Applications and prospects of prompt engineering in pharmaceutical popularization
- VernacularTitle:药学科普中提示词工程的应用与展望
- Author:
Xinyi FAN
1
;
Yan QIAN
1
;
Mingyang ZHU
1
Author Information
1. Dept. of Pharmacy，the Second Affiliated Hospital of Chongqing Medical University，Chongqing 400010，China
- Publication Type:Journal Article
- Keywords:
artificial intelligence;
large language models;
pharmaceutical popularization;
prompt engineering;
human-machine collaboration
- From:
China Pharmacy
2026;37(11):1485-1489
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE This study aims to establish a prompt engineering system for large language models in pharmaceutical popularization， and provide references for pharmacists to carry out efficient and standardized science popularization work. METHODS This study systematically expounded the principles and classifications of prompt engineering， as well as its effect on alleviating problems including model output hallucinations and poor interpretability. The design and optimization strategies of prompt engineering were defined for two core scenarios， namely text-to-text and text-to-image. Typical examples were adopted to compare the output effects before and after application. In addition， the limitations of prompt engineering applied in pharmaceutical popularization at the current stage were summarized. RESULTS In the two major scenarios of pharmaceutical popularization， well-designed prompt engineering improved the accuracy， readability and efficiency of outputs generated by large language models， and produced personalized popularization content adapted to clinical practice. CONCLUSIONS Prompt engineering can effectively improve the output quality of pharmaceutical popularization. The formulated standardized prompt engineering templates tailored for pharmaceutical popularization， can help pharmacists improve the efficiency and quality of popularization content creation.
