式启动双向试点运行。该项目预计于2025年内正式全面投产，采 用本币结算方式，是双方支付合作的重要进展。 潘功胜指出，建立双边交易本币结算框架和跨境支付二维码互联互通是中印尼双边金融合作的重要成 果。近年来，中印尼金融合作持续深化发展，得益于两国不断加深的政治互信，也顺应了两国日益紧密 经贸关系发展 ...

Investment Rating - The report assigns a "Buy" rating for the stock, indicating that it is expected to outperform the benchmark by more than 15% within the next six months [10]. Core Insights - The company has achieved significant revenue growth, with a 403.83% year-on-year increase in revenue to 517 million yuan in the first half of 2025, and a net profit of 83 million yuan, marking a turnaround from a loss of 1.237 billion yuan in the same period of 2024 [2]. - The drug discovery solutions segment saw a remarkable 615% increase in revenue, reaching 435 million yuan, driven by strategic collaborations and advancements in AI technology [2]. - The intelligent automation solutions segment also performed well, with a 95.9% increase in revenue to 82 million yuan, showcasing the effectiveness of AI and robotics in chemical processes [2]. Financial Performance Summary - Revenue projections for the company are as follows: 2024A: 266 million yuan, 2025E: 693 million yuan, 2026E: 984 million yuan, and 2027E: 1.337 billion yuan, reflecting a growth rate of 53%, 160%, 42%, and 36% respectively [4]. - The net profit forecast shows a recovery from a loss of 1.517 billion yuan in 2024A to a profit of 39 million yuan in 2025E, with further increases to 86 million yuan in 2026E and 184 million yuan in 2027E [4]. - The earnings per share (EPS) is projected to improve from -0.79 yuan in 2024A to 0.01 yuan in 2025E, 0.02 yuan in 2026E, and 0.05 yuan in 2027E [4]. Business Segment Performance - The drug discovery solutions segment is highlighted for its strong performance, with significant partnerships and awards enhancing its market position [2]. - The intelligent robotics solutions segment is noted for its innovative applications in chemical processes, achieving high success rates and operational efficiency [2]. - The company is leveraging AI and robotics to create a multi-dimensional innovation ecosystem, enhancing its capabilities in drug development and chemical research [2].

Core Viewpoint - JingTai Technology (2228.HK) has achieved significant recognition in the international capital market, evidenced by its impressive financial performance and strategic partnerships in the AI drug discovery sector [6][11]. Financial Performance - For the first half of 2025, JingTai Technology reported revenue of 517 million yuan, a year-on-year increase of 403.8%. The drug discovery solutions segment saw a revenue increase of 615.2% to 435 million yuan, while the intelligent robotics solutions segment grew by 95.9% to 82 million yuan [5]. - The company achieved its first half-year profit with an adjusted net profit of 142 million yuan [5]. - As of June 30, 2025, JingTai Technology held a cash balance of 5.308 billion yuan, indicating strong liquidity [6]. Market Position - JingTai Technology's market capitalization exceeded 41.2 billion HKD, making it the highest-valued company in the AI drug discovery field in Asia [6]. - The company ranked third in the Hong Kong Stock Connect trading activity, following Tencent and Alibaba [7]. Strategic Partnerships - A significant growth driver for JingTai Technology was its collaboration with biopharmaceutical legend Professor Gregory Verdine, which included a major agreement worth 51 million USD for the first phase and potential further payments totaling 589 million USD based on regulatory and commercial milestones [8][9]. - This partnership is expected to leverage JingTai's AI and robotics drug discovery platform to develop small molecules and antibody candidates for various diseases [9][10]. Technological Advancements - JingTai Technology's AI antibody drug structure modeling platform, XtalFold, was recognized as one of the top ten innovative AI technologies at the World Artificial Intelligence Conference [13]. - The company has developed a unique high-throughput experimental system that integrates advanced visual perception, AI, and robotics, addressing significant challenges in chemical research [15][16]. R&D Investment - In the first half of the year, JingTai Technology increased its R&D investment by 5.3% to 222 million yuan, reflecting a commitment to innovation despite a much higher revenue growth rate [16]. Long-term Value Proposition - JingTai Technology is positioned as a platform company with core competencies in AI and data, capable of empowering various sectors including biomedicine, new materials, and renewable energy, thus representing significant long-term value [18].

