Harnessing Artificial Intelligence in Pharmaceutical Sciences: An Integrative Review

Abstract

The integration of artificial intelligence (AI) into pharmaceutical sciences represents a transformative advancement in modern healthcare. AI techniques—ranging from machine learning and natural language processing to deep learning architectures—have begun to optimize drug discovery, enhance pharmacovigilance, personalize therapy, and streamline clinical trial design. Through pattern recognition and predictive analytics, AI can identify novel drug candidates, repurpose existing drugs, and predict adverse drug reactions with unprecedented accuracy. Moreover, AI-driven algorithms are revolutionizing pharmaceutical supply chains, ensuring optimal inventory management and real-time decision-making. In community and hospital pharmacy settings, AI supports clinical decision-making, medication therapy management, and adherence monitoring, ultimately elevating patient outcomes. Despite these innovations, challenges such as data privacy,ethical considerations, and regulatory frameworks must be addressed to ensure responsible and effective deployment. This paper underscores the growing relevance of AI in pharmacy and highlights its potential to redefine pharmaceutical research, development, and practice.