SBIR/STTR Research Award

SBIR Phase I: Investigating Disparate Pools of Data to Find Counterfeit Products

Award identifier 733193d4d2894e1e1485c3ec9e42698733ab7b33d3fcbef787a4f3b5977599d0Awarding agency National Science Foundation

Award amount

$224,358

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Authentag LLC
Proposal award date
2020-02-01
Contract end date
2020-07-31
UEI
EX93FP3QCAK1
Solicitation number
Not reported
Topic code
DL

Research abstract

The broader impact / commercial potential of this Small Business Innovation Research (SBIR) project is to save lives and reduce the liability and cost associated with pharmaceutical counterfeits, estimated at approximately 5% of US pharmaceuticals. Globally, this number rises to 30% (exceeding 50% in Asia and Africa). Counterfeit pharmaceuticals result in the death of an estimated one million people annually. Identifying these counterfeits by tracking movement through the supply chain is critical. The proposed project will develop a system to apply advanced distributed ledger technology and smart contracts, tracking a pharmaceutical product while maintaining confidential trade data and patient information. This SBIR Phase I project proposes to design a smart contract that can be launched dynamically and independently request, collate, analyze and act on data gathered from the disparate pools of information stored about US pharmaceuticals over the course of the product life cycle. Every packet of pharmaceutical products carries its own unique identification number; however, currently, there exists no secure, confidential and non-centralized chain of custody record. The Verification Router Service (VRS Network) now offers a means to send messages and request information about any pharmaceutical product but cannot authenticate the product. The proposed project will develop smart contracts, advanced encryption techniques, controlled distributed data access, and advanced analytics driven by machine learning algorithms. These smart contracts will be protected from passive observation or malicious interference through asymmetric public encryption, symmetric private keys and Russian doll encryption combined with mixing. The project will develop and integrate these capabilities to meet system requirements, delivering a set of contract specifications and protocols. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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