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Pharmacy
Special Issues
AI Use in Pharmacy and Pharmacy Education
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AI Use in Pharmacy and Pharmacy Education

A special issue of Pharmacy (ISSN 2226-4787). This special issue belongs to the section "Pharmacy Education and Student/Practitioner Training".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 10742

Special Issue Editors

Dr. Bernadette Cornelison

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Guest Editor
R. Ken Coit College of Pharmacy, University of Arizona, Roy P. Drachman Hall, P.O. Box 210202, Tucson, AZ 85721, USA
Interests: interprofessional education; ambulatory medicine; pharmacy education; patient simulation
Dr. Christopher J Edwards

E-Mail Website
Guest Editor
R. Ken Coit College of Pharmacy, University of Arizona, Roy P. Drachman Hall, P.O. Box 210202, Tucson, AZ 85721, USA
Interests: analgesia; sedation; toxicology; infectious diseases; trauma; resuscitation; pharmacy practice; pediatrics

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue of Pharmacy titled “AI Use in Pharmacy and Pharmacy Education”. As artificial intelligence (AI) is increasingly integrated into healthcare and education, its impact on pharmacy practices and pharmacy education will continue to evolve. AI offers numerous advantages, such as enhanced clinical decision support, the automation of routine tasks, and personalized learning experiences. However, its limitations—such as inaccuracies, biases, and over-reliance—highlight the need for critical evaluation by pharmacy professionals and educators.

In pharmacy education, AI has the potential to enhance learning, but students may also view it as a shortcut rather than a tool for deeper understanding. This raises important questions about how AI can be implemented responsibly in the PharmD curriculum and how educators can encourage critical thinking and ethical AI use among students.

We invite submissions exploring the application, benefits, and challenges of AI in pharmacy practices and pharmacy education. Manuscripts may include original research, brief reports, reviews, or short communications. We also encourage submissions of resident or trainee research projects that examine AI utilization in pharmacy settings. We hope that this Special Issue will serve as a platform for sharing best practices, innovative strategies, and research findings that will inform the responsible and effective use of AI in pharmacy.

Dr. Bernadette Cornelison
Dr. Christopher J Edwards
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmacy is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • education
  • pharmacy
  • artificial intelligence
  • community pharmacy
  • clinical pharmacy services

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Published Papers (6 papers)

