Abstract

UNVEILING THE FUTURE: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY

Dhakane Sumeet, Jain Rahul and Joshi Neeta*

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Abstract

In the ever-evolving landscape of pharmaceutical research, a groundbreaking shift is occurring with the combination of Artificial Intelligence (AI) in field of drug discovery. Traditional methods, laden with trial and error, resource-intensive experiments, and time constraints, are giving way to a data-driven revolution. AI, with its computational prowess, navigates the complexities of genomics, proteomics, and biological systems, transforming drug discovery into a strategic, predictive process. From target identification and validation using machine learning and network analysis to AI-driven drug design and optimization through generative models and reinforcement learning, the innovations are profound. Virtual screening, predictive analytics, and personalized medicine, empowered by AI, redefine efficiency, accuracy, and cost-effectiveness in drug development. Furthermore, AI's role in drug repurposing, automation of lab processes, natural language processing, drug safety prediction, and clinical trial optimization herald a new era where technology accelerates the pace of discovery, ensuring safer and more effective medications for the future.

Keywords: Artificial Intelligence, Network Analysis, Generative Models, Reinforcement Learning, Virtual Screening, Predictive Analytics, Personalized Medicine, Drug Repurposing, Lab Automation with AI, Target Identification.