Investment Rating - The report assigns a "Buy" rating for the company, marking its first coverage [4][6]. Core Insights - The company is a leading AI for Science innovative R&D platform, leveraging a combination of AI, quantum technology, and robotics to create competitive advantages, primarily in pharmaceutical R&D, with plans to expand into materials and other fields, suggesting that revenue growth and profit release may exceed expectations [1][2]. Summary by Sections 1. Company Overview - The company integrates quantum physics, AI algorithms, and robotic automation to enhance R&D efficiency in pharmaceuticals and materials science [15]. - Founded by three MIT postdoctoral researchers, the company has established partnerships with major pharmaceutical firms, including 17 of the top 20 global drug companies [2][19]. 2. Financial Performance - The company is expected to achieve revenues of 602 million, 918 million, and 1.316 billion CNY in 2025, 2026, and 2027, respectively, with year-on-year growth rates of 126.1%, 52.4%, and 43.3% [4][10]. - The company anticipates turning a profit in the first half of 2025, with expected revenues of at least 500 million CNY, a 387% increase from the first half of 2024 [40]. 3. Market Trends - The global CRO market is projected to grow from 12.3 billion USD in 2023 to 32.5 billion USD by 2030, with a CAGR of 14.9% [3][55]. - The report highlights a significant trend towards outsourcing in drug development, with the global market for outsourced drug discovery services expected to grow from 7.6 billion USD in 2018 to 32.5 billion USD by 2030 [55][56]. 4. Business Model and Growth Drivers - The company employs a revenue-sharing model that enhances income flexibility, with significant potential revenue from collaborations, including a recent agreement with DoveTree that could yield up to 58.9 billion USD in milestone payments [2][39]. - The company has developed a unique high-throughput experimental platform that operates 24/7, generating high-quality data to improve AI models, thus enhancing the drug discovery process [16][44]. 5. Product and Service Offerings - The company offers a diverse range of products, including intelligent synthesis workstations and AI software applications, which collectively create a robust barrier to entry in the market [48]. - The company has established a comprehensive R&D platform that covers the entire drug development process, integrating multiple core products and technologies [45][46]. 6. Strategic Partnerships - The company has formed strategic partnerships with leading pharmaceutical companies, including Pfizer and Merck, to enhance its market presence and drive innovation [48][49]. - The report notes that the company has successfully developed key projects, including an innovative targeted drug that integrates AI and organoid disease models, receiving FDA approval [50].

Core Viewpoint - The article discusses the significant advancements in AI-driven drug discovery, particularly through the Chai-2 model, which is expected to revolutionize the pharmaceutical industry by increasing efficiency and unlocking new drug targets. Group 1: AI Drug Discovery Breakthroughs - Demis Hassabis predicts that AI-designed drugs may enter clinical trials by the end of 2025 [1] - Chai-2 model achieves a 16% success rate in antibody design, marking a shift from experimental discovery to clinical trial readiness [2][4] - The model allows for rapid generation of molecules based on desired functions, akin to a "Midjourney moment" in molecular design [2] Group 2: Efficiency and Cost Reduction - Chai-2's design process significantly reduces the number of molecules needed for testing, achieving a 16% success rate with only about 20 AI-designed molecules [4][6] - Traditional drug discovery methods require screening millions to billions of compounds, making Chai-2's approach vastly more efficient [5][6] - The technology is expected to make drug development faster, cheaper, and better, addressing previously unreachable drug targets [7][8] Group 3: Engineering Approach to Drug Discovery - The transition from "craftsmanship" to "engineering" in drug discovery is emphasized, with AI facilitating a more systematic approach [9][10] - AI's ability to challenge previously deemed "undruggable" targets represents a significant opportunity for innovation [9] - The integration of AI with traditional laboratory methods will redefine the role of wet labs in drug discovery [10][11] Group 4: Future Prospects and Market Impact - The article highlights the potential for a new class of drugs and targets to emerge in the next five to ten years, driven by advancements in AI [8][7] - The current biotech industry is experiencing a downturn, but breakthroughs like Chai-2 signal a potential turnaround [7] - The collaboration between AI and biopharmaceutical companies is crucial for maximizing the technology's impact [9][10] Group 5: Technical Insights and Model Functionality - Chai-2's ability to predict and generate molecular structures is compared to a "microscope" for atomic-level insights [20][21] - The model's success in diverse biological contexts demonstrates its robustness and generalizability [22][18] - The engineering rigor in developing Chai-2 ensures a reliable and scalable platform for drug discovery [28][29] Group 6: Industry Transformation and Collaboration - The shift towards a more collaborative approach in drug discovery is highlighted, with Chai-2 being made accessible to academic and industry partners [9][10] - The importance of writing effective prompts for AI models is emphasized as a key skill for scientists [36][37] - The article concludes with a call for interdisciplinary collaboration to fully realize the potential of AI in drug discovery [39][40]

