IMPACT OF ARTIFICIAL INTELLIGENCE IN PHARMACY

Artificial Intelligence (AI) is revolutionizing the field of pharmacy, offering innovative solutions across drug discovery, formulation development, clinical decision-making, and patient care. This review explores the multifaceted role of AI in modern pharmacy, highlighting its applications in drug design, predictive modeling, precision medicine, and pharmaceutical supply chains. Machine learning algorithms, natural language processing, and data analytics have accelerated processes such as compound screening, pharmacovigilance, and personalized therapy development. Furthermore, AI enhances clinical outcomes through automated systems in medication dispensing, adherence monitoring, and health informatics integration. Despite its transformative potential, the implementation of AI in pharmacy also poses ethical, regulatory, and technical challenges that require careful navigation. This review outlines current advancements, evaluates real-world use cases, and discusses future prospects of AI in pharmaceutical sciences and healthcare systems.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-01
DOI
https://doi.org/10.5281/zenodo.18426064
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

IMPACT OF ARTIFICIAL INTELLIGENCE IN PHARMACY

*Sayali Chinchawade
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

IMPACT OF ARTIFICIAL INTELLIGENCE IN PHARMACY

*Sayali Chinchawade
article en

Abstract

Artificial Intelligence (AI) is revolutionizing the field of pharmacy, offering innovative solutions across drug discovery, formulation development, clinical decision-making, and patient care. This review explores the multifaceted role of AI in modern pharmacy, highlighting its applications in drug design, predictive modeling, precision medicine, and pharmaceutical supply chains. Machine learning algorithms, natural language processing, and data analytics have accelerated processes such as compound screening, pharmacovigilance, and personalized therapy development. Furthermore, AI enhances clinical outcomes through automated systems in medication dispensing, adherence monitoring, and health informatics integration. Despite its transformative potential, the implementation of AI in pharmacy also poses ethical, regulatory, and technical challenges that require careful navigation. This review outlines current advancements, evaluates real-world use cases, and discusses future prospects of AI in pharmaceutical sciences and healthcare systems.

Zenodo (CERN European Organization for Nuclear Research)
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Computational Drug Discovery Methods
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