Automated sample prep for faster plasma and feed analysis in targeted LC-MS/MS
Official title: Scalable Plasma and Feed Sample Preparation Workflows Using Automated Liquid Handling for Targeted LC-MS/MS Testing
Funded at Kansas State University · NIH-11529018 · Data updated 2026-11-12
This grant aims to speed up lab workflows by using automated liquid handling to prepare plasma and feed samples for targeted LC-MS/MS testing, helping labs process more tests with less variability.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Kansas State University NIH-funded |
| Lab location | 1 site (Manhattan, United States) |
| Project start | September 1, 2026 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $74,565 |
| NIH project number | 1U18FD008939-01 |
| Project ID | NIH-11529018 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients whose samples would be analyzed using LC-MS/MS for targeted antibiotic or related compound monitoring in plasma or feed matrices.
✕Less likely to help
Patients whose testing needs fall outside automated LC-MS/MS workflows or who are not involved in such diagnostic pipelines may not directly benefit.
What this research studies
In this project, automated liquid handling will replace time-consuming manual steps like adding internal standards, dilution, and aliquoting to improve consistency and throughput. The work starts with plasma samples analyzing tetracycline to establish reliable automated workflows, then expands to feed matrices to tackle more complex real-world samples. The team will compare reproducibility and batch sizes between manual and automated methods and collect performance data under controlled conditions before applying them to regulatory investigations. The outcome should demonstrate clearer, faster turnaround times in diagnostic settings without sacrificing accuracy.
Why it matters
Potential benefit: If successful, clinicians and regulators could receive faster, more consistent test results from LC-MS/MS analyses.
How similar studies have gone: Previous work shows automated sample preparation can improve consistency and throughput in analytical labs, supporting potential benefits in clinical diagnostics.
Where this research is happening
-
Kansas State University
Manhattan, United States Active
Researchers
- Principal investigator: Fritz, Scott — Kansas State University
- Study coordinator: Fritz, Scott
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.