# Personalized Therapies of Pediatric Sepsis

> **NIH AI K23** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2026 · $185,573

## Abstract

PROJECT ABSTRACT
Sepsis is a life-threatening condition characterized by a dysregulated response to infection, leading to
significant organ dysfunction and affecting 75,000 children and one million adults each year. The estimated
yearly impact of this disease is 200,000 lives lost and $20 billion dollars in healthcare expenditures.
Unfortunately, many initially promising sepsis therapeutics have failed to show wide benefit with tested in wider
clinical trials. However, post-hoc analyses of some of these therapeutics demonstrate benefit to specific
subgroups, raising concern that failure of sepsis therapeutics have failed due to the one-size-fits-all approach
employed in clinical trials. It is now widely accepted that sepsis represents a heterogeneous group, likely with
subtypes that are expected to respond differently to various treatments. Multiple efforts have been made to
characterize this heterogeneity, though few of these have been in pediatric patients. Moreover, phenotyping
efforts have typically relied on point measurements in time, including for vital signs. However, the ICU provides
a wealth of continuously measured vital sign data, including high-frequency physiologic data, that may offer
insights into underlying physiologic derangements and augment sepsis subtypes. Moreover, this type of data
may provide evidence in real time of developing infections prior to the onset of more classic signs such as
fever. Such insights have already been demonstrated in neonatal patients. The overarching goal of this study is
to develop personalized sepsis therapeutics by developing predictive tools based on integrating high-frequency
physiologic data with electronic health record data. Aim 1 focuses on augmenting sepsis phenotypes through
the inclusion of high-frequency data. This data is expected to identify additional subtypes or aid in prediction of
disease progression after day 1. Aim 2 aims to first retrospectively identify signs of bloodstream infection (BSI)
prior

## Key facts

- **NIH application ID:** 11266232
- **Project number:** 5K23AI190128-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Zachary  Aldewereld
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** AI
- **Fiscal year:** 2026
- **Award amount:** $185,573
- **Award type:** 5
- **Project period:** 2025-02-01T00:00:00 → 2030-01-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11266232

## Citation

> US National Institutes of Health, RePORTER application 11266232, Personalized Therapies of Pediatric Sepsis (5K23AI190128-02). Retrieved via AI Analytics 2026-05-17 from https://api.ai-analytics.org/grant/nih/11266232. Licensed CC0.

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