关键词: 医学本体, 监管审评, 智能化监管, 数据模型, 药品研发

Abstract:

 With the increasing complexity of drug development and rising regulatory demands， regulatory agencies are facing more challenges in ensuring the scientific and efficient evaluations throughout drug whole life cycle. Traditional methods of regulatory data management struggle to cope with the growing volume and complexity of data. Medical ontology technology， which standardizes and integrates multi-source heterogeneous data， has gradually been applied in drug review processes to enhance decision-making precision and scientific accuracy. This study proposes an intelligent regulatory data model based on medical ontology， integrating ontology engineering， machine learning， big data and artificial intelligence， automated data indexing and retrieval， and data security technologies， aiming to optimize data integration and analysis in drug evaluations. The model design includes semantic data modeling and data classification and annotation， while multi-source data integration and processing cover data fusion and automated indexing. The application scenarios of this model in global drug supervision include drug safety monitoring， approval pathway optimization， health data integration， and long-term safety assessments. By exploring the application of medical ontology technology in drug development and evaluation， this research provides theoretical and practical support for improving the efficiency and scientific validity of drug evaluation and advancing digitalized regulation.

Key words:  , Medical ontology； , Regulatory review； , Intelligent supervision； , Data model； , Drug development