In order to thoroughly implement the Opinions of the State Council on Further Implementing the "Artificial Intelligence +" Initiative and the Opinions of the General Office of the State Council on Comprehensively Deepening the Regulatory Reform of Drugs and Medical Devices to Promote the High-Quality Development of the Pharmaceutical Industry, and to seize major strategic opportunities presented by the development of AI, the National Medical Products Administration (NMPA) has issued the Implementation Opinions of NMPA on "Artificial Intelligence + Drug Regulation" (hereinafter referred to as the Opinions). An interpretation of the relevant content is hereby provided as follows.

I. Background of the Drafting of the Opinions

The NMPA attaches great importance to information technology and has clearly put forward the vision of "leading drug regulation modernization through information technology," with the development of smart regulation being promoted as a key focus in priority for the quality and efficiency of drug regulation. During the 14th Five-Year Plan period, drug regulatory departments at all levels, based on the overall approach of "unified planning, integrated development, and networked regulation," have used the "14th Five-Year Plan for Drug Regulatory Network and Informatization Planning" as a blueprint to comprehensively upgrade information infrastructure, data governance, government services, regulatory applications, and security protection systems. This has resulted in the basic establishment of the nationwide integrated drug smart regulation system.

In recent years, the rapid development and iterative advancement of new-generation information technologies, such as AI, have provided new tools and injected new momentum into smart regulation. To implement the series of plans and deployments from the Party Central Committee and the State Council regarding the "AI +" initiative and the comprehensive deepening of drug regulation reform, the NMPA has carefully summarized the achievements and experiences of drug smart regulation during the 14th Five-Year Plan period. It has deeply analyzed the current situation and problems, focusing on the challenges and weaknesses of drug regulation reform. In line with the overall deployment of the State Council regarding the "AI +" initiative, the NMPA has researched and drafted the Opinions, outlining the overall blueprint for the coordinated advancement of "AI + Drug Regulation" development over the next five to ten years.

II. General Considerations and Main Content of the Opinions

The Opinions focus on the central tasks of comprehensively deepening drug regulation reform and implementing the "AI +" initiative. It thoroughly analyzes the current groundwork for this work and proposes an overall design for the initiative of "AI + Drug Regulation," advancing the innovative application of AI across the entire drug lifecycle regulation. The Opinions consist of four parts: overall requirements, key regulatory scenarios empowered by digital intelligence, foundational support for "AI + Drug Regulation", and organizational implementation.

Part I sets forth the overall requirements, clarifying the guiding principles and main objectives. It sets the goal that by 2030, a preliminary system for the integration and innovation of drug regulation and AI will be established. The operational management mechanism of "AI + Drug Regulation" will be basically formed, the computing power support infrastructure will become more integrated and efficient, and high-quality datasets, vertical large models, and intelligent agents that meet regulatory intelligence needs will be developed. AI will be effectively applied in various scenarios such as review and approval, supervision and inspection, testing and surveillance, and government services. The efficiency of human-machine collaboration will be significantly enhanced, and digital intelligence-driven regulatory capabilities throughout the entire lifecycle will reach new heights. By 2035, a new pattern of intelligent and agile drug safety governance driven by digital intelligence, independent and controllable systems, and ecological collaboration will be basically formed. Part II focuses on key regulatory scenarios empowered by digital intelligence and proposes seven key directions centered on AI empowerment of drug regulation. Part III, based on the new trends in AI technology development and relevant document requirements, proposes five key tasks to strengthen the foundational support for "AI + Drug Regulation." Part IV emphasizes the need for strengthened coordination during the implementation of the Opinions. It highlights the importance of leading by example, reinforcing scientific and technological support, and intensifying training efforts to ensure successful execution.

III. How to Accelerate the Effective Application of AI in Drug Regulation

The Opinions focus on the key tasks of drug regulation reform, and based on the nationwide integrated drug smart regulation system, set drug regulation modernization as the goal. It proposes seven key directions for the next phase of digital intelligence-driven regulation.

(I) Establishing a human-machine collaborative intelligent review and approval system. With the goal of enhancing review and approval efficiency through digital intelligence, efforts will focus on the collaborative co-development of large models and intelligent agents for the review and approval of "drugs, medical devices, and cosmetics." Relevant units of the NMPA and provincial-level drug regulatory departments will accelerate exploring the application of AI in various stages of the review and approval process. Based on this, a human-machine collaborative mechanism will be established and refined.

(II) Enhancing full-chain intelligent regulatory capabilities. Considering the current state of industry digitalization in the R&D, manufacturing, and circulation and use stages, and building upon prior advancements in digitalized production regulation and traceability systems, the focus is on the innovation and upgrading of regulatory methods across the entire chain, and a series of new digital intelligence-driven regulatory measures are proposed.

