Intersection of ChatGPT and Pharmacology: A Bibliometric Assessment of Research Trends and Key Themes

Mahmoud Kandeel

Background and Objective: The rapid evolution of Artificial Intelligence (AI) technologies has profoundly impacted various scientific fields, including pharmacology. The ChatGPT, an advanced language model, has become a valuable tool in this domain, enhancing productivity and innovation. This study aims to investigate the integration of advanced AI technologies, particularly ChatGPT, into pharmacological research through a comprehensive bibliometric analysis. Materials and Methods: A comprehensive search was conducted in the Scopus database, using specific keywords related to ChatGPT, AI and pharmacology. The search yielded 274 relevant articles. The selected articles were analyzed using bibliometric tools to construct co-authorship and keyword co-occurrence networks, highlighting key research areas and trends. Results: The bibliometric analysis identified five research clusters: Experimental and Molecular Pharmacology, AI and Computational Approaches, Clinical and Human Studies, Veterinary and Animal Science and Chemical and Screening Methods. Keyword co-occurrence mapping highlighted prominent themes like ‘machine learning’, ‘gene expression’ and ‘clinical pharmacology’. A dramatic increase in publications was observed, particularly from 2020 to 2024, reflecting the growing integration of AI in pharmacological research. Conclusion: The findings emphasize the importance of addressing ethical considerations and fostering collaborations between AI experts and pharmacologists to ensure responsible and innovative advancements in pharmacology and avoid the concerns raised by the use of AI tools such as ChatGPT.

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