%A Deepa Maheshvare,M. %A Raha,Soumyendu %A Pal,Debnath %D 2022 %J Frontiers in Network Physiology %C %F %G English %K Biophysical interactions,discrete network model,Functional Networks,hierarchical modeling,microvasculature and microenvironment,solute transport,Spatio-temporal dynamics,Systems Biology %Q %R 10.3389/fnetp.2021.802881 %W %L %M %P %7 %8 2022-January-12 %9 Methods %# %! Modeling multiscale physiological transport %* %< %T A Graph-Based Framework for Multiscale Modeling of Physiological Transport %U https://www.frontiersin.org/articles/10.3389/fnetp.2021.802881 %V 1 %0 JOURNAL ARTICLE %@ 2674-0109 %X Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches in which it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here, we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective–dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element–based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from in vitro–in vivo studies and vascular topology from imaging studies for examining the structure–function relationship of complex vasculatures. The framework can advance simulation of whole-body networks at user-defined levels and is expected to find major use in personalized medicine and drug discovery.