Core Viewpoint - Xaira Therapeutics, an AI drug discovery company, has raised $1 billion in seed funding and aims to revolutionize drug discovery through advanced AI technologies [2] Group 1: Company Overview - Xaira Therapeutics was founded in April 2024 and has a distinguished leadership team, including Nobel laureates and former executives from major pharmaceutical companies [2] - The company has released the largest publicly available Perturb-seq dataset, named X-Atlas/Orion, which supports virtual cell research and enhances drug discovery predictions [3][4] Group 2: Dataset Details - The X-Atlas/Orion dataset includes 8 million cells and covers all protein-coding genes in humans, with over 16,000 unique molecular identifiers from single-cell deep sequencing [4][8] - Perturb-seq technology used in this dataset allows for the simultaneous reading of CRISPR sgRNA genetic perturbations and transcriptomes, revealing dose-dependent genetic effects [4][9] Group 3: Technological Innovations - The FiCS Perturb-seq platform developed by Xaira Therapeutics enables scalable production of perturbation sequencing data, overcoming previous limitations in data generation [8][11] - The platform demonstrates high sensitivity and minimal batch effects, accurately capturing transcriptional changes due to genetic perturbations [8] Group 4: Research Implications - The release of X-Atlas/Orion addresses the challenges of data generation scalability and standardization, facilitating the development of next-generation foundational models in life sciences [11] - The dataset will be shared under a non-commercial license to promote open collaboration in the biotechnology sector, with potential commercial partnerships available [12] Group 5: Future Directions - Xaira Therapeutics plans to expand data generation to include induced pluripotent stem cells and in vivo animal models, aiming for broader applications in AI-driven virtual cell development [20]

Core Viewpoint - Insilico Medicine, an AI drug discovery company, has submitted a new listing application to the Hong Kong Stock Exchange, with joint sponsors including Morgan Stanley, CICC, and GF Securities (Hong Kong) [1] Group 1 - Insilico Medicine is focused on AI-driven drug development [1] - The company has previously attempted to list and is now making another effort [1] - The involvement of major financial institutions as sponsors indicates strong backing for the listing [1]

Core Insights - Xellar Biosystems, a technology platform focused on "AI + organ-on-a-chip" integration, has completed a new round of strategic financing amounting to tens of millions of yuan, led by XtalPi, a global leader in AI drug and new materials research [1] - The funding will accelerate the development of its "3D-Wet-AI" closed-loop system, which integrates organ-on-a-chip technology, wet lab capabilities, and AI algorithms, while also expanding international collaborations and commercial applications [1][2] - Xellar Biosystems aims to redefine drug development, safety evaluation, and precision medicine processes through its self-developed high-throughput organ-on-a-chip and AI model platform [1][4] Investment and Collaboration - The strategic investment from XtalPi will facilitate deep collaboration on high-quality biological data generation, complex disease modeling, AI-assisted toxicology predictions, and drug efficacy extrapolation [2] - The partnership aims to integrate organ-on-a-chip technology with automation, creating a seamless connection between in vitro complex models and AI molecular generation and screening algorithms [2][5] - This collaboration is expected to enhance drug development efficiency and success rates by providing clinically relevant research data [2][3] Regulatory Landscape - Global regulatory bodies are accelerating the transition away from animal testing, with the FDA Modernization Act 2.0 allowing non-animal methods for new drug IND submissions [3] - The FDA is launching multiple multi-center validation projects from 2023 to 2025 to incorporate organ-on-a-chip and human cell models into mainstream toxicology and efficacy evaluation standards [3] - Xellar Biosystems is actively participating in standard validation with regulatory agencies, providing safety and efficacy analysis services to pharmaceutical companies and research institutions [3] Technological Advancements - Xellar's EPIC platform combines microfluidic chip technology, disease modeling, high-throughput experimental systems, and generative AI algorithms, enabling rapid construction of complex microenvironments and multi-dimensional imaging [4] - The platform has been utilized in early drug toxicity prediction, functional food and skincare product screening, and personalized treatment response simulation [4] - The integration of AI and organ-on-a-chip technology is seen as a transformative shift in life sciences, enhancing the entire research and development logic [4][5] Market Position and Future Outlook - Xellar Biosystems is positioned as a key player in the AI + organ-on-a-chip sector, with strong technical execution and industry sensitivity demonstrated over the past two years [5][6] - The collaboration with XtalPi is viewed as a significant step in reinforcing Xellar's leading position in the AI + organ-on-a-chip integration path [5] - The focus on high-quality physiological data generation and deep coupling with AI models is expected to drive innovation in biomedicine, enhancing decision-making across regulatory, industrial, and consumer scenarios [6]