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Research

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17 pages, 230 KB  
Article
Guidance for Use of Artificial Intelligence in Community Pharmacy Practice: Perspectives and Needs of Pharmacists in Ontario, Canada
by Zubin Austin and Paul Gregory
Pharmacy 2026, 14(2), 57; https://doi.org/10.3390/pharmacy14020057 - 1 Apr 2026
Viewed by 756
Abstract
Background: As Artificial Intelligence (AI) proliferates in society, community pharmacists must make decisions as to how to responsibly adopt this technology in their practice. Currently, there are few regulatory requirements or tools to support pharmacists in ensuring safe and ethical integration of AI [...] Read more.
Background: As Artificial Intelligence (AI) proliferates in society, community pharmacists must make decisions as to how to responsibly adopt this technology in their practice. Currently, there are few regulatory requirements or tools to support pharmacists in ensuring safe and ethical integration of AI in their work. Methods: An exploratory qualitative study of community pharmacists in Ontario, Canada was undertaken to examine their needs for guidance, regulation, and support in adopting AI in their practice. Results: Semi-structured interviews with 24 community pharmacists were undertaken to the point of thematic saturation. Constant-comparative analysis highlighted three key themes: (a) currently, AI is being used in unstandardized and unregulated ways; (b) pharmacists desire guidance or regulation focused on patient safety considerations; and (c) in the absence of regulation, ad hoc informal decision making is occurring. Conclusions: With or without formal regulation, AI is being adopted in pharmacy practice. Current reliance on informal network support without clear regulatory guidance raises concerns for pharmacists regarding patient safety and their work as professionals. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)
12 pages, 1248 KB  
Article
AI-Enabled Sacramento Public Health (SACPH) App: A Reproducible AI-Based Method for Population-to-Practice Reasoning in Foundational Sciences in Pharmacy Education
by Ashim Malhotra
Pharmacy 2026, 14(1), 10; https://doi.org/10.3390/pharmacy14010010 - 16 Jan 2026
Viewed by 501
Abstract
Foundational biomedical sciences are commonly taught without routine integration of local population health contexts, limiting students’ ability to connect mechanisms to community disease burden and practice responsibilities. In this method paper, we developed and piloted an AI-enabled “Sacramento County Public Health (SACPH)” AI [...] Read more.
Foundational biomedical sciences are commonly taught without routine integration of local population health contexts, limiting students’ ability to connect mechanisms to community disease burden and practice responsibilities. In this method paper, we developed and piloted an AI-enabled “Sacramento County Public Health (SACPH)” AI workflow and app prototype, a structured, faculty-authored prompt sequence designed to guide population-to-practice reasoning using publicly available data. The workflow was implemented during a TBL session with first-year PharmD students in an immunology course. Using splenectomy and risk of overwhelming post-splenectomy infection (OPSI) as an illustrative use case, students executed a standardized prompt sequence addressing data source identification, coding logic (diagnosis vs. procedure codes), population-level estimation with uncertainty framing, and translation to pharmacist-relevant prevention and counseling implications. Feasibility was defined by conceptual convergence. The validated reasoning workflow was subsequently translated into a prototype, app-style interface using generative design prompts. Across student teams, outputs converged on similar categories, consistent recognition of coding frameworks and verification steps, and directionally similar interpretations of local burden and pharmacist responsibilities. The prototype demonstrated successful externalization of the reasoning workflow into a modular, reproducible artifact. SACPH demonstrates a feasible, reproducible method for using generative AI to integrate foundational science instruction with local population health context and pharmacist practice reasoning, while supporting AI literacy competencies. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)
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19 pages, 917 KB  
Article
Leveraging Artificial Intelligence-Based Applications to Remove Disruptive Factors from Pharmaceutical Care: A Quantitative Study in Eastern Romania
by Ionela Daniela Ferțu, Alina Mihaela Elisei, Mariana Lupoae, Alexandra Burlacu, Claudia Simona Ștefan, Luminița Enache, Andrei Vlad Brădeanu, Loredana Sabina Pascu, Iulia Chiscop, Mădălina Nicoleta Matei, Aurel Nechita and Ancuța Iacob
Pharmacy 2026, 14(1), 7; https://doi.org/10.3390/pharmacy14010007 - 9 Jan 2026
Viewed by 763
Abstract
Artificial Intelligence (AI) has increasingly contributed to advancements in pharmaceutical practice, particularly by enhancing the pharmacist–patient relationship and improving medication adherence. This quantitative, descriptive, cross-sectional study investigated Eastern Romanian pharmacists’ perception of AI-based applications as effective optimization tools, correlating it with disruptive communication [...] Read more.
Artificial Intelligence (AI) has increasingly contributed to advancements in pharmaceutical practice, particularly by enhancing the pharmacist–patient relationship and improving medication adherence. This quantitative, descriptive, cross-sectional study investigated Eastern Romanian pharmacists’ perception of AI-based applications as effective optimization tools, correlating it with disruptive communication factors. An anonymous and online questionnaire was distributed to community pharmacists, examining sociodemographic characteristics, awareness of disruptive factors, and the perceived usefulness of AI. The sample included 437 respondents: pharmacists (55.6%), mostly female (83.8%), and aged between 25 and 44 (52.6%). Data analysis involved descriptive statistics and independent t-tests. The statistical analysis revealed a significantly positive perception (p < 0.001) of AI on pharmacist–patient communication. Respondents viewed AI as a valuable tool for reducing medication errors and optimizing counseling time, though they maintain a strong emphasis on genuine human interaction. Significant correlations were found between disruptive factors—such as noise and high patient volume—and the quality of communication. Participants also expressed an increased interest in applications like automatic prescription scheduling and the use of chatbots. The study concludes that a balanced implementation of AI technologies is necessary, one that runs parallel with the continuous development of pharmacists’ communication skills. Future research should focus on validating AI’s impact on clinical outcomes and establishing clear ethical guidelines regarding the use of patient data. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)
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16 pages, 213 KB  
Article
Responsible Adoption of Artificial Intelligence (AI) in Pharmacy Practice: Perspectives of Regulators in Canada and the United States
by Paul A. M. Gregory and Zubin Austin
Pharmacy 2025, 13(6), 152; https://doi.org/10.3390/pharmacy13060152 - 27 Oct 2025
Cited by 1 | Viewed by 2675
Abstract
Background: Use of Artificial Intelligence (AI) is proliferating in society and in pharmacy practice. For some, this represents a great advancement that will enhance effectiveness and efficiency of health care. For others, it is an existential risk that will worsen inequalities, lead to [...] Read more.
Background: Use of Artificial Intelligence (AI) is proliferating in society and in pharmacy practice. For some, this represents a great advancement that will enhance effectiveness and efficiency of health care. For others, it is an existential risk that will worsen inequalities, lead to deskilling of the workforce, and spiral beyond the comprehension or control of humans. Human-in-the-loop (HiL) vs. human-out-of-the loop (HoL) AI have different potential risks and challenges that raise questions regarding patient safety. Defining principles for responsible adoption of AI in pharmacy practice will be an important safeguard for both patients and the profession. Methods: Semi-structured interviews with 12 pharmacy regulators from across Canada and the United States were undertaken, with informed consent. Constant comparative data analysis using nVivo v15 was used to identify common themes. The COREQ framework was applied to assure quality of research processes used. Results: Pharmacy regulators highlighted the value of a principles-based, rather than rules-based, approach to AI. Core principles related to transparency, redundancy, audit and feedback, quality assurance, privacy/data security, alignment with codes of ethics, and interoperability were identified. There was limited consensus on the role of consent and choice as principles to be considered. Conclusions: The role of regulation in shaping responsible adoption of AI in pharmacy will be significant. This study highlighted a series of agreed-upon principles but also identified lack of consensus with respect to how consent and choice could be operationalized in pharmacy practice. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)

