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Author(s): Rutuja R. Kamble1, * Sanika S. Varale2, Hrushikesh D. Sajanikar3, Shivani S. Kavale4, Sheetal K. Kamble5, Shoan V. Mane6

Email(s): 1rutujak725@gmail.com

Address:

    Y. D. Mane Institute of Pharmacy, Kagal 416 216, Maharashtra, India

Published In:   Volume - 4,      Issue - 10,     Year - 2025

DOI: https://doi.org/10.71431/IJRPAS.2025.41002  

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ABSTRACT:
Artificial intelligence (AI) has emerged as a transformative force in pharmaceutical research, revolutionizing the traditional process of drug discovery and development. Conventional methods are lengthy, costly, and prone to high failure rates, whereas AI provides a faster, data-driven, and more efficient alternative. Through techniques such as machine learning, deep learning, and predictive analytics, AI accelerates target identification, molecular design, and lead optimization while improving safety assessments and clinical trial efficiency. Current innovations, including protein structure prediction, generative AI models, and integration of multi-omics data, are reshaping modern drug discovery by enabling the development of novel and precise therapeutics. Moreover, AI contributes to post-market surveillance by detecting adverse reactions and ensuring ongoing drug safety. Despite its remarkable potential, several challenges persist, including data quality and standardization issues, limited model interpretability, regulatory uncertainty, and ethical considerations. Addressing these barriers requires collaboration between researchers, regulators, and technology experts to ensure transparency, reproducibility, and responsible implementation. Looking ahead, the integration of AI with quantum computing, systems biology, and personalized medicine is expected to significantly enhance innovation, reduce development timelines, and increase the overall success rate of new drugs. Ultimately, AI is paving the way for a new era of intelligent, efficient, and patient-centered pharmaceutical discovery.

Cite this article:
Rutuja R. Kamble, Sanika S. Varale, Hrushikesh D. Sajanikar, Shivani S. Kavale, Sheetal K. Kamble, Shoan V. Mane. AI and The Future of Drug Discovery: From Innovation to Implementation. IJRPAS, October 2025; 4(10): 6-25.DOI: https://doi.org/https://doi.org/10.71431/IJRPAS.2025.41002


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