Speaker:
Abstract: Understanding infection and immunity-and immune responses in contexts ranging from arthritis to cancer-requires linking molecular, cellular, tissue, and whole-body dynamics across scales. Multiscale Virtual-Tissue models-physics-based, multicellular, agent-based simulations-provide a framework for connecting intracellular networks, cell behaviors, and tissue microenvironments, and can be embedded within physiologically based pharmacokinetic (PBPK) models of dosimetry. These methods are maturing into practical biomedical tools through platforms such as CompuCell3D, PhysiCell, Tissue Forge, Morpheus, and CHASTE.
I will introduce this modeling approach and illustrate its application to infection and immune dynamics, including models of SARS-CoV-2 infection, antiviral pharmacokinetics and pharmacodynamics, and the role of spatial and metabolic heterogeneity in shaping therapeutic outcomes. I will also show how these models integrate immune cell recruitment, cytokine dynamics, and tissue damage and repair, yielding predictions that cannot emerge from well-mixed models alone. Looking forward, there are both opportunities and challenges in modeling the immune system and in designing effective control strategies. Scientifically, many aspects of immune recognition remain uncertain, immune responses are highly complex and context dependent, and spatial heterogeneity is central to outcomes.
Clinically, if we want to realize immune digital twins for medical use, we face the impossibility of directly measuring immune state in real time; most data come from serum assays, which mask spatial inhomogeneity within the patient. Moreover, immune states change rapidly and stochastically, while our current therapeutic modulators are relatively coarse and non-specific. Addressing these scientific and translational hurdles will require close collaboration between experimentalists, modelers, and clinicians.
I will conclude by outlining how Duke's new center can play a pivotal role in bridging these gaps, linking advanced experimental platforms with predictive multiscale modeling to move toward patient-specific immune digital twins.
Speaker: James A. Glazier, PhD. Professor of Intelligent Systems Engineering, Professor & Director of Biocomplexity Institute Biophysics, Luddy School of Informatics, Computing, and Engineering
For this hybrid seminar Zoom registration is required. Please register at: https://duke.zoom.us/meeting/register/iVayZ_iyQKOHY9h5fBdxJQ#/
This seminar series is organized by the Multiscale Immune Systems Modeling (MISM) Center of Excellence, funded by NIAID/NIH (U54AI191253).