Artificial Intelligence, Multi-Omics, and Digital Twin Technologies as Converging Pillars of Precision Medicine: A Comprehensive Review

Precision medicine is being reshaped by the convergence of artificial intelligence (AI), multi-omics profiling, and digital twin modelling. This review synthesizes spanning bioinformatics, drug discovery, cardiology, and pharmacogenomics to examine how foundation models, generative networks, and patient-specific virtual replicas are jointly advancing disease interpretation and individualized therapy. We describe representative AI architectures across omics layers, summarize digital twin applications in cardiology and oncology, and outline barriers including data heterogeneity, interpretability, cost, and equity. Coordinated, implementation-focused development is identified as the key determinant of clinical translation.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-05
DOI
https://doi.org/10.5281/zenodo.22327130
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence, Multi-Omics, and Digital Twin Technologies as Converging Pillars of Precision Medicine: A Comprehensive Review

Venna R Surya Anusha, Koppala RVS Chaitanya, Konkati Priyaranjan
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence, Multi-Omics, and Digital Twin Technologies as Converging Pillars of Precision Medicine: A Comprehensive Review

Venna R Surya Anusha, Koppala RVS Chaitanya, Konkati Priyaranjan
article en

Abstract

Precision medicine is being reshaped by the convergence of artificial intelligence (AI), multi-omics profiling, and digital twin modelling. This review synthesizes spanning bioinformatics, drug discovery, cardiology, and pharmacogenomics to examine how foundation models, generative networks, and patient-specific virtual replicas are jointly advancing disease interpretation and individualized therapy. We describe representative AI architectures across omics layers, summarize digital twin applications in cardiology and oncology, and outline barriers including data heterogeneity, interpretability, cost, and equity. Coordinated, implementation-focused development is identified as the key determinant of clinical translation.

Zenodo (CERN European Organization for Nuclear Research)
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Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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