Multiscale Lung Tissue Simulator for Sars-Cov-2 Infection and Damage
- Type: Conference Presentation
- Conference Type: AIChE Annual Meeting
- Presentation Date: November 18, 2020
- Duration: 16 minutes
- Skill Level: Intermediate
- PDHs: 0.30
We are developing an open-source, multi-scale tissue simulator that can be used to investigate mechanisms of intracellular viral replication, infection of epithelial cells, host immune response, and tissue damage. The aim of this project is to concentrate community modeling efforts to create a comprehensive multiscale simulation framework that can subsequently be calibrated, validated, and used to rapidly explore and optimize therapeutic interventions for COVID-19. Once the prototype has been completed (after several design iterations), this coalition will transition to maintain and support the simulation and data collection/curation framework and aggregate calibrated/validated parameter values. To address the acute need for rapid access to an actionable model, we are using a community-driven coalition and best open science practices to build and iteratively refine the model.
Multiple chemical engineers are in the SARS-CoV-2 Tissue Simulation Coalition. Even from the first prototype version, the model applies chemical engineering fundamentals to systemically analyze dynamic interactions between processes involved in SARS-CoV-2 infection and damage. Chemical reactions, enzyme kinetics, and molecular binding interactions are simulated for viral and host cellular processes. Transport phenomena including extracellular diffusion of secreted chemicals and cell endocytosis and exocytosis of viral materials are explicitly included in the current version. In future versions, we plan to consider convection of aerosol droplets laden with virus throughout the lungs, penetration of the virus through the mucus lining the airways, signaling to systemic host responses, and distribution of systemic immune responses into local tissues. Core concepts in mass and population balances, numerical methods, and mathematical modeling with ordinary and partial differential equations are also used throughout the project. Stochastic and multiscale modeling approaches are also incorporated to address challenges at different length and times scales and to allow for uncertainty and biological variations. This is not simply a theoretical and computational study. Experimental and clinical collaborators who are setting up for animal and cell culture experiments in April 2020 are also part of the Coalition. It is anticipated that these data as they become available will be incorporated into multiple versions of the model before the AIChE Annual Meeting.
- Heiland, R.; Macklin, P. PhysiCell model for COVID19. https://nanohub.org/tools/pc4covid19
- Wang, Y. N.; Heiland, R.; Craig, M.; Davis, C.; Ford Versypt, A. N.; Jenner, A.; Ozik, J.; Collier, N.; Cockrell, C.; Becker, A.; An, G.; Glazier, J. A.; Narayanan, A.; Smith, A. M.; Macklin, P. bioRxiv 2020, 2020.04.02.019075, https://doi.org/10.1101/2020.04.02.019075.
|AIChE Member Credits||0.5|
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|