# CVM Vet-LIRN Veterinary Laboratory Diagnostic Program (U18)

> **NIH FDA U18** · VIRGINIA POLYTECHNIC INST AND ST UNIV · 2024 · $32,000

## Abstract

Project Abstract
Virginia Tech Animal Laboratory Services (ViTALS) at the Virginia-Maryland College of Veterinary
Medicine (VMCVM) has been a member of the FDA CVM Vet-LIRN laboratory network since 2012. With
previous infrastructure funding, ViTALS was able to conduct staff training and expansion of the
molecular diagnostics section to comply with the American Association of Veterinary Laboratory
Diagnosticians (AAVLD) requirements for accreditation. ViTALS was granted accreditation in 2017. The
expertise of the faculty and staff along with the highly organized and well established facility have
served as an integral component of the network. ViTALS encompasses six units including anatomic
pathology, clinical pathology, clinical microbiology, molecular diagnostics, clinical immunology, and
clinical parasitology. ViTALS has experience and expertise in running GLP studies and is capable of
providing technical skill and support for ongoing surveillance or outbreak testing. In addition, ViTALS has
expertise in deep sequencing, in particular long read technologies, which have been employed for
bacterial, viral and parasitic whole genome sequencing as well as pathogen discovery with shotgun
metagenomics.

## Key facts

- **NIH application ID:** 10845277
- **Project number:** 5U18FD006159-08
- **Recipient organization:** VIRGINIA POLYTECHNIC INST AND ST UNIV
- **Principal Investigator:** KEVIN K LAHMERS
- **Activity code:** U18 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2024
- **Award amount:** $32,000
- **Award type:** 5
- **Project period:** 2017-08-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10845277

## Citation

> US National Institutes of Health, RePORTER application 10845277, CVM Vet-LIRN Veterinary Laboratory Diagnostic Program (U18) (5U18FD006159-08). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10845277. Licensed CC0.

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