摘要
随着人工智能(AI)技术的迅速发展,毒理学正由依赖动物实验的传统模式,迈向以数据驱动和预测评估为核心的现代范式,如系统毒理学与预测毒理学。然而,当前毒理学教育体系尚未与学科的智能化转型同步,面临数据建模能力薄弱、实验教学与前沿实践脱节、智能化教学工具缺乏以及课程内容更新滞后等突出问题。为应对这些挑战,高校亟须构建以“数据-实践-智能”深度融合为核心的新型教学范式。文章从教育体系改革的视角,提出了人工智能赋能毒理学教学的可行路径,包括建立“毒理学-AI”双轨师资培养机制,整合高质量开源数据库与虚拟实验平台,发展可解释与可信的算法教学框架,以实现从机制理解到风险决策的能力闭环。展望未来,毒理学教育应进一步推动知识体系的动态更新、教学场景的元宇宙化融合与能力认证的智能化转型,从而系统性地培养具备多学科交叉能力的复合型人才,为精准化公共卫生治理提供坚实支撑。
With the rapid advancement of artificial intelligence(AI)technologies,toxicology is shifting from the traditional animal-based paradigm to data-driven and predictive framework,such as systems toxicology and predictive toxicology.However,the current teaching system of toxicology has not kept pace with this technological transformation and it is faced with problems of weak data modeling competence,disconnection between experimental teaching and frontier practice,lack of intelligent teaching tools,and outdated course content.To address these gaps,universities urgently need to build a new educational paradigm integrating“data-practice-intelligence”.This paper proposes feasible strategies for AI-empowered teaching reform:establishing a toxicology-AI dual-track faculty development mechanism,integrating high-quality open-access databases and virtual laboratories,and developing interpretable and trustworthy algorithmic framework to support mechanism understanding,data analysis,and risk decision-making.Looking ahead,teachers need to further update the knowledge system of toxicology,integrate metaverse-based immersive learning environments,and promote the intelligent transformation of competency certification,thereby systematically cultivating interdisciplinary talents to provide strong support for precision-oriented public health governance.
作者
常秀丽
卢国栋
周志俊
CHANG Xiuli;LU Guodong;ZHOU Zhijun(Department of Occupational Health and Toxicology,School of Public Health,Fudan University,Shanghai 200032,China)
出处
《基础医学教育》
2025年第12期1180-1184,共5页
Basic Medical Education
关键词
毒理学
教育改革
人工智能
预测毒理学
教育伦理
toxicology
educational reform
artificial intelligence
predictive toxicology
educational ethics
