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#artificial intelligence Open access

DRUG REPURPOSING USING ARTIFICIAL INTELLIGENCE AND NETWORK PHARMACOLOGY FOR NEURODEGENERATIVE DISEASES: A COMPREHENSIVE REVIEW

Varshini K.1 Ruba Sree N.1*
Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods Bioinformatics and Genomic Networks

Abstract

Alzheimer's disease (AD), Parkinson's disease (PD) and multiple sclerosis (MS) are complex neurodegenerative diseases that are significant public health problems worldwide. Drug repurposing involves using drugs that are already known to be safe for some purpose for a new purpose. It's more likely to be a success than developing novel drugs. Therefore, drug repositioning could serve as a method to hasten the drug discovery process while also conserving both expenditure and time. Artificial intelligence (AI), machine learning (ML), and network-based pharmacology has transformed drug repositioning with integrated analysis of multi-omics data, knowledge biomedical knowledge graphs and real-world evidence (RWE). An assessment of the contemporary state of AI-powered drug repositioning and network-based pharmacology tactics applied to neurodegenerative illnesses comprising major approaches, candidate drugs, mechanisms, and translation barriers. The topic of this paper is the integration of multi-omics, systems biology, and sex-specific considerations in drug delivery tactics. Finally, it outlines potential paths towards clinical translation for the field – in AI related precision medicine and experimental testing.

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