# Ultra-High Resolution Gas Phase Separation and Analysis Platform for Metabolomics

> **NIH NIH R01** · BATTELLE PACIFIC NORTHWEST LABORATORIES · 2022 · $637,313

## Abstract

PROJECT SUMMARY/ABSTRACT
Metabolomics is increasingly utilized and essential to biomedical research, with broad applications
extending to the clinic. This potential is inhibited by the limitations of current platforms that are largely
based upon either the combination of chromatography separations with mass spectrometry (MS) or
by MS alone. The objective of this project is to develop a new ultra-high resolution and ultra-sensitive
platform that will enable much higher quality and more comprehensive metabolomics measurements
than previously feasible and to do so with significant gains in measurement throughput. The key
developments will involve the implementation of greatly improved ion mobility (IM) separations
providing much greater resolution, higher speed, broader applicability to metabolite chemical classes,
and improved sensitivity and measurement dynamic range in conjunction with mass spectrometry
(MS). The new IM-MS platform development efforts will include the essential platform control and
data acquisition capabilities and result in a platform ready for initial metabolomics applications, as
well as a foundation for its rapid dissemination.

## Key facts

- **NIH application ID:** 10350669
- **Project number:** 5R01GM130709-04
- **Recipient organization:** BATTELLE PACIFIC NORTHWEST LABORATORIES
- **Principal Investigator:** Yehia Ibrahim
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $637,313
- **Award type:** 5
- **Project period:** 2019-03-01 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10350669

## Citation

> US National Institutes of Health, RePORTER application 10350669, Ultra-High Resolution Gas Phase Separation and Analysis Platform for Metabolomics (5R01GM130709-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10350669. Licensed CC0.

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