Application of Artificial Intelligence in Pharmacy Education: A Scoping Review

Artificial intelligence (AI) shows emerging potential in pharmacy education that it fundamentally enhancing the way students learn, practice, and apply clinical knowledge. With AI-driven adaptive learning systems, instruction becomes highly personalized, catering to individual learning styles and needs. This scoping review seeks to comprehensively synthesize the current literature on the application of artificial intelligence (AI) in pharmacy education, while also identifying gaps that demand further investigation. This scoping review was conducted in accordance with methodological guidance from the Joanna Briggs Institute. The literature search aimed to identify peer-reviewed publications in English in PubMed, Embase, and Scopus, which were searched from inception to August 7, 2025. Two reviewers independently completed title, abstract, and full-text screening against inclusion criteria. Data extracted were used to describe the body of literature using descriptive and qualitative approaches. A total of seven studies have been identified that explore the role of AI in pharmacy education. Five studies focus on how AI can change teaching and learning, while one study focuses on its capability to predict academic performance for admissions. The final study critically evaluates the benefits and limitations of employing AI text generation, particularly ChatGPT, highlighting its relevance and implications for the future of pharmacy education. At present, the number of publications exploring the application of AI in pharmacy education is quite limited. This presents significant challenges, including the necessity for faculty expertise and time, the restricted generalizability of available tools, insufficient outcomes data, and various legal and ethical considerations.

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Publication Details

Journal
Journal of Pharmacy Practice
Published
2026-09-17
DOI
https://doi.org/10.1177/08971900261491254
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Application of Artificial Intelligence in Pharmacy Education: A Scoping Review

Chiranjeev Sanyal, Ronald Watema-Lord
Journal of Pharmacy Practice
Artificial Intelligence in Healthcare and Education
article

Application of Artificial Intelligence in Pharmacy Education: A Scoping Review

Chiranjeev Sanyal, Ronald Watema-Lord
article en

Abstract

Artificial intelligence (AI) shows emerging potential in pharmacy education that it fundamentally enhancing the way students learn, practice, and apply clinical knowledge. With AI-driven adaptive learning systems, instruction becomes highly personalized, catering to individual learning styles and needs. This scoping review seeks to comprehensively synthesize the current literature on the application of artificial intelligence (AI) in pharmacy education, while also identifying gaps that demand further investigation. This scoping review was conducted in accordance with methodological guidance from the Joanna Briggs Institute. The literature search aimed to identify peer-reviewed publications in English in PubMed, Embase, and Scopus, which were searched from inception to August 7, 2025. Two reviewers independently completed title, abstract, and full-text screening against inclusion criteria. Data extracted were used to describe the body of literature using descriptive and qualitative approaches. A total of seven studies have been identified that explore the role of AI in pharmacy education. Five studies focus on how AI can change teaching and learning, while one study focuses on its capability to predict academic performance for admissions. The final study critically evaluates the benefits and limitations of employing AI text generation, particularly ChatGPT, highlighting its relevance and implications for the future of pharmacy education. At present, the number of publications exploring the application of AI in pharmacy education is quite limited. This presents significant challenges, including the necessity for faculty expertise and time, the restricted generalizability of available tools, insufficient outcomes data, and various legal and ethical considerations.

Journal of Pharmacy Practice
Dalhousie University (CA)
Quality Education
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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