Other

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9 pages, 188 KB  
Brief Report
Pharmacy Students’ Perspectives on Integrating Generative AI into Pharmacy Education
by Kaitlin M. Alexander, Eli O. Jorgensen, Casey Rowe and Khoa Nguyen
Pharmacy 2025, 13(6), 183; https://doi.org/10.3390/pharmacy13060183 - 15 Dec 2025
Viewed by 1078
Abstract
Objective: This study aims to evaluate pharmacy students’ perceptions regarding the integration of generative artificial intelligence (GenAI) into pharmacy curricula, providing evidence to inform future curriculum development. Methods: A cross-sectional survey of Doctor of Pharmacy (PharmD) students at a single U.S. College of [...] Read more.
Objective: This study aims to evaluate pharmacy students’ perceptions regarding the integration of generative artificial intelligence (GenAI) into pharmacy curricula, providing evidence to inform future curriculum development. Methods: A cross-sectional survey of Doctor of Pharmacy (PharmD) students at a single U.S. College of Pharmacy was conducted in April 2025. Students from all four professional years (P1–P4) were invited to participate. The 10-item survey assessed four domains: (1) General GenAI Use, (2) Knowledge and Experience with GenAI Tools, (3) Learning Preferences with GenAI, and (4) Perspectives on GenAI in the curriculum. Results: A total of 110 students responded (response rate = 12.4%). Most were P1 students (56/110, 50.9%). Many reported using GenAI tools for personal (65/110, 59.1%) and school-related purposes (64/110, 58.1%) sometimes, often, or frequently. ChatGPT was the most used tool. While 40% (40/99) agreed or strongly agreed that GenAI could enhance their learning, 62.6% (62/99) preferred traditional teaching methods. Open-ended responses (n = 25) reflected a mix of positive, neutral, and negative views on GenAI in education. Conclusions: Many pharmacy students in this cohort reported using GenAI tools and demonstrated a basic understanding of GenAI functions, yet students also reported that they preferred traditional learning methods and expressed mixed views on incorporating GenAI into teaching. These findings provide valuable insights for faculty and schools of pharmacy as they develop strategies to integrate GenAI into pharmacy education. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)
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8 pages, 192 KB  
Brief Report
Accuracy and Safety of ChatGPT-3.5 in Assessing Over-the-Counter Medication Use During Pregnancy: A Descriptive Comparative Study
by Bernadette Cornelison, David R. Axon, Bryan Abbott, Carter Bishop, Cindy Jebara, Anjali Kumar and Kristen A. Root
Pharmacy 2025, 13(4), 104; https://doi.org/10.3390/pharmacy13040104 - 30 Jul 2025
Cited by 3 | Viewed by 3721
Abstract
As artificial intelligence (AI) becomes increasingly utilized to perform tasks requiring human intelligence, patients who are pregnant may turn to AI for advice on over-the-counter (OTC) medications. However, medications used in pregnancy may pose profound safety concerns limited by data availability. This study [...] Read more.
As artificial intelligence (AI) becomes increasingly utilized to perform tasks requiring human intelligence, patients who are pregnant may turn to AI for advice on over-the-counter (OTC) medications. However, medications used in pregnancy may pose profound safety concerns limited by data availability. This study focuses on a chatbot’s ability to accurately provide information regarding OTC medications as it relates to patients that are pregnant. A prospective, descriptive design was used to compare the responses generated by the Chat Generative Pre-Trained Transformer 3.5 (ChatGPT-3.5) to the information provided by UpToDate®. Eighty-seven of the top pharmacist-recommended OTC drugs in the United States (U.S.) as identified by Pharmacy Times were assessed for safe use in pregnancy using ChatGPT-3.5. A piloted, standard prompt was input into ChatGPT-3.5, and the responses were recorded. Two groups independently rated the responses compared to UpToDate on their correctness, completeness, and safety using a 5-point Likert scale. After independent evaluations, the groups discussed the findings to reach a consensus, with a third independent investigator giving final ratings. For correctness, the median score was 5 (interquartile range [IQR]: 5–5). For completeness, the median score was 4 (IQR: 4–5). For safety, the median score was 5 (IQR: 5–5). Despite high overall scores, the safety errors in 9% of the evaluations (n = 8), including omissions that pose a risk of serious complications, currently renders the chatbot an unsafe standalone resource for this purpose. Full article
(This article belongs to the Special Issue AI Use in Pharmacy and Pharmacy Education)
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