NSFC-funded Chinese materia medica research (2015-2024): achievements output, research characteristics, and evolution.

BACKGROUND: To systematically analyze the project completion status and research characteristics in the field of Chinese Materia Medica (CMM, discipline code H32) funded by the National Natural Science Foundation of China (NSFC), thereby providing a basis for optimizing the allocation of scientific research resources and adjusting funding strategies. METHODS: Based on the NSFC big database system, a retrospective analysis was conducted to descriptively analyze the research output, potential translational capacity, and research characteristics of completed projects in the CMM field funded by NSFC from 2015 to 2024. RESULTS: From 2015 to 2024, a total of 4,574 projects in the CMM field were completed, with a compound annual growth rate (CAGR) of 3.0%. The cumulative total funding was 1.86 billion RMB, with an average of 410 KRMB per project. The average research output was 6.6 items per project, and the potential patent conversion ratio was 61%. For the first time, the 19 sub-directions within the CMM field were categorized into four echelons: double-high advantage, high-output low-conversion, low-output high-conversion, and Low-Output Low-Conversion areas. Key advantage areas included CMM pharmacodynamic substances, CMM resources, and ethnic pharmacology. Disease research primarily focused on cardiovascular and cerebrovascular diseases, tumors, metabolic diseases, and neurological disorders. Technical methodologies rapidly evolved from traditional chemical analysis to multi-omics and systems biology, while research mechanisms expanded towards multi-dimensional regulatory networks. CONCLUSION: NSFC funding for the CMM field has been consistently stable. The discipline demonstrates an overall trajectory characterized by deepening basic research, rapid iteration of technical methods, increasing diversification of research directions, and steadily improving translational potential. These findings provide data support and decision-making references for optimizing NSFC funding strategies in the CMM field.