Artificial intelligence (AI) has emerged as a powerful tool in drug discovery and development, revolutionizing traditional processes and accelerating the identification of new therapeutic compounds. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), are being integrated into various stages of drug development, from target identification to clinical trials. This review explores the impact of AI on drug discovery, its advantages over conventional methods, key AI applications in pharmaceutical research, and the challenges associated with its implementation. The article also highlights future directions for AI in drug development, emphasizing its potential to enhance efficiency, reduce costs, and improve patient outcomes.
Keywords: Artificial intelligence, Drug discovery, Therapeutic compounds
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How to Cite This Article
Vancouver
Sachdev A, Mehta SS, Mehta CS. The integration of artificial intelligence in drug discovery and development: A transformative approach [Internet]. Indian J Pharm Pharmacol. 2025 [cited 2025 Sep 14];12(2):74-81. Available from: https://doi.org/10.18231/j.ijpp.2025.013
APA
Sachdev, A., Mehta, S. S., Mehta, C. S. (2025). The integration of artificial intelligence in drug discovery and development: A transformative approach. Indian J Pharm Pharmacol, 12(2), 74-81. https://doi.org/10.18231/j.ijpp.2025.013
MLA
Sachdev, Anik, Mehta, Sanwal Singh, Mehta, Chanjiv Singh. "The integration of artificial intelligence in drug discovery and development: A transformative approach." Indian J Pharm Pharmacol, vol. 12, no. 2, 2025, pp. 74-81. https://doi.org/10.18231/j.ijpp.2025.013
Chicago
Sachdev, A., Mehta, S. S., Mehta, C. S.. "The integration of artificial intelligence in drug discovery and development: A transformative approach." Indian J Pharm Pharmacol 12, no. 2 (2025): 74-81. https://doi.org/10.18231/j.ijpp.2025.013