MINI REVIEW article
Front. Vet. Sci.
Sec. Veterinary Humanities and Social Sciences
A Paradigm Shift and Practical Exploration in Veterinary Pharmacology and Toxicology Teaching Reform in China 's Frontier Regions under AI Empowerment
Provisionally accepted
- 1Kunming University, Kunming, China
- 2First Affiliated Hospital of Kunming Medical University, Kunming, China
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Veterinary pharmacology and toxicology education in Southwest China's border regions faces unique challenges, including plateau animal diseases and transnational epidemic control, and the need for strict veterinary drug residue monitoring and toxic risk prevention, which traditional teaching methods cannot adequately address. This paper explores an AI-driven educational reform centered on data-driven instruction and virtual-real integration. By constructing dynamic regional knowledge graphs, personalized learning pathways, and high-fidelity simulation platforms for plateau pharmacology experiments and clinical decision-making, and toxicological risk assessment, we establish an intelligent teaching system tailored to frontier characteristics. The system deeply integrates pharmacological efficacy research with toxicological safety evaluation, an integration emphasized as the cornerstone of veterinary practice in ensuring drug safety, controlling residue risks, and safeguarding the "One World, One Health" paradigm. The reform also addresses digital divide risks while developing a multidimensional evaluation framework covering both therapeutic effectiveness and toxicological safety competencies. This paradigm shift aims to enhance the quality of veterinary pharmacology and toxicology education in border regions, providing systematic solutions for cultivating professionals capable of balancing drug efficacy and safety, responding to regional toxicological challenges, and serving regional development needs.
Keywords: artificial intelligence, High-Altitude Animal Diseases, Southwest Border Region, Teaching reform, veterinary pharmacology and toxicology
Received: 03 Nov 2025; Accepted: 26 Jan 2026.
Copyright: © 2026 Li, Ma, Du, Wang and Hongyan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Meiquan Li
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