HemaTwin: Artificial Intelligence Based Molecular Digital Twin of Human Blood

Dinesh Appavoo, Olivia Levine • 2026

Abstract

Blood is a complex biological system composed of cellular elements, plasma proteins, metabolites, gases, and transient foreign agents such as pathogens. While clinical hematology characterizes blood primarily through cellular and biochemical assays, recent advances in structural biology and artificial intelligence enable molecular-level representation of blood components. In this work, we present a comprehensive framework for cataloging, storing, and comparing blood constituents using established biological databases and AlphaFold 3-based structural prediction. By integrating proteomics, genomics, metabolomics, and pathogen sequence data with three-dimensional structural repositories such as the Protein Data Bank (PDB), we propose a unified digital architecture for constructing a molecular digital twin of human blood. This framework facilitates standardized storage, structural comparison, and computational analysis of blood components for applications in diagnostics, systems biology, and drug discovery.