Innovation and practice of artificial intelligence-empowered training model for applied pharmaceutical talents in a local university

Published on Oct. 28, 2026Total Views: 23 times Total Downloads: 7 times Download Mobile

Author: WANG Yuanyuan ¹ XIE Qian ¹ LIU Zheng ¹ YANG Zhihui ² HE Fangling ^1, ³ CHANG Yiqun ⁴ ZENG Xuxin ^1, ³  GUO Jialiang ^1, ^3, ⁴

Affiliation: 1.School of Medicine, Foshan University, Foshan 528225, Guangdong Province, China 2.School of Computer Science and Artificial Intelligence, Foshan University, Foshan 528225, Guangdong Province, China 3.Department of Pharmacy, The Third Affiliated Hospital of Foshan University, Foshan 528231, Guangdong Province, China 4.College of Pharmacy, Jinan University, Guangzhou 511436, China

Keywords: Artificial intelligence Pharmaceutical education Applied talents Industry-education integration Local universities

DOI: 10.12173/j.issn.1004-4337.202601046

Reference: Wang YY, Xie Q, Liu Z, et al. Innovation and practice of artificial intelligence-empowered training model for applied pharmaceutical talents in a local university[J]. Journal of Mathematical Medicine, 2026, 39(10): 781-786. DOI: 10.12173/j.issn.1004-4337.202601046.[Article in Chinese]  Copied

Abstract
Full-text
References

Abstract

Artificial intelligence (AI) technology is profoundly transforming the entire process of drug research and development, driving the transition of pharmaceutical education towards cultivating interdisciplinary talents of "Pharmacy+AI". However, local universities generally face practical dilemmas when carrying out such interdisciplinary education, including difficulty in breaking down disciplinary barriers, outdated curriculum systems, weak practical platforms and single evaluation methods. Based on regional industrial characteristics and relying on the provincial demonstration industrial college, the pharmacy major of Foshan University has explored a feasible "Pharmacy+AI" training path for applied talents suitable for local universities through systematic reforms, such as establishing the "Artificial Intelligence Pharmacy" micro-curriculum, constructing a smart curriculum cluster, conducting AI-assisted drug research and development, deepening university-enterprise collaborative practice and innovating a multi-dimensional evaluation system. Practice has shown that this model has effectively improved students' ability to solve practical industrial problems, significantly enhanced graduates' employment quality and achieved remarkable teaching and scientific research results. It has formed replicable and promotable local experience, providing a reference for similar universities to carry out new medical education reforms.

Full-text

Please download the PDF version to read the full text: download

References

1. 马蓁, 洪兰, 戚建平. 人工智能赋能药学拔尖创新人才培养体系的探索[J]. 药学教育, 2025, 41(5): 1-6.MaZ, HongL, QiJP. Exploration of an AI-empowered training system for top innovative talents in pharmacy[J]. Pharmaceutical Education, 2025, 41(5): 1-6. DOI: 10.3969/j.issn.1007-3531.2025.05.002.

2. 赵莹, 彭春花, 叶红, 等. 人工智能驱动下中医药高等院校数学实验与案例建模教学的实践与创新[J]. 数理医药学杂志, 2025, 38(8): 636-641.ZhaoY, PengCH, YeH, et al. Practice and innovation of mathematics experiment and case modeling teaching in traditional Chinese medicine colleges and universities driven by artificial intelligence[J]. Journal of Mathematical Medicine, 2025, 38(8): 636-641. DOI: 10.12173/j.issn.1004-4337.202503048.

3. RazaMA, AzizS, NoreenM, et al. Artificial intelligence (AI) in pharmacy:An overview of innovations[J]. Innov Pharm, 2022, 13(2): 10.24926/iip.v13i2.4839. DOI: 10.24926/iip.v13i2.4839.

4. ZhangK, YangX, WangY, et al. Artificial intelligence in drug development[J]. Nat Med, 2025, 31(1): 45-59. DOI: 10.1038/s41591-024-03434-4.

5. 国家发展改革委. “十四五”生物经济发展规划[EB/OL]. (2021-12-20) [2026-08-24].. https://www.gov.cn/zhengce/zhengceku/2022-05/10/content_5689556.htm.

6. 宋建飞, 何勤, 高慧媛, 等. 人工智能赋能高等药学教育新形态教材的现实挑战及政策建议[J]. 药学教育, 2025, 41(5): 7-11.SongJF, HeQ, GaoHY, et al. Practical challenges and policy recommendations for developing AI-empowered new-form textbooks in higher pharmaceutical education[J]. Pharmaceutical Education, 2025, 41(5): 7-11. DOI: 10.3969/j.issn.1007-3531.2025.05.003.

7. 张智朝, 朱峰, 曾苏. 人工智能赋能新药研发:数智药学的全链条创新实践[J].中国现代应用药学, 2025, 42(17): 2981-2983.ZhangZZ, ZhuF, ZengS. Artificial intelligence-enabled drug discovery and development: end-to-end innovation in digital pharmaceutics[J]. Chinese Journal of Modern Applied Pharmacy, 2025, 42(17): 2981-2983. DOI: 10.13748/j.cnki.issn1007-7693.20252412.

