# ASEHL Admin Core

> **NIH FDA U19** · ALASKA STATE DEPT/ENVIRONMTL CONSERVATN · 2020 · $97,167

## Abstract

ASEHL Project Summary-Admin SFY21-25 
The Alaska State Environmental Health Laboratory (ASEHL) has sufficient personnel, 
experience, and authority to manage activities to complete these projects. The 
administrative documentation and actions include: supervisory, resource management, 
expenditure and procurement approval, coding instruction for personnel time, workload 
prioritization, general coordination, routine IT support, financial review, administrative 
reports, coordination with sampling agency, in-state travel approvals, and attendance at 
required and facultative meetings and conferences. This includes quarterly reports, mid- 
year progress report, and RPPR. 
By maintaining and enhancing ISO/IEC 17025 for food testing, the Alaska State 
Environmental Health Laboratory (ASEHL) will continue to deliver both scientifically valid 
and legally defensible data to its clients. The clients, including the Alaska Food Safety 
and Sanitation (FSS) Program and U.S. FDA, will benefit by receiving enhanced 
customer service, consistent turnaround times, and little to no down time. Accreditation 
allows ASEHL to satisfy Standard 10 of the Manufactured Food Regulatory Program 
Standards (MFRPS) as the primary designated testing facility for the Food Safety and 
Sanitation Program (FSS). FSS is in full conformance to MRFPS standards.

## Key facts

- **NIH application ID:** 10173549
- **Project number:** 1U19FD007065-01
- **Recipient organization:** ALASKA STATE DEPT/ENVIRONMTL CONSERVATN
- **Principal Investigator:** PATRYCE D MCKINNEY
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2020
- **Award amount:** $97,167
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10173549

## Citation

> US National Institutes of Health, RePORTER application 10173549, ASEHL Admin Core (1U19FD007065-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10173549. Licensed CC0.

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