The NIMML Creates the First High-Resolution Agent-Based Model of the Gut

The immune system is a complex massively and dynamically interacting network with trillions of interactions between host cells, molecules and microbes. Studying the human immune system is like trying to work a vast, multidimensional jigsaw puzzle with pieces that are constantly changing shape. The Nutritional Immunology and Molecular Medicine Laboratory (NIMML) is applying advanced computational systems to study the gut immune system as a large-scale information processing representations to predict new emerging behaviors. The immune system is a highly complex and dynamic system that encompasses hierarchical interactions between cells and molecules leading to emergent behaviors with dimensions ranging from nanometers to meters, and time scales from nanoseconds to years.

Agent based modeling (ABM) is a class of computational models for simulating the actions, interactions and mechanisms of autonomous agents with a view to assessing their effects on the system as a whole. ABM have been used extensively in biology, including the analysis of epidemics, biowarfare, and systems biology. The NIMML has developed the first ABM of the gut and uses an array of high-performance computing (HPC)-driven advanced computational technologies such as the ENteric Immunity SImulator (ENISI) - multiscale modeling (MSM) to solve infectious diseases and autoimmune disease challenges. The NIMML pioneers applying advanced modeling approaches to solve the complex puzzle of immunity. NIMML’s modeling infrastructure enables the study of immune system by simulating cell phenotype changes, signaling pathways, immune responses, lesion formation, cytokine/chemokine diffusions and cell movements at the gut mucosa.

ENISI MSM is at the forefront of advanced computational modeling and simulation of biological systems. This multiscale modeling tool integrates the ABM with other modeling technologies including differential equations (DE) based methods such as ODE and PDE. It further enables the study of immune system at an unprecedented scale and speed by simulating immune responses with trillions of interacting components at the gut mucosa, and integrating spatiotemporal scales spanning from nanoseconds to years, from molecules to cells, and into clinical cohorts.

“NIMML’s advanced computational modeling platform is unprecedented in its ability to predict how to an immune system behaves during the course of infection,” said Dr. Josep Bassaganya-Riera, the Director of NIMML. “The ENISI MSM is able to achieve an unprecedented scalability of up to 1012 agents and is an important step towards building large-scale information processing representations of host responses to biological, radiation, or chemical threats. NIMML is working closely with DTRA to build generalizable advanced computational models that can be applied in the field to improve military readiness.”

NIMML’s advanced computational modeling capabilities include the involvement of various cell types across varying dynamic patterns in gut immune responses. The modular architecture of the ABM, ODE, PDE modeling platform can facilitate the modeling of therapeutic interventions or modeling the impact of biological or chemical threats. The integration of the hybrid model with advanced machine learning algorithms and data from electronic health records pioneered by NIMML have enabled smart simulations of human clinical trials that accelerated the development of innovative therapeutics with the potential to disrupt current treatment paradigms.


The NIMML tackles unsolved fundamental challenges in complex human diseases with unmet clinical needs. The NIMML combines advanced computational technologies such as computer modeling and artificial intelligence with pre-clinical and clinical experimentation to catalyze the translation of scientific discoveries into creative solutions to the most challenging problems in healthcare. NIMML is located in Blacksburg, VA.

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ENISI MSM Models Trillions of Immune Cells and Molecules in the Gut Mucosa

NIMML Contact:

Josep Bassaganya-Riera