dbGaP Study Accession: phs002543

NIH Institute/Center: NIAAA

RADx Data Program: RADx-rad

DOI: 10.60773/prf9-6708

Release Date: 08/05/2022

Study Description: Reliable real-time detection of SARS-CoV-2 virus represents a considerable challenge, with available tools requiring extensive sample preparation and/or expensive lab-based equipment to obtain accurate results. The objective of this study was to build a touch-screen sensor array to directly capture, detect, and identify model SARS-CoV-2 virus particles with minimal false alarms. This ambitious goal was achieved by the interdisciplinary team of General Electric (GE) Research scientists and engineers, and was a synergistic combination of the proposed innovations and the prior scientific and engineering accomplishments of the team.

Updated Date: 12/09/2022

Principal Investigator: Potyrailo, Radislav A

Has Data Files: Yes

Study Domain: Biosensor Technology; Digital Health Applications

Data Collection Method: Unspecified COVID Testing Device

Keywords: Aptamer Beads Detection; Bioreceptors; Sample Data

Study Design: Device Validation Study

Multi-Center Study: FALSE

Data Types: Other; Immunological

Data Types, Other: Virus-binding data and technology of the developed biosensors

Study Start Date: 12/21/2020

Study End Date: 11/30/2022

Species: Non-Human Data

Estimated Cohort Size: 2

Study Population Focus: Adults

Acknowledgement Statement: This study was supported through funding, 4U01AA029324-02, for the National Institute on Alcohol Abuse and Alcoholism (NIAAA) as part of the RADx-rad program. Approved users should acknowledge the provision of data access by dbGaP for accession phs002543.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.

Funding Opportunity Announcement (FOA) Number: RFA-OD-20-014

NIH Grant or Contract Number(s): 4U01AA029324-02

Consent/Data Use Limitations: General Research Use