# Modeling Core

> **NIH AI U19** · NORTHWESTERN UNIVERSITY · 2026 · $344,151

## Abstract

Project Summary/Abstract – Modeling Core
The Modeling Core, as part of SCRIPT, aimed to apply machine learning approaches to clinical and -omics data
generated by the SCRIPT projects and cores to develop a models of severe pneumonia and identify novel
biomarkers and therapeutic targets. Using an iterative systems biology approach, we generated a detailed
model, published in Nature, of how severe SARS-CoV-2 pneumonia, in contrast with severe pneumonia due to
other pathogens, possesses a peculiar host response pathobiology that explains its propensity to cause
prolonged critical illness. Importantly, SCRIPT’s model predicted the efficacy of an experimental pharmacologic
intervention in SARS-CoV-2 pneumonia – the CRAC channel inhibitor Auxora. In this renewal, Super-SCRIPT
(SCRIPT2) will continue to leverage serial sampling of biological materials (bronchoalveolar lavage fluid, nasal
epithelium, blood) paired with cutting-edge multi-omics technologies and deep clinical phenotyping to develop
models of pneumonia pathogenesis which could augment clinical decision making. We used clinical and -omics
data collected and generated during the first cycle of this award to generate preliminary data for the renewal. We
discretized time in the ICU and related physiological measures on a per-day basis, similar to how physicians
view and treat patients with severe pneumonia in the ICU. Our novel approach overcomes a critical limitation in
the application of machine learning approaches to clinical data, which often do not take into account interventions
that can change the course of the disease and typically focus only on clinical state at presentation and ultimate
outcome, analogous to drawing a line between two points. We generated a low-dimensional interpretable latent
space model of clinical states in patients with severe pneumonia. We show that transitions between these clinical
states are different in patients with SARS-CoV-2 pneumonia and other types of pneumonia. By projecti

## Key facts

- **NIH application ID:** 11248060
- **Project number:** 5U19AI135964-09
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** LUIS A. Nunes AMARAL
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** AI
- **Fiscal year:** 2026
- **Award amount:** $344,151
- **Award type:** 5
- **Project period:** 2018-01-17T00:00:00 → 2027-12-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11248060

## Citation

> US National Institutes of Health, RePORTER application 11248060, Modeling Core (5U19AI135964-09). Retrieved via AI Analytics 2026-05-16 from https://api.ai-analytics.org/grant/nih/11248060. Licensed CC0.

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