# Preclinical development of a synthetic lung surfactant dry powder aerosol for hypoxemia or acute respiratory distress syndrome patients receiving different modes of ventilation support

> **NIH NIH R01** · VIRGINIA COMMONWEALTH UNIVERSITY · 2024 · $733,241

## Abstract

Hypoxemia and acute respiratory distress syndrome (ARDS) arising from direct lung injury are associated
with a dysfunctional lung surfactant system; however, large clinical trials of surfactant replacement therapy have
been unsuccessful in this population. The method employed for surfactant delivery in these unsuccessful trials
was liquid bolus instillation, which often requires intubation, use of large liquid volumes (~500 ml) and subsequent
mechanical ventilation often late in the progression of ARDS. A successful dry powder aerosol synthetic lung
surfactant product would provide the advantages of early surfactant administration, potentially before the need
for invasive mechanical ventilation (IMV), rapid and high dose delivery to the alveolar region, and improved
efficacy compared with instillation based on preliminary animal model findings.
 The goal of this study is the preclinical development of a synthetic lung surfactant dry powder aerosol product
(including delivery strategies, formulations and devices) for administration to adults experiencing hypoxemia or
ARDS from direct lung injury in a rapid, efficient and safe manner while receiving different modes of ventilation
support. Aerosol delivery strategies and devices will be developed and optimized for high efficiency aerosol
administration during high flow nasal cannula (HFNC) therapy, noninvasive positive pressure ventilation (NPPV)
and IMV. High efficiency aerosol administration will be enabled by a combination of a highly dispersible spray-
dried powder formulation, a new positive-pressure dry powder inhaler (DPI), and an excipient enhanced growth
(EEG) aerosol delivery strategy. Aerosolization performance and lung delivery efficiency will be established and
optimized using a concurrent approach of realistic in vitro experiments and computational fluid dynamics (CFD)
modeling. Animal experiments (in rats) will be implemented to determine appropriate levels of the surfactant
protein analog and assess in vivo efficacy of the lead synthetic surfactant dry powder formulation in different
models of direct lung injury. Specific aims of the project are as follows:
Specific Aim 1. Develop a synthetic surfactant dry powder aerosol formulation that can be easily dispersed into
a small particle aerosol with low air volume, exhibit hygroscopic growth, and enable stable product storage.
Specific Aim 2. Develop and optimize surfactant delivery strategies and devices that enable safe, efficient and
rapid aerosol administration to adults receiving HFNC, NPPV or IMV.
Specific Aim 3. Test the efficacy of the lead synthetic surfactant formulations administered with an animal-
version of the air-jet DPI using in vivo rat models of acute lung injury (ALI) mimicking bacterial infection, viral
infection, and ventilator-induced lung injury.
Outcomes and Impact. The proposed advances directly address multiple previous failure mechanisms related
to instilled and aerosolized (liquid and powder) surfactants and...

## Key facts

- **NIH application ID:** 10863857
- **Project number:** 5R01HL164508-02
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** P. Worth Longest
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $733,241
- **Award type:** 5
- **Project period:** 2023-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10863857

## Citation

> US National Institutes of Health, RePORTER application 10863857, Preclinical development of a synthetic lung surfactant dry powder aerosol for hypoxemia or acute respiratory distress syndrome patients receiving different modes of ventilation support (5R01HL164508-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10863857. Licensed CC0.

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