# Modular design of multiscale models, with an application to the innate immune response to fungal respiratory pathogens

> **NIH NIH U01** · UNIVERSITY OF FLORIDA · 2020 · $800,977

## Abstract

PROJECT SUMMARY
Increased availability of biomedical data sets across spatial and temporal scales makes it possible to calibrate
complex models that capture integrated processes from the molecular to the whole organism level. This
complexity poses multiple challenges related to mathematical modeling, software design, validation,
reproducibility, and extensibility. Visualization of model features and dynamics is a key factor in the usability of
models by domain experts, such as experimental biologists and clinicians. The proposed project addresses
these challenges in the context of the immune response to an important respiratory fungal infection. Its goal is
to develop a novel modular approach to model architecture, using a recently introduced technology of
lightweight virtual machines and our user-friendly open-source platform for the construction and linking of these
so-called “Docker containers” to create complex modular models in a transparent fashion. A key benefit of
software containers is that they can encompass the entire computational environment of a model, enabling
unprecedented reproducibility of computational results. The overarching computational goal is to develop a
novel approach to the modular design of multiscale models. While broadly applicable, this novel computational
modeling approach will be focused on the development of a multiscale model capturing the early stages of
invasive aspergillosis, an important health problem.
 Invasive aspergillosis is one of the most common fungal infections in immunocompromised hosts and
carries a poor prognosis. The spores of the causative organism, Aspergillus fumigatus, are ubiquitously
distributed in the environment. Healthy hosts clear the inhaled spores without developing disease, but
individuals with impaired immunity are susceptible to a life-threatening respiratory infection that can then
disseminate to other organs. The increasing use of immunosuppressive therapies in transplantation and
cancer has dramatically increased suffering and death from this infection, and this trend is expected to
continue. Current therapeutic approaches have been focused primarily on the pathogen, but a better
understanding of the components of host defense in this infection may lead to the development of new
treatments. In particular, restricting iron availability is a critical mechanism of antimicrobial host defense;
conversely, successful pathogens have evolved potent mechanisms for scavenging iron from the host. These
mechanisms have the potential to be harnessed therapeutically. The biological focus of the proposed project is
the battle over iron between the fungus and the host. The overarching biomedical goal is to develop a
simulation tool to explore the role of iron in invasive aspergillosis across biochemical and biophysical
conditions.

## Key facts

- **NIH application ID:** 10007822
- **Project number:** 5U01EB024501-05
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** REINHARD LAUBENBACHER
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $800,977
- **Award type:** 5
- **Project period:** 2017-09-20 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10007822

## Citation

> US National Institutes of Health, RePORTER application 10007822, Modular design of multiscale models, with an application to the innate immune response to fungal respiratory pathogens (5U01EB024501-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10007822. Licensed CC0.

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