Revolutionizing personalized medicine through AI-driven drug discovery

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Authors: Mayur Rele, Dipti Patil, Anitha Julian, M Udaya Krishnan
Cited by: 0

Abstract

This groundbreaking AI-driven technology is transforming personalized medicine by enabling the identification of optimal medication candidates, predicting their effectiveness, and creating tailored treatment plans. By integrating molecular simulations, deep learning algorithms, and bioinformatics, the approach significantly reduces the time and cost of traditional drug discovery. Leveraging multi-omics data, including genomics, proteomics, and transcriptomics, it enhances drug design, optimizes molecular interactions, and accelerates drug target identification. Early results from pilot studies indicate improved drug development efficiency and precise predictions of individual patient responses. This AI-based paradigm has the potential to revolutionize precision medicine, offering patients customized therapies and better treatment options for various medical conditions.

Fields of Study & Subjects

Computational Drug Discovery Methods Artificial Intelligence in Healthcare and Education Science Research and Medicine

Publication details

Journal / source
CRC Press eBooks
Pages
803–809
Publication date
10 March 2026
Language
EN
Document type
Book chapter