# Establish and Characterize an Air Liquid Interface In Vitro Exposure System

> **NIH NIH N01** · BATTELLE MEMORIAL INSTITU · 2021 · $1,397,365

## Abstract

The Division of the National Toxicology Program (DNTP) decided to procure a Vitrocell 48 2.0 plus exposure system to provide the program with in vitro capabilities that mimic inhalation exposure. The inhalation route of exposure is commonly seen among air pollutants as well as with industrial settings, and until recently has been very difficult to simulate in vitro. The procurement of this system will allow in vitro testing of potential toxicants for inhalation exposure which contributes to the program's goals of reducing the use of animals. This system provides high throughput and can be used for airborne substances such as vapors, complex mixtures of liquid aerosol, dry powders, and fibers. DNTP is conducting additional evaluation of the system to increase confidence that the system will function as intended. This will be achieved through the design and conduct of system characterization and pilot in vitro toxicity testing of selected test agents with robust in vivo data for correlation, using tissue from representative human populations. The system also allows testing of cells from humans and rats to provide data supporting species extrapolation.
Keyword: in vitro, inhalation exposure

## Key facts

- **NIH application ID:** 10486372
- **Project number:** 273201400015C-P00020-9999-29
- **Recipient organization:** BATTELLE MEMORIAL INSTITU
- **Principal Investigator:** Barney Sparrow
- **Activity code:** N01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,397,365
- **Award type:** —
- **Project period:** 2014-04-15 → 2022-04-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10486372

## Citation

> US National Institutes of Health, RePORTER application 10486372, Establish and Characterize an Air Liquid Interface In Vitro Exposure System (273201400015C-P00020-9999-29). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10486372. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*