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Zeteo Tech, Inc. SBIR Phase II Award, April 2022

A SBIR Phase II contract was awarded to Zeteo Tech in April, 2022 for $995,762.0 USD from the U.S. Department of Homeland Security and Countering Weapons of Mass Destruction Office.

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Contents

sbir.gov/node/2234689
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Zeteo Tech
Zeteo Tech
0
Government Agency
U.S. Department of Homeland Security
U.S. Department of Homeland Security
0
Government Branch
Countering Weapons of Mass Destruction Office
Countering Weapons of Mass Destruction Office
0
Award Type
SBIR0
Contract Number (US Government)
70RWMD22C000000020
Award Phase
Phase II0
Award Amount (USD)
995,7620
Date Awarded
April 6, 2022
0
End Date
April 5, 2024
0
Abstract

Our Phase 1 effort demonstrated that high resolution MALDI-MS can reliably deconvolve complex mixtures and accurately identify the individual components. The Phase 1 prototype was an enhanced version of a mass analyzer like that of the BioTOF system and demonstrated both enhanced resolution and higher sensitivity. This effort will further improve mass resolution and sensitivity and result in a High-Performance BioTOF platform. We will upgrade existing real-time BioTOF signal processing and classification software to incorporate multiplex classification capability and statistically analyze performance.During the first three months of this effort, we will integrate these enhancements to produce the first High-Performance BioTOF system. After integration, we will verify operability and performance with simulant mixtures, followed by testing in BSL-2 with mixtures of five inactive agents. A second system will be completed by the end of month six, and we will begin field testing as these systems are completed. Two additional systems will be completed by month 14 allowing us to ramp up field testing from two to four sites. To examining signature stability over time, one of these systems will undergo inactive agent testing in MRIGlobal’s BSL-2 laboratory during year two. Using agent data collected at MRIGlobal we will train a classifier to detect both single agents and mixtures of up to five agents. This classifier will be installed into the current BioTOF real-time system and will be utilized during field tests. Additionally, field test data will be archived for further post-collection analysis, algorithm optimization and ROC curve generation.

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