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We extend our established agent-based multiscale computational model of infection of lung tissue by SARS-CoV-2 to include pharmacokinetic and pharmacodynamic models of remdesivir. We model remdesivir treatment for COVID-19; however, our methods are general to other viral infections and antiviral therapies. We investigate the effects of drug potency, drug dosing frequency, treatment initiation delay, antiviral half-life, and variability in cellular uptake and metabolism of remdesivir and its active metabolite on treatment outcomes in a simulated patch of infected epithelial tissue. Non-spatial deterministic population models which treat all cells of a given class as identical can clarify how treatment dosage and timing influence treatment efficacy. However, they do not reveal how cell-to-cell variability affects treatment outcomes. Our simulations suggest that for a given treatment regime, including cell-to-cell variation in drug uptake, permeability and metabolism increase the likelihood of uncontrolled infection as the cells with the lowest internal levels of antiviral act as super-spreaders within the tissue. The model predicts substantial variability in infection outcomes between similar tissue patches for different treatment options. In models with cellular metabolic variability, antiviral doses have to be increased significantly (>50% depending on simulation parameters) to achieve the same treatment results as with the homogeneous cellular metabolism.
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Inverse Modeling Approach for Fetal Oxygen Saturation Estimation with Spatial Intensity
Non-invasive fetal saturation prediction is challenging. We propose a multi-detector, inverse modeling, ML based approach. Trained on a large simulated simple tissue model dataset, our generalized NN can estimate simulation parameters given the simulation results. Our model achieves a 9.2% overall validation MSE for tissue model parameters.
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- Award ID(s):
- 1838939
- PAR ID:
- 10566455
- Publisher / Repository:
- Optica Publishing Group
- Date Published:
- ISBN:
- 978-1-957171-34-0
- Page Range / eLocation ID:
- JS4A.1
- Format(s):
- Medium: X
- Location:
- Fort Lauderdale, Florida
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1364/TRANSLATIONAL.2024.JS4A.1
