The irrational use of narcotic drugs and psychotropic drugs has let to sig-nificant public health issues in Europe and the United States. It is a key challenge in the regulatory work to assess the risk of drug abuse and other irrational use pattern, and to supervise the entire process of the use of narcotic and psychotropic drugs. Over recent years, an increasing number of studies oversea have used machine learning methods to build predictive models to rapidly identify drug abuse and drug use disorders, predict drug dependency, persistent use and other irrational use patterns and adverse effects using real-world data, while Chinese scholars still pay less attention to similar research para-digms. This paper compares the status of research on narcotic and psychotropic drug prediction models, mainly focuses on the related research of opioid drug risk prediction, summarizes the research scenarios and key points of research design, as well as presents considerations on model transformation and regulatory priorities for China, aiming to provide suggestions for the use of machine learning in the field of narcotic and psychotropic drug regulation in China.

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