Smartphone Enabled Point-of-Care Diagnostics for Operationally Significant Pathogens

Abstract

We developed a novel high-throughput screen in microarray format that identifies optimal pairing of antibody pairs, which led to successful identification of optimal antibody reagents for Ebola having excellent sensitivity. We have identified 24 highly promising clones for antibody reagents used for detecting Salmonella. We successfully developed an approach for self-calibrating assay chips that correlate fluorescence intensities to the true known concentration of spiked Ag in serum. We have also identified an optimal strategy for labeling our reagents that is well-suited for our portable assay reader. Furthermore, we have developed 3 redundant designs for our ruggedized, portable reader in case of primary device failure. For assay cassettes, we have devised a simple, low-cost chip that encases all reagents and test components in a user-friendly format. Finally, we devised a development strategy for a smartphone app that automates assay readout.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2017
Accession Number
AD1045963

Entities

People

  • Ashutosh Chilkoti
  • Michael Gunn

Organizations

  • Duke University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Computers
  • Detection
  • Detectors
  • Disease Attributes
  • Gram-Negative Bacterial Infections
  • Health Services
  • Identification
  • Infectious Diseases
  • Medical Personnel
  • Mobile Phones
  • Point-Of-Care Diagnostic Testing
  • Polymers
  • Quantum Dots
  • Self Assembly
  • Smartphones
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Biology

Readers

  • Oncology and Biomarker-Based Cancer Detection.
  • Optical Fiber Sensing and Electromagnetic Propagation.
  • Systems Analysis and Design