APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN CLINICAL PHARMACY: A BIBLIOMETRIC ANALYSIS OF THE EVOLUTION OF SCIENTIFIC PRODUCTION BETWEEN 2019 AND 2026

Abstract

 Artificial Intelligence (AI) has promoted significant transformations in healthcare, including Clinical Pharmacy, by enabling new strategies for clinical decision support, pharmacotherapy optimization, and improvement of patient safety. This study aimed to analyze the global scientific production on Artificial Intelligence applications in Clinical Pharmacy between 2019 and 2026 through a bibliometric analysis. This is a quantitative, descriptive, and documentary study based on 432 scientific records retrieved from the PubMed database. Indicators related to publication trends over time, author productivity, geographic distribution, publication sources, institutional collaboration, and frequency of scientific terms were analyzed. Data were organized and evaluated using bibliometric approaches to identify research trends and patterns in the field. Results demonstrated significant growth in scientific production, particularly after 2023, a period associated with the expansion of generative artificial intelligence and large language models. Scientific productivity was concentrated among a limited number of authors, with the United States, China, India, and France representing the main contributors to international production. Universities and healthcare institutions played an important role in scientific collaboration. Textual analysis revealed a predominance of terms related to Artificial Intelligence, ChatGPT, Clinical Pharmacy, pharmacists, Machine Learning, and large language models. It is concluded that AI applied to Clinical Pharmacy represents an emerging, interdisciplinary, and rapidly expanding scientific field, with potential to transform pharmaceutical practice. However, further clinical studies are required to evaluate its effectiveness, safety, and practical implementation in healthcare settings.