STTR Phase I: Smart SAM for Visible Detection of Paralytic Shellfish Toxins

Award Information
Agency:
National Science Foundation
Amount:
$150,000.00
Program:
STTR
Contract:
0740590
Solitcitation Year:
N/A
Solicitation Number:
NSF 07-551
Branch:
N/A
Award Year:
2008
Phase:
Phase I
Agency Tracking Number:
0740590
Solicitation Topic Code:
AM
Small Business Information
White River Bioscience, Inc.
672 N. Cliffside Drive, Fayetteville, AR, 72701
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
191079842
Principal Investigator
 Thomas Atkinson
 BA
 (479) 575-6933
 tommy.atkinson@gmail.com
Business Contact
 Thomas Atkinson
Title: BA
Phone: (479) 575-6933
Email: tommy.atkinson@gmail.com
Research Institution
 University of Arkansas
 Robert Gawley
 120 Ozark Hall
Fayetteville, AR, 72701
 (479) 575-6933
 Nonprofit college or university
Abstract
This Small Business Technology Transfer Phase I project applies newly developed technology to construct a smart Self-Assembled Monolayer (SAM) for the rapid detection of Paralytic Shellfish Toxins, (PSTs), which are neurotoxic seafood poisons produced by algae then accumulated in filter-feeding shellfish. The disease that results from ingestion of contaminated shellfish is called Paralytic Shellfish Poisoning or PSP. The proposed technology could be applicable to an inexpensive, portable device, to an accessory for a benchtop fluorometer, or in an array for high throughput analysis. The broader impacts of this research are related to the protection of human health by providing an alternative to animal testing in determining the safety of shellfish for human consumption. PSTs can be fatal to humans. PST detection programs may use a number of techniques, but mouse bioassay is the current benchmark technique in the food safety arena. This method involves injection of a shellfish extract into a mouse. The time it takes the mouse to die correlates with toxicity. The mouse bioassay is a reliable indicator of human toxicity, but it is expensive and time consuming, especially for large numbers of samples. For both economic and ethical reasons, an alternative is highly desirable.

* information listed above is at the time of submission.

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