(III) Promoting the digital intelligence upgrade of the risk regulatory system. By advancing the digital intelligence upgrade of systems for inspection and testing, surveillance and evaluation, complaints and reports, online sales, and public opinion monitoring, enhancing the mining and analysis of whole lifecycle regulatory big data, and developing a series of risk regulation models and intelligent agents, risk profiles will be created to support risk consultations and to improve the overall risk regulatory capabilities.

(IV) Advancing the intelligent and standardized approach to inspections and law enforcement. In line with national requirements for standardizing inspections and law enforcement, the Opinions specify a series of measures to accelerate the digital and intelligent upgrade of inspection systems. Key tasks will include speeding up the development of inspection plans based on big data, coordinating the development of provincial-level inspection and law enforcement systems, utilizing digital intelligence technologies to enhance on-site inspection efficiency, and strengthening mobile law enforcement. These efforts aim to improve the level of intelligent and standardized inspection and law enforcement.

(V) Enhancing collaborative regulatory effectiveness. Relying on the Smart Regulatory Information Platform, an efficient, intelligent, and multi-party collaborative national business system will be built. Digital intelligence technologies will be used to strengthen cross-region, cross-level, and cross-departmental collaborative regulatory capabilities. Focus will be placed on critical scenarios to address prominent issues such as inadequate collaboration mechanisms, inefficient business flows, lack of information sharing, and difficulties in closing the loop on issue resolution.

(VI) Enhancing the intelligence level of government services. In accordance with the State Council’s ongoing requirements for "Efficiently Handling One Matter," key tasks for the development of "AI + Government Services" will be outlined. Efforts will focus on advancing the intelligence, precision, and convenience of government services.

(VII) Promoting collaborative digital intelligence development between regulation and industry. Focusing on the requirements of intelligent regulation, efforts will be made to encourage and guide the industry to accelerate its digital intelligence transformation and upgrading. We will advance the digital intelligence transformation of high-risk products, such as blood products and traditional Chinese medicine injections, develop relevant regulatory requirements, and gradually expand this approach to other product categories. The goal is to guide the industry in improving quality control capabilities across the entire process in accordance with established standards.

IV. How to Support the Efficient and Safe Operation of "AI + Drug Regulation"

(I) Promoting the development of high-quality drug regulation datasets. Adhering to the principle of "scenario-driven, urgent needs prioritized" and focusing on the core business scenarios of the entire drug lifecycle regulation and the practical needs of AI applications, proceed with the phased, stepwise development of high-quality drug regulation datasets.

(II) Strengthening the AI application support system. Comprehensively advance the training, deployment, and application of large models in the field of drug regulation. Build a large model application and algorithm management platform, unify the foundational model application system and technical framework, promote the open sharing of common technological components, strengthen support for AI applications, and enhance the management capabilities of foundational models and algorithms.

(III) Strengthening computing power infrastructure development. The NMPA will coordinate the planning of a multi-level intelligent computing power resource coordination system, with national and provincial-level regulatory departments advancing the provision of smart computing resources as needed. Create a standardized and scalable intelligent computing power foundation to meet the smart application needs of various network domains, such as the Internet, government extranet, and government intranet.

(IV) Fortifying the security protection system. Enhance the application of AI in the security protection system, promoting the development of an intelligent and collaborative protection system to improve cybersecurity and data security protection capabilities. At the same time, strengthen AI risk monitoring and evaluation, establish algorithm transparency requirements and model validation standards, and enhance security capabilities for models, algorithms, data resources, infrastructure, and application systems.

(V) Improving the development and operation management mechanism. Clearly define the supportive role of AI in the drug regulation field and the basic principles for coordinated development. Establish a dedicated mechanism to oversee the governance of AI applications, and develop management systems related to "AI + Drug Regulation." Strengthen the filing and management of AI models and algorithms.

V. Key Requirements for Promoting the Implementation of the Opinions

(I) Strengthening coordination and planning. Drug regulatory authorities at all levels shall deeply understand the new trends in AI development and regard it as a key lever to support the comprehensive deepening of drug regulation reform and as a strong support for enhancing drug regulation capabilities. These authorities shall coordinate and align relevant plans, increase investments, and promote the application of AI in frontline regulation. The approach shall be "promoting development through application and integrating development with application," ensuring that AI plays a practical role in regulation.

(II) Strengthening demonstration and leadership. Focus on the key challenges and bottlenecks in regulatory business, deepen the innovative application of smart regulation, and effectively empower business innovation.

(III) Strengthening scientific and technological support. Strengthen regulatory science research to provide technological support for "AI + Drug Regulation," and promote the implementation, translation, and application of relevant major scientific and technological projects.

(IV) Enhance training efforts. Improve the digital thinking, digital skills, and digital literacy of the regulatory workforce.

　　(NMPA April 2, 2026)