AI and Drug Discovery

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Authors: Khushi Goyal, Amisha Vyas, Anupama Diwan
Cited by: 0
References: 52

Abstract

This chapter briefly and concisely addresses the evolutionary impact made due to artificial intelligence (AI) in drug discovery. The sections of the chapter include the process of drug discovery and drug design, their accelerated growth powered by AI and the current scenario, also a brief discussion on AI in personalized drug dosing. The literature comprehensively provides the difference between the traditional approaches and AI-based approaches in drug discovery. The section is followed by various application of AI in drug discovery such as finding and validating biomarkers for novel medications, repurposing the existing drugs with the help of AI, toxicity prediction and assessment, drug design and optimization, and data-analysis for high-throughput screening. AI aided development of therapeutic target for Alzheimer’s disease, serotonin 5-HT1A receptor agonist to treat OCD, MEK protein inhibitor identification, novel antibiotic discovery, i.e., Halicin, anti-plasmodia drug and management of terbinafine hepatotoxicity, witness positive contribution.AI is a necessary evil. AI algorithms will not be valid or reliable unless it takes into consideration the ethical aspects and the stipulated condition of the regulatory bodies. However, it has markedly transformed the struggle to get people keen on listening to the drug discovery research topics because it is topic people won’t stop debating and discussing about.

Fields of Study & Subjects

Computational Drug Discovery Methods Artificial Intelligence in Healthcare and Education Artificial Intelligence Applications

Publication details

Journal / source
Advanced technologies and societal change
Pages
217–238
Publication date
1 January 2026
Language
EN
Document type
Book chapter