7部门联合发文！医药工业数字化转型按下“快进键”

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].