Assessment and monitoring of the viral load of HIV+ patients and their adherence to antiretroviral (ART) therapy are critically important for controllig the course of the disease, assessing transmission risks, and monitoring of HIV infection within communities. Viral load measurements are currently conducted in laboratory settings using costly and bulky apparatus including benchtop optical microscopes and sample preparation steps that require advanced lab instruments, which are hard to find and operate in resource limited environments or at the patient's home. In addition to the complexity, cost and bulkiness of existing tools, HIV viral load measurement methods currently rely on blood drawing, which can in general create significant sanitary and safety concerns in resource limited settings or at home. The proposed research plan covers the development and testing of a field-portable and label-free flexible sensing platform that is based on surface plasmon resonant (SPR) properties of specially designed quasi three-dimensional metal nanostructures (MNS) which will be integrated with commercially available soft contact lenses to create a cost effective and non-invasive diagnostic tool that can work even at home for measuring the viral load of HIV+ patients using tear. This new sensing platform will be designed to achieve flexibility by constructing its sensing unit on flexible substrates to enable intimate, direct contact with curved or irregular surfaces such as the human eye without any additional sample retrieval or processing steps and without obscuring natural vision or causing user discomfort. In addition to the flexible plasmonic sensor integrated onto the contact lens surface, we will also create a field portable and cost- effective smart phone based spectral reader platform to specifically analyze and quantify the viral load through multi-spectral imaging and automated analysis of the built-in nano-sensor on the surface of each contact lens. Previous studies have shown that HIV particles exist in tear and ocular fluids of HIV+ patients, and therefore tracking HIV status through tear can present a much safer and simpler approach for monitoring of HIV+ patients and their adherence to ART. In addition to improving care adherence and non- invasively quantifying the viral load of HIV+ patients through tear films, this proposed platform will ultimately provide a simple, cost-effective and light-weight toolset for multiplexed biological and chemical sensing needs, enabling various other future biomedical applications of wearable sensors.

Public Health Relevance

This application aims to create a flexible and wearable nano-plasmonic sensor platform that will be integrated onto commercially available soft contact lens surfaces to facilitate the measurement of HIV viral load in tear, which will provide a fundamentally new non-invasive method to monitor HIV+ patients in resource limited settings and even at home. In addition to the flexible plasmonic sensor integrated onto the contact lens surface, we will also create a smart phone based spectral reader platform to specifically analyze and automatically quantify the viral load through multi-spectral imaging of the surface of each contact lens. Apart from improving care adherence and non-invasively quantifying the viral load of HIV+ patients, the same platform technology will be significant for various other multiplexed bio-sensing applications using wearable flexible sensors and mobile phone based field portable microscopic readers.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB023115-02
Application #
9295029
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lash, Tiffani Bailey
Project Start
2016-07-01
Project End
2019-04-30
Budget Start
2017-05-01
Budget End
2019-04-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of California Los Angeles
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Veli, Muhammed; Ozcan, Aydogan (2018) Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning. ACS Nano 12:2554-2559
Ballard, Zachary S; Shir, Daniel; Bhardwaj, Aashish et al. (2017) Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning. ACS Nano 11:2266-2274