AI in Patient Care and Personalized Medicine in Pharmaceutical Industries

Abstract

Artificial intelligence (AI) is reshaping healthcare and personalized medicine, particularly in the pharmaceutical industry. This review provides a comprehensive examination of current AI applications across various stages of the drug development pipeline, including drug discovery, clinical trial design, patient stratification, diagnosis, and treatment personalization. By employing advanced computational approaches such as machine learning, deep learning, and natural language processing, AI enables the integration and analysis of large and complex biological and clinical datasets, including genomic, proteomic, and electronic health record data. These capabilities facilitate the identification of novel therapeutic targets and support the development of individualized treatment strategies. The review also addresses critical considerations such as data quality, algorithmic transparency, ethical challenges, and regulatory frameworks that influence the safe and effective deployment of AI technologies. Furthermore, it highlights the growing need for robust data integration, interpretation strategies, and interdisciplinary collaboration to fully realize AI’s potential in advancing personalized medicine. Future perspectives emphasize AI’s role as a transformative tool for innovation in patient-centered pharmaceutical care.

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