Abstract

ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY: REVOLUTIONIZING PHARMACEUTICAL RESEARCH

Vaibhav Solanki*, Darshangiri Goswami, Dr. Khushbu Patel and Dr. C. N. Patel

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Abstract

The pharmaceutical industry is undergoing a transformative shift with the integration of Artificial Intelligence (AI) in drug discovery. AI technologies, including machine learning, deep learning, and natural language processing, are revolutionizing traditional methods by accelerating the identification of potential drug candidates, optimizing chemical structures, and predicting drug properties with unprecedented accuracy. The adoption of AI in pharmaceutical R&D has facilitated groundbreaking collaborations, enhanced the development of novel therapies, and significantly reduced attrition rates. This review explores the history, current landscape, and future prospects of AI in drug discovery, highlighting its applications in target identification, virtual screening, de novo drug design, and predictive modeling. While challenges and limitations exist, the strategic integration of AI with traditional approaches is poised to transform the pharmaceutical industry, ultimately enhancing patient care and global healthcare outcomes.

Keywords: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP).