Artificial Intelligence in Pharmaceutical and Health Sciences Education:
A PRISMA-Guided Narrative Literature Review of Educational Applications, Ethical Challenges, and Future Directions
DOI:
https://doi.org/10.61856/ncsvq208Keywords:
Artificial Intelligence, Pharmaceutical Education, Health Sciences, Ethical Challenges, Adaptive Learning, Virtual RealityAbstract
Artificial intelligence (AI) increasingly influenced pharmaceutical and health sciences education by transforming teaching, assessment, simulation-based learning, and curriculum development. This PRISMA-guided narrative literature review evaluated current educational applications, examined associated ethical challenges, and identified future directions for responsible curricular integration. A structured search of PubMed, Scopus, Web of Science, Google Scholar, and ScienceDirect identified English-language publications from 2020 to 2026. After duplicate removal, title and abstract screening, and full-text eligibility assessment, 32 studies and policy documents met the predefined criteria and were included in a qualitative narrative synthesis. Data were extracted and synthesized thematically. The review showed that AI-driven systems supported adaptive learning, virtual patient simulations, learning analytics, automated assessment, generative AI, and large language models, improving personalized learning, student engagement, educational efficiency, and clinical training. Important challenges involved data privacy, algorithmic bias, academic integrity, transparency, equitable access, AI literacy, and institutional governance. International policy recommendations emphasized ethical implementation and responsible governance in higher education. Overall, AI demonstrated considerable potential to improve pharmaceutical and health sciences education when combined with evidence-based educational practices, comprehensive faculty and student training, and robust ethical and regulatory frameworks. Continued interdisciplinary collaboration and responsible governance remained essential to ensure that AI complemented, rather than replaced, human-centered teaching and learning.
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