To analyze the key changes in the 2026 edition of the good clinical practice (GCP) and to explore specific implementation measures.

By interpreting the revised provisions of the new GCP edition and comparing them with the 2020 edition, together with reference to ICH E6 (R3), this study examines the implementation measures necessitated by these key changes.

The provisions regarding the management of trial protocols, investigator’s brochures, and essential documents, as well as most terminology, have been removed; implementation now follows ICH E6 (R3) guidelines, while retaining fundamental requirements and China-specific regulations. The General Provisions incorporate the three core principles of the ICH E6(R3), clarify the ultimate responsibilities of the principal investigator and the sponsor, introduce a separate chapter on data governance, and streamline the safety reporting process.

To implement the new version of GCP and to promote the development of clinical drug trials in China, sponsors should align with international standards to strengthen their sense of responsibility and implement quality management and data governance; principal investigators and clinical trial institutions should enhance their awareness of ultimate responsibility and clarify the boundaries of authorization; and service providers should perform their duties in compliance with contractual obligations.

To analyze the new requirements imposed on principal investigators and clinical trial institutions by the revised Good Clinical Practice (GCP) guidelines, and to explore the challenges currently facing the industry along with corresponding response strategies.

Through an in-depth interpretation of the revised GCP provisions and a comparative analysis with the 2020 version, integrated with the core principles of ICH E6(R3), this study examined compliance and the current status from the perspectives of legal liability delineation, participant protection, data integrity, and quality management system development.

The legal status of the principal investigator as the “ultimate responsible party at the clinical trial site” was established, and it was proposed that clinical trial institutions should build and ensure the effective operation of a full process quality management system. In addition, an intelligent management pathway was identified, embedding digital tools into management processes to address practical challenges including technical barriers, cost investments, and cognitive biases.

The implementation of the revised GCP signifies a shift in China’s clinical trial management from the former “compliance oriented” approach toward “quality-by-design” and “risk-based” approaches. Principal investigators and clinical trial institutions should leverage digital transformation and the co-evolution of management paradigms to create an intelligent quality ecosystem, achieving a substantial leap in clinical trial performance while maintaining full regulatory compliance.

To analyze the new requirements and challenges in the data governance chapter of China’s 2026 edition of Good Clinical Practice (GCP), and to propose corresponding strategies.

This paper systematically summarizes the core provisions in the new GCP, including the full data lifecycle, blinding management, and computerized system standards, and explores of practical implementation challenges in the context of China’s specific circumstances.

The new GCP faces challenges in China, including inconsistencies between regulatory frameworks and technical standards, great difficulties in the execution of blinding management, imperfect development and validation of computerized systems, and insufficient awareness and capabilities in data governance.

China’s regulatory requirements for drug clinical trials should further align with international concepts; management mindsets should be adjusted; standard operating procedures should be updated in a timely manner; and coordinated efforts should be made to improve the regulatory framework, optimize blinding processes, promote standardization of computerized systems, and strengthen data governance training and cultural development, so as to establish a scientific and efficient clinical trial data governance system.

To explore the current application status, implementation considerations, and practical measures for a new model of delivering investigational drugs directly to trial participants (direct-to-subject, DTS) in the context of the revised Good Clinical Practice (GCP) and ICH E6 (R3), with the aim of providing a reference for optimizing its management quality.

Through a literature review, this study compared regulatory policy differences, current implementation status, and common models for the direct-to-subject model between domestic and international settings, and analyze the key considerations for its implementation.

The direct-to-subject model has been adopted both domestically and internationally, but there is a lack of unified implementation guidelines. Its use may be considered when appropriate. Effective implementation can be ensured by strengthening the following aspects: clarification of responsibilities, ethical review, informed consent, risk assessment, qualification verification, training, information system development, risk management, privacy protection, and investigator oversight.

The model aligns with the “patient-centered” philosophy but is still in its exploratory phase. When planning to adopt this approach, its feasibility should be fully demonstrated in the protocol, with enhanced emphasis on ethical review, training, and risk control, while clearly defining the responsibilities of all parties to safeguard participants’ rights and ensure data reliability.

To construct a multidimensional value assessment framework for novel drugs for lung cancer, thereby supporting evidence-informed decision-making for medical insurance reimbursement.

First, literature on the value assessment of novel drugs for lung cancer was searched and reviewed. Based on a literature review and a focus group discussion, the framework was preliminarily constructed. Then, the Delphi method was used to determine the criteria, sub-criteria, weights, and value assessment methods. Finally, the feasibility of framework was verified through the value assessment of three novel drugs for lung cancer.

The constructed multidimensional value assessment framework for novel drugs for lung cancer consists of five core criteria, two contextualized criteria, and 20 sub-criteria. The core criteria include comparative effectiveness, comparative safety, affordability, economic value, and evidence quality, with comparative effectiveness having the highest weight. Among the sub-criteria of the core criteria, overall survival and progression-free survival have the highest weights. The contextual criteria are innovation and equity.

The structured multidimensional value assessment framework provides a decision-support tool for medical insurance policymakers and helps to improve the scientific rigor and transparency of decision-making.