Pandemic community-acquired pneumonia (CAP) caused by SARS-CoV-2 highlighted CAP’s public health impact. In SCRIPT, we established a comprehensive research infrastructure, collecting over 1,500 serial respiratory samples from 595 patients with severe CAP and hospital-acquired pneumonia (HAP). Using advanced multi-omics analyses, we developed a systems model of SARS-CoV-2 pathogenesis, leading to a successful clinical trial of Auxora, which reduced 30-day mortality by 53% in phase II trials.
Project 1 aims to refine this approach by leveraging longitudinal clinical and molecular data. Machine learning models will identify clinical states and molecular predictors associated with favorable or unfavorable transitions during CAP episodes. Single-cell RNA sequencing, cytokine, proteomic, and microbiome analyses will inform these models. We will identify clinical predictors, genomic determinants, and therapeutic pathways, ultimately driving actionable insights and novel therapies for severe CAP.
A model to explain the unique pathobiology of severe SARS-CoV-2 CAP generated from SCRIPT