IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics Mini Seminars
Aug 12, 2021
Welcome - The meeting will start at 3PM EDT
NOTE: THE MEETING WILL BE RECORDED, STREAMED AND PUBLICLY AVAILABLE�FOR THOSE MEMBERS UNABLE TO ATTEND
Agenda
People
Co-Lead: Reinhard Laubenbacher, PhD
Department of Medicine
Laboratory for Systems Medicine
University of Florida
reinhard.laubenbacher@medicine.ufl.edu
Co-Lead: James A. Glazier, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Web Administration, Slack: James P. Sluka, PhD
Dept. of Intelligent Systems Engineering and Biocomplexity Institute
Indiana University, Bloomington
Activities Coordination: Bruce G. Shapiro, PhD, PMP
Laboratory for Systems Medicine
University of Florida
bruce.shapiro@medicine.ufl.edu
Slack Channel
https://Msm-working-group.slack.com
Our IMAG/MSM Wiki page
https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics Feel free to suggest additional content!
Or, use the Tiny URL: https://tinyurl.com/hkr97vfe
IMAG’s LinkedIn
YouTube “MSM Working Group on Multiscale Modeling” https://www.youtube.com/channel/UCuDFvhgFziRRDcpRnT3vlrw
Announcements
�Any short (~1 minute) items such as;
Schedule for Upcoming Meetings and mini-Seminars
Aug 19:
Aug 26:
Sept 2:
Request for future speakers (Aug 26, …)
Rules of the Meeting
Mini-Seminar�Computational Modeling Reveals the Role of Macrophages�in Respiratory A. fumigatus Infection in�Immunocompromised Hosts
Henrique de Assis
Laboratory for Systems Medicine, University of Florida.
Fungal infections of the respiratory system are a life-threatening complication for immunocompromised patients. Invasive pulmonary aspergillosis, caused by the airborne mold Aspergillus fumigatus, has a mortality rate of up to 50% in this patient population. The lack of neutrophils, a common immunodeficiency caused by, e.g., chemotherapy, disables a mechanism of sequestering iron from the pathogen, an important virulence factor. This paper shows that a key reason why macrophages are unable to control the infection in the absence of neutrophils is the onset of hemorrhaging, as the fungus punctures the alveolar wall. The result is that the fungus gains access to heme-bound iron. At the same time, the macrophage response to the fungus is impaired. We show that these two phenomena together enable the infection to be successful. A key technology used in this work is a novel dynamic computational model used as a virtual laboratory to guide the discovery process.
Mini-Seminar�Generating Multicellular Spatiotemporal Models of Population Dynamics from Ordinary Differential Equations
T.J. Sego
Indiana University
The biophysics of an organism span multiple scales from subcellular to organismal, and include processes characterized by spatial properties, such as the diffusion of molecules, cell migration, and flow of intravenous fluids. While non-spatial, ordinary differential equation (ODE) models are often used and readily calibrated to experimental data, they do not explicitly represent the spatial and stochastic features of a biological system, limiting their insights and applications. However, spatial models describing biological systems with spatial information are mathematically complex and computationally expensive, which limits the ability to calibrate and deploy them, and highlights the need for simpler methods able to model the spatial features of biological systems. This work develops a formal method for deriving cell-based, spatial, multicellular models from ODE models of population dynamics in biological systems, and vice-versa. The method is demonstrated by generating spatiotemporal, multicellular models from ODE models of viral infection and immune response. In these models the determinants of agreement of spatial and non-spatial models are the degree of spatial heterogeneity in viral production and rates of extracellular viral diffusion and decay. These generated spatial models show how ODE model parameters can implicitly represent spatial parameters, and cell-based spatial models can generate uncertain predictions through sensitivity to stochastic cellular events, which is not a feature of ODE models. Using the method, we can test ODE models in a multicellular, spatial context and translate information to and from non-spatial and spatial models, which help to employ spatiotemporal multicellular models using calibrated ODE model parameters. The method may be useful for generating new ODE model terms from spatiotemporal, multicellular models, recasting popular ODE models on a cellular basis, and generating better models for critical applications where spatial and stochastic features affect outcomes.
Requests for Input/Suggestions
We would like the subgroup leads to prepare brief presentations for the Thursday meetings, please let us know when you would like to present
Ideas/help for publicising our Thursday mini-seminars more effectively and for speakers to invite
Suggestions for agenda items and approaches to organizing the Steering Committee Meetings more effectively
There have also been a number of requests for more explicit statements of goals and tasks from the WG leadership, we would appreciate your suggestions
Please contact Reinhard Laubenbacher, James Glazier, James Sluka or Bruce Shapiro with your ideas on all of these issues
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Have you made new research contacts or collaborations based on the Viral Pandemics working group?
