9月11日，由世界自然保护联盟教育与传播委员会、中国医药保健品进出口商会、北京服务贸易协会联合主办的"2025中国国际医疗健康产业发展与投资论 坛"在京举行。论坛以"自然守护+AI智治：共筑健康新生态"为主题，旨在打造高规格国际化服务贸易合作平台。 中国医药健康产业国际化发展正不断迈向高质量发展的新阶段。中国医药保健品进出口商会副会长王茂春在论坛上表示，从对外投资看，中国已成为全球医 药对外投资的主要输出国之一。中国医药健康产业对外投资正逐步升级为技术、资本、标准等全方位合作，覆盖了研发、生产、物流、并购、基础建设等领 域，助力合作伙伴所在地的医药产业发展。 从医药创新的角度来看，2024年我国医药创新对外授权交易总额突破了522.6亿美元，成为全球单笔交易额最高和首付款最大的医药资产的授权国，获得了 全球医药界的广泛认可。中国的药械创新已经从过去的跟跑迈向并跑阶段，并在ADC、双抗、细胞治疗等细分领域实现了局部的领跑。 随着新一代科技革命的深入推进，人工智能、大数据、数字化和智能化技术与医药工业正在加速融合，为中国医药产业高质量发展提供了新的动力。 今年4月，工业和信息化部、商务部、国家卫生健康委、国家医保 ...

Core Insights - The pharmaceutical distribution industry in China is heavily concentrated in regions with convenient transportation, with the Yangtze River Economic Belt accounting for nearly half of the total sales in 2023, at 49.8% of the national sales [1] - The East China region remains a major pharmaceutical distribution market, contributing 36.2% to the national sales, although this represents a decrease of 0.2 percentage points year-on-year [3] - In the distribution of Western medicine, Guangdong province holds the highest share at 10%, followed by other provinces primarily in East China [7] - For Traditional Chinese Medicine distribution, Beijing leads with a 10.7% share, with other significant contributions from provinces like Zhejiang and Henan [8] - In the medical device distribution sector, Guangdong again ranks first with a 16.8% share, followed by provinces such as Henan and Beijing [10] Regional Distribution Analysis - The sales distribution across six major regions in China for 2023 is as follows: East China 36.2% (down 0.2 percentage points), Central South 27.0% (down 0.2 percentage points), North China 15.2% (up 0.3 percentage points), and Southwest 13.4% (unchanged) [3] - The Yangtze River Economic Belt's dominance in sales highlights the importance of transportation infrastructure in the pharmaceutical distribution sector [1] Market Opportunities - The report indicates potential investment opportunities in the pharmaceutical distribution sector, particularly in regions with high sales concentrations and growth potential [12]

Core Viewpoint - Hong Kong is positioned to continue as an international R&D hub, talent gateway, and capital connector within the Greater Bay Area, leveraging its unique role and strategies to support the development of enterprises in the region [1][3]. Group 1: Hong Kong's Role in the Greater Bay Area - Hong Kong is utilizing the Lok Ma Chau Loop as a core platform to break down cross-border barriers and attract global innovation and technology resources through policy innovation [2]. - The collaboration between Hong Kong and other cities in the Greater Bay Area aims to create a complete innovation ecosystem that integrates "Hong Kong R&D and pilot production + Greater Bay Area manufacturing and application + global market" [2]. - Hong Kong's strengths include five globally ranked universities, 76 leading disciplines, 15 national key laboratories, and 30 global research laboratories, which enhance its R&D capabilities [2]. Group 2: Policy Innovations and International Integration - Policies such as the "Cross-Border Data Standard Contract" and "Hong Kong-Macao Drug and Medical Device Pass" are designed to create a business environment that aligns with international standards for Greater Bay Area enterprises [2]. - The "Hong Kong-Macao Drug and Medical Device Pass" allows designated hospitals in the Greater Bay Area to use certain drugs and medical devices already approved in Hong Kong, facilitating faster clinical trials and registration processes for global pharmaceutical companies in mainland China [2]. Group 3: Focus Areas for Development - Hong Kong is focusing on R&D in artificial intelligence, robotics, life sciences, new energy, and new materials, supported by international R&D centers established by industry giants like CATL [2]. - The aim is to position the Greater Bay Area at the forefront of global technological advancements through enhanced collaboration among government, industry, academia, research, and investment [3].

Core Viewpoint - The implementation of the "Intelligent Transformation Implementation Plan for the Pharmaceutical Industry (2025-2030)" aims to enhance the digitalization and intelligence of the pharmaceutical industry in China, focusing on research, production, and distribution processes through specific tasks and goals [1][2]. Group 1: Digital Transformation Goals - The plan sets ambitious targets, including the establishment of over 100 intelligent pharmaceutical factories and the creation of more than 50 leading enterprises in intelligent transformation [1]. - It emphasizes the need to build over 10 innovative platforms for pharmaceutical big models and over 30 exemplary service providers for intelligent transformation [1]. Group 2: Addressing Industry Pain Points - The plan addresses key challenges in the pharmaceutical industry, such as the transition from scale expansion to quality improvement, and aims to support the creation of application verification and pilot testing platforms [2][3]. - It highlights the integration of AI technology in drug development, production monitoring, and quality control to enhance efficiency and product quality [3]. Group 3: Digital Transformation Pathways - The digital transformation process is outlined in three steps: building foundational digital infrastructure, leveraging big data for business model innovation, and utilizing AI and new technologies for significant business changes [4]. - Companies are encouraged to focus on real-time monitoring and precise control of key production parameters to optimize processes and reduce costs [5]. Group 4: Recommendations for Quality and Compliance - Companies should establish energy management systems and safety risk warning platforms to monitor and optimize energy consumption and enhance safety measures [6]. - The plan suggests that pharmaceutical companies should adopt intelligent systems tailored to their specific business needs to improve production efficiency and quality [5]. Group 5: Supporting Measures for Transformation - The transformation requires comprehensive measures, including collaboration among government, industry associations, and enterprises to establish a robust data-sharing framework [7][8]. - It is essential to develop a talent cultivation system that bridges the gap between AI and pharmaceutical fields to foster interdisciplinary expertise [8].