# Digital pathology for defining myeloid cell-mediated lung injury during acute SARS CoV-2 Infection in hamsters > **NIH NIH R21** · TUFTS UNIVERSITY BOSTON · 2022 · $247,500 ## Abstract Project Summary Macrophages and neutrophils are implicated in SARS CoV-2 pathogenesis in people and non-human primates but their contribution to SARS CoV-2 pathology in the hamster model is poorly defined. We hypothesize that myeloid cells can be targeted therapeutically to improve COVID-19 outcomes and we will explore this in the hamster model of COVID-19 infection. The hamster model is a tractable small animal model for COVID-19 that models severe clinical disease in humans yet, variations in study design, tissue and time-points assessed limit cross-institutional comparison of results and result reproducibility. We propose that quantitative image analysis can be used to effectively monitor immune cell infiltrates and define mechanisms of disease progression in the hamster model, but pathologic correlates of clinical disease need to be established. More broadly, there is a need to standardize quantitative pathologic endpoints in animal models of SARS CoV-2 infection in order to benchmark study quality, improve cross-institutional comparison of data, validate cellular targets, and assess therapeutic efficacy such that potential drugs for SARS CoV-2 can rapidly advance. We will use quantitative image analysis to explore mechanisms of myeloid mediated tissue damage such as antibody dependent enhancement of disease (ADE) and the PI3K inflammatory pathway. Using the Syrian hamster model and digital pathology we will assess the relative contribution of myeloid cell populations to disease pathology in SARS CoV- 2 infection and explore mechanisms of myeloid-mediated lung damage. We will develop image analysis tools to quantify inflammatory infiltrates and define pathologic correlates of clinical disease in the hamster model of SARS CoV-2 infection. We will perform titration studies to establish pathologic endpoints that correlate with clinical disease and viral load to better understand vaccine and therapeutic outcomes in this model. We will also define mechanisms of myeloid-mediated tissue damage in SARS CoV-2 infected hamsters using an optimized image analysis toolset. We will explore subtherapeutic monoclonal Ab (MAb) treatment and non-protective levels of vaccine-induced neutralizing antibodies to establish pathologic metrics for assessing iADE and use a PI3K-γ inhibitor currently in Phase II clinical trials for solid tumors, to determine whether myeloid cell trafficking can be modulated by inhibiting the PI3K-γ pathway. Development of validated and standardized quantitative image analysis end-points that correlate with clinical and virologic control in hamsters will more rapidly advance pre- clinical drug and vaccine efficacy trials for development of SARS CoV-2 therapeutics and preventives. These tools can also be used to explore pathologic mechanisms of disease in COVID-19. 1 ## Key facts - **NIH application ID:** 10348996 - **Project number:** 1R21AI166743-01 - **Recipient organization:** TUFTS UNIVERSITY BOSTON - **Principal Investigator:** Amanda Martinot - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $247,500 - **Award type:** 1 - **Project period:** 2022-09-08 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10348996 ## Citation > US National Institutes of Health, RePORTER application 10348996, Digital pathology for defining myeloid cell-mediated lung injury during acute SARS CoV-2 Infection in hamsters (1R21AI166743-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10348996. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*