Journal of Integrative Health Research

An Official Publication of Sankalchand Patel University, Visnagar, Gujarat, India.
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Volume - 1 | Issue - 1 (Jan-Jun 2024)

Revolutionizing Drug Discovery: The Role of Artificial Intelligence in Modern Drug Design

Author: Indla R, Baghel VS, Soni P, Khuteta N, Prajapati A, Virani H A.
Published Online: November 30, -0001
Abstract
References

The traditional drug discovery process is slow, expensive, and prone to high failure rates, with timelines of 10–15 years and costs reaching $1–2 billion. Recent advancements in artificial intelligence (AI) have revolutionized drug design by enabling the analysis of vast biomedical datasets, identifying patterns, and making predictions that streamline and optimize the drug discovery pipeline. This article explores the transformative role of AI methodologies, including Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and generative models, in accelerating target identification, lead compound optimization, and predicting drug toxicity or efficacy. AI applications in drug repurposing, de novo drug design, and the prediction of drug-target interactions are discussed, showcasing significant reductions in time and resource requirements. The article also highlights critical challenges, such as data quality, model interpretability, and regulatory concerns, which must be addressed to fully realize the potential of AI in drug discovery. With continued advancements and collaboration between computational and pharmaceutical sciences, AI promises to revolutionize drug development, paving the way for personalized and precision medicine.

Keywords: Artificial Intelligence (AI), Deep Learning (DL), Natural Language Processing (NLP), Drug Repurposing, Lead Compound Optimization, DrugTarget Interactions, De Novo Drug Design.
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