Multi-cellular and multi-scale systems modeling to understand the dynamics of the human immune system in interdisciplinary applications
Project Number5R35GM119770-09
Former Number3R35GM119770-04
Contact PI/Project LeaderHELIKAR, TOMAS
Awardee OrganizationUNIVERSITY OF NEBRASKA LINCOLN
Description
Abstract Text
PROJECT SUMMARY/ABSTRACT
The immune system is arguably the second most complex human system after the brain. Its
proper response to foreign stimuli is governed by network-like interactions among various types
of cells and cytokines as their communication mediators. The complexity at the inter-cellular
level of the immune system is further exacerbated by the similarly complex biological and
biochemical networks within each cell (metabolism, gene regulation, etc.) responsible for the
dynamics and decision-making at the single-cell level. Such multiscale complexity makes it
incredibly challenging to understand the complete etiology and pathology of
immune-system-related diseases. My research program aims to identify how the immune
system can be rewired en masse to elicit higher-order decision-making while still enabling the
system to remain otherwise “healthy.” To this end, my research program is leveraging a highly
interdisciplinary research team (computational and experimental immunologists, software
engineers, and education researchers) and collaborators to build a Virtual Immune System -- a
multi-scale, multi-approach computational framework to understand better the complex
dynamical nature of the immune system, identify more accurate multi-dimensional biomarkers,
and identify safe and effective treatments within a reasonable time and cost. In the next five
years, in addition to expanding the Virtual Immune system, my program will continue to develop
methods and technologies for data-driven model construction, visualization, computation,
real-time simulations, and reproducibility to advance multi-scale modeling of the immune system
and beyond. We will continue to decipher the dynamics of the immune system under various
pathologies and the re-programmability of CD4+ T cells under the milieu of their
microenvironments. My laboratory will continue to iteratively predict, validate, and refine
predictions generated using the systems approaches and technologies. To do this, we will
generate our multi-omics data to more precisely validate immune system behaviors and apply
our findings to refine the computational approaches directly. My team will continue to build
collaborations and deepen our existing relationships, including with translational partners to
advance the impact of our systems work on drug discovery, the international team modeling
COVID-19, and with virologists and immunologists to further validate our computational
predictions experimentally.
Public Health Relevance Statement
NARRATIVE
The proper response of the immune system to pathogens is governed by complex, network-like
interactions among various types of cells and their associated communication mediators.
Computational systems modeling provides the ability to describe and interrogate the dynamics
of these complex systems with the objective to identify and design more sophisticated and
effective drug therapies. This funding will enable us to continue to develop a “Virtual Immune
System” -- a multi-cellular and multi-scale model of the human immune system -- to study the
properties of the immune system, investigate immune-related diseases, and make predictive
modeling software technologies more accessible to the broad scientific community (including
immunologists, computational biologists, and translational researchers).
No Sub Projects information available for 5R35GM119770-09
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