Additional Business
We ask that everyone sign up for subgroups using the Google Form at
https://forms.gle/Vf6RtapTeXfXLBaq6
People are welcome to post tools and software to IMAG/MSM website, but be careful to be clear that a posting does not include endorsement by NIH
Please register on IMAG/MSM web site https://www.imagwiki.nibib.nih.gov/index.php/�(Details are on the next slide)
Charge to subgroups�(review):
Deliverable: White paper on the subgroup focus areas.�Due date: February 26, 2021
Steps to be taken:
Should be added to the subgroup’s Wiki page
IMAG/MSM Wiki Pages
The Viral Pandemics WG has an IMAG/MSM Wiki page at:�https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics
In addition, each subgroup can have their own WIki page.
IMAG/MSM Wiki Pages
We ask that:
To register for the MSM�(Multiscale Modeling Consortium):
“Multiscale Modeling and Viral Pandemics”
If you have any problems please contact JSluka@iu.edu
Current Subgroup Updates
Subgroup Roll Call and Feedback
Subgroup leads quick check in (subgroup list on next slides):
Subgroups 1 of 2�(28 total subgroups)
Leads Names
Physiological Models
[Innate and Adaptive Immune Response] J Shoemaker, R Datta, V Zarnitsyna, E Schwartz
[Host-pathogen Interactions] Y Liu, J Thakar, W Garira
[Tissue Damage and Recovery] Y Jiang, K Ye
Virus Models
[Viral Transport and Modes of Entry and Barrier Functions] MG Forest
[Viral Replication and Release] J Faeder, P Rangamani, EY Kim
[Viral Evolution] F Adler, A Zilman
Therapeutics and Medicine
[Drug Development] R Stratford
[Vaccine Development] K Ye, E Schwartz
[Modeling individual responses to disease and treatment] G An, E Schwartz, T Mapder
[Modelling Decontamination of Surfaces/Materials] K Kiradjiev
[Machine Learning for Health Monitoring] G Lin, Y Jiang
Individual Organ Systems
[Lungs] Y Jiang
[Heart],[Vasculature] C Lynch
[Kidney and Liver] M Rafailovich, C Mazza, C Mahapatra, C Yedjou
[Comorbidities] J Barhak, G Gonzalez-Parra
Subgroups 2 of 2
Data
[Experimental and Clinical Data for Model Construction and Validation] S Schnell
[AI-based Data Processing, Heterogeneous Data Fusion] O Gevaert, Y Kevrekidis
[Infection in experimental models including Relationship between in vivo � and in vitro responses and Infection in vivo model organisms] tbd
[Infection in zoonotic reservoir animals and Interspecies Transmission] G An, J Rice, T Mapder
[Coinfection and/or other pathogens] H. Dobrovolny
[Emerging and Reemerging Diseases] A Gumel
Modeling Technology
[Aerosol Transport in Lung, Lymph and Blood] M Tawhai, C Darquenne
[Integration] ** J Barhak, R Bowness, Y Liu, R Thompson
[Knowledge Acquisition and Modeling] SMR Naqvi, J Thakar
[Crowd-sourcing Models] R Laubenbacher, P Macklin
[Model Standards, Credibility, and Annotation] J Barhak, R Sheriff
�Social Issues
[Dissemination, training and outreach to the public, � research community and Liaisons] T Helikar, B Madamanchi, J Rice
[Health Equity] *** B Madamanchi
[Dissemination and Communication to funding agencies] J Glazier, R Laubenbacher
** Merged two groups – � [Integration Within and Across Scales and challenges]
[Integration Between Within-host and Population Scales]
*** Merged
Please Sign Up For Subgroups!
Subgroup Sign up
We ask that everyone sign up for subgroups using the Google Form at:
https://forms.gle/Vf6RtapTeXfXLBaq6
�The form allows you to join a group and volunteer to lead. If you think subgroups overlap, feel free to sign up for multiple groups. We will likely combine some of the groups based on the number of participants and the number of people common across related groups.
Discussion of Recruitment of Subgroup Leads, Subgroup Members and WG Members
Procedure for the establishment of new subgroups:
New subgroup proposals should include a brief description of the focus, at least one person who has agreed to lead the subgroup, and a rationale why the proposed subgroup focus is not covered by already existing subgroups.
Review of Web Site and Contents
https://www.imagwiki.nibib.nih.gov/working-groups/multiscale-modeling-and-viral-pandemics
We can add linked pages for each subgroup.