Abstract: OBJECTIVE To analyze the evolution of the focus of Chinese pharmaceutical administration, so as to improving the effectiveness of drug regulation. METHODS Through word frequency and social network analysis, the word cloud and network graph were visualized for the evolution process of Chinese drug regulatory policies, and the different evolutionary characteristic of policies content were analyzed using graph density, clustering coefficient, betweenness centrality, degree centrality and other indicators. RESULTS There were differences in network characteristics in different periods, the overall network connection tended to be tight, the structure tended to be optimized, and the connection between individual network subgroups was gradually complicated. However, the number of subgroups decreased in 2018—2022, and the core nodes were transferred. CONCLUSION In the current special period of “epidemic economy”, it is necessary to broaden the special policy areas and strengthen the coordination and intersection of policy concerns.