# Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center

> **NIH NIH U19** · NORTHWESTERN UNIVERSITY · 2024 · $2,402,774

## Abstract

PROJECT SUMMARY/ABSTRACT – Overall
Pneumonia, including both community-acquired pneumonia (CAP) and hospital-acquired/ventilator-associated
pneumonia (HAP/VAP), causes almost 80% of deaths from infections in the US. As evidenced by the ongoing
COVID-19 pandemic, severe pneumonia represents an important cause of morbidity and mortality. Our U19
Systems Biology Center, Successful Clinical Response In Pneumonia Therapy (SCRIPT), which we rename
Super-SCRIPT (SCRIPT2) for this renewal, leverages bronchoalveolar lavage (BAL), nasal curettage, and blood
sampling paired with cutting-edge multi-omics technologies—including multiparameter flow cytometry, single-
cell RNA-sequencing, deep pathogen sequencing, DNA metagenomics, and deep clinical phenotyping—to
develop models of pneumonia pathogenesis. In SCRIPT, we generated a detailed systems biology model of
SARS-CoV-2 pathobiology that supported a novel therapy for severe SARS-CoV-2 pneumonia that was
efficacious in a phase II clinical trial. In SCRIPT2, we will determine whether models generated using high-
dimension longitudinal data describing the host response, pathogen, microbiome, and clinical phenome in
patients with severe CAP (Project 1) and HAP/VAP (Project 2) can predict favorable or unfavorable clinical
transitions over the course of a pneumonia episode. We test the hypothesis that multi-omics inputs will
create actionable models that identify favorable and unfavorable clinical transitions/outcomes for both
severe CAP and severe HAP/VAP.
Aim 1/Project 1. To generate actionable models to improve the clinical course of patients with severe
CAP using multi-omics analysis of longitudinal samples from the distal lung and nasopharynx.
Aim 2/Project 2. To generate actionable models to improve the clinical course of patients with severe
HAP/VAP using a multi-omics analysis of longitudinal samples from the distal lung.
Three scientific cores support the projects. The Technology Core developed cutting edge multi-omics
approaches for the analysis of bronchoalveolar lavage samples collected as part of clinical care. The Data
Management and Bioinformatics Core weaves together clinical data extracted from our own EHR and those from
other centers. The Modeling Core works seamlessly with the Projects and Cores to integrate, validate and
iteratively improve latent space models of disease. Clinician scholars who provide direct care to patients with
pneumonia lead or contribute to each project and core, enhancing the translational impact of our findings.

## Key facts

- **NIH application ID:** 10757318
- **Project number:** 5U19AI135964-07
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** RICHARD G WUNDERINK
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,402,774
- **Award type:** 5
- **Project period:** 2018-01-17 → 2027-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10757318

## Citation

> US National Institutes of Health, RePORTER application 10757318, Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center (5U19AI135964-07). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10757318. Licensed CC0.

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