CHINA Law and Practice Contributed by: Gil Zhang, Diana Li, Muran Sun and Yongqi Tao, Fangda Partners
patients, as required by the Provisions on the Admin - istration of Instructions and Labels of Medical Devic - es. If used in decentralised clinical trials, the Technical Guidelines for the Implementation of Patient-Centered Clinical Trials (Trial) mandate proper de-identification and protection of patient data, and careful evaluation of digital health technologies (DHTs) based on disease characteristics and patient attributes (eg, education level, digital literacy). Real-time alerts for potential adverse events are also required. As discussed in 5.4 Human Oversight , broader tel- emedicine laws, like the Regulatory Rules for Inter - net-based Diagnosis and Treatment (Trial), explicitly restrict the use of AI in clinical decision-making and require AI use to be human-centred. These AI-related considerations are closely linked with broader man - agement requirements for medical records. 8.5 Drug Discovery and Development AI applications in drug discovery and development are subject to general pharmaceutical laws, such as the Drug Administration Law, the Measures for the Admin - istration of Drug Registration and the Measures for the Administration of Drug Standards. Although there are no AI-specific regulations in this area, validation must align with existing technical standards. Notably, the CDE issued the Guiding Principles for Model-Informed Drug Development, which require that the data used to establish models be derived from credible sources such as clinical trials, non-clinical studies or bibliographic references. When real-world data is used, developers must also comply with the Guiding Principles for Real-World Data regarding data quality, governance and applicability. 9. Future Trends and Regulatory Developments in Healthcare AI 9.1 Pending Legislation and Regulation Several general legislative and regulatory initiatives in China are underway that may shape the development and use of healthcare AI. • The Medical Device Management Law (public consultation draft): This draft proposes a uni -
fied national framework for medical device data management, promoting data interoperability and resource sharing. It is expected to accelerate healthcare AI development by improving access to standardised, high-quality data. It also allows the use of qualified foreign clinical trial data in registra - tion under certain circumstances. • The Artificial Intelligence Law (draft, included in the State Council’s 2024 legislative plan): While China’s proposed AI law draft was removed from the 2025 legislative agenda, the issues of liability and risk management in medical AI remain long-term con - cerns. It is advisable to keep in view and monitor the development of the comprehensive Artificial Intelligence Law. As laws and regulations govern - ing specific AI-related scenarios are expected to be introduced, the compliance burden will not be alleviated. • Model Artificial Intelligence Law 2.0 (expert draft): The draft, crafted by legal experts, has not offi - cially entered the legislative agenda but may potentially serve as a reference. The draft’s main points include strongly supporting open-source AI development through community building and clear liability rules. Additionally, it establishes new IP rules, addressing the use of training data and personal information, and defining protection in relation to AIGC. 9.2 Regulatory Sandboxes and Innovation Programmes At the national level, MIIT and the NMPA have launched a task-based programme targeting AI medical devic - es. Selected participants receive regulatory and tech - nical support to accelerate AI product development and deployment. In parallel, the National Data Admin - istration and other regulatory bodies have introduced policy to support enterprise data utilisation, with an emphasis on piloting regulatory sandboxes to create a flexible, innovation-friendly environment for emerging technologies and business models, like AI. Many local governments have also published their own policies. In Beijing, the AI Data Training Base incorporates a regulatory sandbox that facilitates compliant access to large-scale, high-quality data - sets for AI model training. It offers end-to-end services
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