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

Researchers introduce OmniBioTwin, a modular framework for health digital twins that integrates multiple biological scales through a seven-layer architecture. The system demonstrates how molecular, cellular, and organ-level computational models can be coupled together, using GLP-1 signaling pathways in Alzheimer's disease as a proof-of-concept application.

OmniBioTwin addresses a fundamental limitation in computational biology: the inability to seamlessly connect models operating at different biological scales. Existing digital twin approaches typically operate in isolation—either focusing narrowly on single organs or lacking generalized architectural frameworks that enable cross-scale interaction. This fragmentation prevents accurate simulation of complex disease mechanisms where molecular changes cascade through cellular processes to produce organ-level dysfunction.

The framework's significance lies in its systematic approach to integration. By organizing digital twins as modular entities coupled through explicit interaction operators within a multi-layer network, OmniBioTwin creates a reusable template applicable beyond the GLP-1/Alzheimer's use case. The seven coordinated layers—spanning data integration, autonomous modeling, cross-scale coupling, temporal synchronization, and human-in-the-loop support—represent a comprehensive blueprint for future health digital twin development.

For the biotech and pharmaceutical sectors, this architecture enables more precise patient-specific modeling and accelerated drug development. Researchers can simulate how interventions at one biological scale propagate through the system, reducing reliance on expensive clinical trials. The human-in-the-loop component ensures clinical decision-makers remain central to the process rather than ceding authority entirely to automated systems.

The broader impact extends to precision medicine infrastructure. As digital twin technologies mature, frameworks like OmniBioTwin could standardize how multiscale biological simulations are constructed and validated. This standardization is essential for clinical adoption, regulatory approval, and enabling institutions to collaborate on shared computational models.

• →OmniBioTwin solves the fragmentation problem in health digital twins by enabling modular composition of multi-scale biological models.
• →The seven-layer architecture provides a generalizable framework applicable across different disease contexts and biological systems.
• →The GLP-1/Alzheimer's pathway demonstration shows how molecular, cellular, and organ-level twins can be coupled within a unified computational system.
• →Human-in-the-loop design ensures clinical practitioners maintain decision authority while leveraging computational insights.
• →Standardized frameworks like this could accelerate precision medicine adoption by reducing development fragmentation across institutions.