The Future of Pharmaceutical Information: A Case for Generative AI Over Pharmacopoeias and Medical Apps

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dc.contributor.authorBashirudeen Opeyemi Ibrahim
dc.contributor.authorOlubayo Adekanmbi
dc.contributor.authorAnthony Soronnadi
dc.date.accessioned2024-11-26T09:54:18Z
dc.date.available2024-11-26T09:54:18Z
dc.date.issued2024-11-25
dc.description.abstractTraditional sources of pharmaceutical information, such as pharmacopoeias and medical apps, need more scope, updated frequency, and depth of information as Artificial intelligence (AI) evolves, particularly through generative AI and large language models (LLMs) and a unique opportunity exists to remodel how healthcare professionals access pharmaceutical data. This paper explores how generative AI can surpass traditional methods by providing up-to-date, personalised, comprehensive drug information. When trained on extensive pharmaceutical datasets from codices, pharmacopoeias, and regulatory bodies like the FDA and WHO, generative AI can generate novel insights and streamline access to current pharmaceutical knowledge. By incorporating real-time updates and query-based systems such as AI-powered chatbots, generative AI ensures healthcare professionals can retrieve more accurate, relevant, and personalised drug interactions, dosage forms, and side-effect profiles. Findings suggest that generative AI offers grreat advantages over traditional drug information, enhancing decision-making and patient care outcomes even though its adoption raises concerns about data privacy, bias, and the reliability of AI-generated content. Rigorous validation processes and continuous updates are essential to maintaining trust in the system as generative AI is a powerful supplement to traditional pharmaceutical information sources, facilitating better-informed decisions by healthcare professionals while addressing many of the inherent challenges of pharmacopoeias and apps. Generative AI can help shape the future of pharmaceutical care which eventually improves patient outcomes by upholding ethical standards, ensuring accuracy, and integrating feedback from medical experts.
dc.identifier.citationBashirudeen O. I., Olubayo A. & Anthony S. (2024). “The Future of Pharmaceutical Information: A Case for Generative AI Over Pharmacopoeias and Medical Apps". In Proceedings of the International Conference on Artificial Intelligence and Robotics (MIRG-ICAIR 2024), pp. 23-28, MIRG
dc.identifier.isbn978-978-771-680-9
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/13068
dc.language.isoen
dc.publisherMIRG
dc.relation.ispartofseriesMIRG-ICAIR 2024
dc.titleThe Future of Pharmaceutical Information: A Case for Generative AI Over Pharmacopoeias and Medical Apps
dc.typeArticle
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