To establish a scientific risk assessment system, identify and quantify key risk factors affecting the quality of clinical research on innovative anti-tumor drugs, and provide a decision-making basis for quality management and risk control.

This study adopted the triangular fuzzy analytic hierarchy process (TFAHP) to construct a risk assessment indicator system consisting of 8 primary indicators and 26 secondary indicators. Expert scoring was used to determine the weight of each indicator, followed by consistency testing and comprehensive ranking analysis.

Among the primary indicators, the highest weights were assigned to clinical research ward construction and management risk (0.139 4), information and data risk (0.130 2), and safety event management (0.125 3), highlighting research environment, data management, and subject safety as key focus areas. At the secondary level, data security risk and system security risk under the category of information and data risk (both 0.065 1) ranked highest, followed by litigation risk and policy risk under legal and policy risk (both 0.059 3), together constituting the high-risk tier. The top ten indicators in overall ranking also included safety data collection, quality control, biospecimen collection and processing, and adverse events/serious adverse events (AE/SAE) documentation, reflecting expert emphasis on data integrity, legal compliance, research quality assurance, and subject safety.

TFAHP effectively identifies and quantifies multidimensional risk factors in clinical research of innovative anti-tumor drugs. This study defines high, medium, and low-risk levels and proposes corresponding preventive strategies, providing theoretical and practical guidance for improving research quality and reducing clinical trial risks.