Amber M. Smith

This paper introduces TM-RWFS, a method to generate heterogeneity in mechanistic models by constraining trajectories between data bounds, showing it efficiently reproduces biological variability.

This study uses virtual patient cohorts to model immune response differences in cancer and immunosuppressed COVID-19 patients, identifying key immune dysregulation factors.

The paper models viral-viral coinfections to show how interactions between viruses affect disease severity and clearance rates in different infection scenarios.

This study links influenza virus infection kinetics to lung injury, inflammation, and disease severity using a model-experiment framework.

Open-source agent-based PhysiCell model of SARS-CoV-2 infection in lung epithelium; version 5 clears virus in about 6 days in simulation, and delayed T cell arrival increases epithelial loss.

The paper develops a new mathematical model to capture biphasic viral decay in influenza A virus infections, revealing that viral clearance rates change with infected cell density.