8. 周展, 曹戟, 周斌彬, 等. 人工智能赋能药学教育改革的探索与实践[J]. 药学教育, 2025, 41(4): 1-6. [ZhouZ, CaoJ, ZhouBB, et al. Exploration and practice of AI-empowered pharmaceutical education reform[J]. Pharmaceutical Education, 2025, 41(4): 1-6.].https://jiaoyu.cpu.edu.cn/article/id/959895d5-33c4-44bb-8d10-22e7343b4525.

9. 郭嘉亮, 颜海波, 杨凌, 等. 科研成果在药物化学实验教学中的应用[J]. 药学教育, 2015, 31(3): 56-60.GuoJ, YanHB, YangL, et al. Practice and exploration on the application of research achievements in the medicinal chemistry experiments[J]. Pharmaceutical Education, 2015, 31(3): 56-60. DOI: 10.16243/j.cnki.32-1352/g4.2015.03.016.

10. 杨彬, 曾煦欣, 邓涛, 等. 产业导向下基于OBE理念的药物分析课程改革与探索[J]. 海峡药学, 2025, 37(3): 53-56.YangB, ZengXX, DengT, et al. Exploration on curriculum reform of pharmaceutical analysis based on the OBE theory under the industrial-orientation[J]. Strait Pharmaceutical Journal, 2025, 37(3): 53-56. DOI: 10.3969/j.issn.1006-3765.2025.03.012.

11. 郭嘉亮, 李艳萍, 赵志雄, 等. 服务地方产业, 建设医药产业学院[J]. 药学教育, 2020, 36(6): 17-20.GuoJ, LiY, ZhaoZ, et al. On the construction of a medical industry college for local industries[J]. Pharmaceutical Education, 2020, 36(6): 17-20. DOI: 10.16243/j.cnki.32-1352/g4.2020.06.005.

12. 佛山市新闻传媒中心. 着力构建以实体经济为根基的现代化产业体系[N]. 佛山日报,2025-10-30(A02)..https://epaper.fsonline.com.cn/fsrb/html/2025-10/30/content_69119_316234.htm.

13. 佛山市新闻传媒中心. 云东海打造医药健康“产业引力场”[N]. 佛山日报, 2025-12-22(A02)..https://epaper.fsonline.com.cn/fsrb/html/2025-12/22/content_69734_319211.htm.

14. 中共中央, 国务院. 教育强国建设规划纲要（2024—2035年）[EB/OL]. (2025-01-19)[2026-08-24]..https://www.gov.cn/gongbao/ 2025/issue_11846/202502/content_7002799.html.

15. 张俊宗, 解睿. 超越知识本位:跨学科课程的流变逻辑与生成机制[J]. 高等工程教育研究,2025, (6): 99-105. [ZhangJZ, XieR. Beyond the knowledge base: the rheological logic andgeneration mechanism of interdisciplinary courses[J]. Research in Higher Education of Engineering, 2025, (6): 99-105.https://kns.cnki.net/kcms2/article/abstract?v=-w8R4t09JVXCGFmgln3dZTU9-Ssm1TCFuDIWUwiihWBRvqhRGRPg6Kn34vSeOoMk11-gI5Jc91gQFdFegHN8goVHrNKo7Wd7LAAJMH2zRPHMtoWhsm_LWbeMnyfYC5YnCRj09jx0JoXhp6JVa2CuTUg6EUsTB5VWzboJDb01oX3y2q4LxQj6og==&uniplatform=NZKPT&language=CHS.

16. 李一鸣, 吴佼, 蒋建利, 等. “培优”背景下特色研究驱动式医学实验教学新模式探析[J]. 细胞与分子免疫学杂志, 2025, 41(1): 90-94.LiYM, WuJ, JiangJL, et al. Exploration of a new model of characteristic research driven medical experimental teaching under the background of "cultivating excellence"[J]. Chinese Journal of Cellular and Molecular Immunology, 2025,41(1): 90-94. DOI: 10.13423/j.cnki.cjcmi.009899.

17. 赵炬明. 关注学习效果:美国大学课程教学评价方法述评——美国“以学生为中心”的本科教学改革研究之六[J]. 高等工程教育研究, 2019, (6): 9-23. [ZhaoJM. Align with learning outcomes: highlights of course-level learning outcome assessments-studies of the SC undergraduate education reform in the USA (6)[J]. Research in Higher Education of Engineering, 2019, (6): 9-23.].https://d.wanfangdata.com.cn/periodical/CiBQZXJpb2RpY2FsQ0hJU29scjkyMDI2MDkxNTE0MjIxORIRZ2RnY2p5eWoyMDE5MDYwMDMaCGp1bzlkZGZy.

18. 郝莉, 冯晓云, 宋爱玲, 等. 新工科背景下跨学科课程建设的思考与实践[J]. 高等工程教育研究, 2020, (2): 31-40. [HaoL, FengXY, SongAL, et al. A study on the construction of interdisciplinary courses under the background of emerging engineering education[J]. Research in Higher Education of Engineering, 2020, (2): 31-40.].https://d.wanfangdata.com.cn/periodical/CiBQZXJpb2RpY2FsQ0hJU29scjkyMDI2MDkxNTE0MjIxORIRZ2RnY2p5eWoyMDIwMDIwMDYaCDh5cHU3azMy.

Exploration and reflection on integrating ideological and political elements of excellent traditional Chinese culture into evidence-based dental education