From Genome to Monitor: Integrating Multi-Omics into Patient-Specific Anesthesia Digital Twins

This review article explores the emerging integration of multi-omics technologies (genomics, proteomics, and metabolomics) with artificial intelligence–driven anesthesia digital twins. It highlights how patient-specific molecular data can be combined with real-time physiological monitoring to create predictive, adaptive models that optimize anesthetic management, enhance patient safety, and enable precision perioperative care. The review discusses the underlying architecture, clinical applications, technical challenges, and future prospects of multi-omics–enabled digital twins in anesthesiology.