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arXiv · 2606.11264

OmniBioTwin: A System-of-Twinned-Systems Framework for Health Digital Twins

Zhaohui Wang·Yu Huang·Jiang Bian
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Abstract

Health digital twins (HDTs) promise patient-specific modeling and decision support but current approaches remain structurally fragmented: monolithic models that address a single organ or task lack cross-scale fidelity, while system-level twins lack generalizable architectural frameworks. We propose OmniBioTwin, a System-of-Twinned-Systems (SoTS) framework that organizes HDTs as modular computational entities coupled through explicit interaction operators within a multi-layer network architecture. The framework comprises seven coordinated layers - spanning data integration, autonomous twin modeling, cross-scale coupling, temporal synchronization, and human-in-the-loop decision support. We demonstrate OmniBioTwin by instantiating a multiscale twin for glucagon-like peptide-1 (GLP-1) signaling pathways in Alzheimer's disease, illustrating how molecular, cellular, and organ-level twins can be composed and coupled within a unified system.

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Zhaohui Wang, Yu Huang, Jiang Bian. 2026-06-09. OmniBioTwin: A System-of-Twinned-Systems Framework for Health Digital Twins. https://doi.org/10.1109/ichi69079.2026.00266

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