AI and ChatGPT Use in Pharmacy: Knowledge and practices among students and professionals

RS, GAYATHRI SHARMILI and JANANI, M and KARKUZHALI, S and MOUNIKA, MP and DEVI S, YAMUNA and ARUNKUMAR, M and CHERIAN, ANGEL and NITHYA, K and AZARUDEEN J, MOHAMMED and ABINESH, R and AMAAN SA, SYED and KUMAR T, THANISH and HABEEB S, MOHAMMED (2025) AI and ChatGPT Use in Pharmacy: Knowledge and practices among students and professionals. World Journal of Biology Pharmacy and Health Sciences, 21 (3). 047-053. ISSN 2582-5542

The purpose of this study is to find out how much pharmacist know and have used ChatGPT in their practice. this cross-sectional study was carried out between November and December 2024 to assess the potential and problem that pharmacist observed while integrating chatbots powered by AI(ChatGPT) in pharmacy practice. The correlation among perceived advantages and worries changed into evaluated the use of spearman’s rho correlation because of the data’s non-everyday distribution. A convenient sampling technique was used to choose the participant and the study questionnaire was distributed utilizing an online platform (WhatsApp and Email). The potential advantages of ChatGPT in the pharmacy practice where widely acknowledge by the participant. the majority of participant (13.4%) concurred that educational material about drug interaction and pharmacy products provided using ChatGPT, with 82.3% of responders believe that ChatGPT is a machine learning algorithm.in contrast to those who were either unsure or had not heard of ChatGPT (23.4%), individuals who had heard of it were more likely to have strong concerns (68.5%) (p=0.002). finally, the result shows a significant association between the use and perception of the AI tool(p<0.001). Although ChatGPT has shown promise in health and pharmaceutical practice, its application should be rigorously regulated by evidence-based law. According to the study’s findings, pharmacists support the use of ChatGPT in pharmacy practice but have concerns about it use due to ethical reasons, legal problems, privacy concerns worries about the accuracy of the data generated data learning, and bias risk.