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

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.