Volume : 12, Issue : 10, October – 2025
Title:
A REVIEW ON AI-DRIVEN DRUG DISCOVERY: CURRENT TRENDS AND FUTURE DIRECTIONS
Authors :
Ragul.M , S.Nivetha, P. Nandhini
Abstract :
The drug discovery process traditionally takes a longer time to be developed and is expensive to the high failure rate, calling for very new implementations to accelerate and optimize the development of therapeutics. The transformational AI has opened several options of data-centric problems to solve during various phases of the drug discovery pipeline. AI methods like machine learning, deep learning, natural language processing, and generative models offer great possibilities in target identification, virtual screening, lead optimization, and clinical trial design. Case studies reveal how AI has been applied for the discovery of new compounds, drug repurposing, and precision medicine. Challenges, however, exist to this day, such as data quality issues, model interpretability, regulatory challenges, and integration into existing pharma frameworks. This review provides an extensive insight into the major AI-driven trends in drug discovery, emphasizing key successes and limitations and taking an inside look into the future, including AI convergence with quantum computing and personalized medicine, to transform the pharmaceutical innovation landscape.
Keywords: Artificial Intelligence (AI), Drug Discovery, Machine Learning, Deep Learning, Precision Medicine, Computational Drug Design, Pharmaceutical Innovation
Cite This Article:
Please cite this article in press Ragul.M et al.,A Review On Ai-Driven Drug Discovery: Current Trends And Future Directions, Indo Am. J. P. Sci, 2025; 12(10).
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