The goal of this project is to develop an easy to use sensor device (similar to the over-the counter pregnancy test) for the detection of malarial infection at a sensitivity suitable for diagnosis. The sensor device is expected to be robust, rapid, low-cost, easy-to-interpret and have a low detection limit while requiring no equipment or trained personnel. The primary goal is to significantly improve the detection limit while maintaining all the desirable operating characteristics.

Available diagnostic methods for malaria have excellent sensitivities and specificities, but are not suitable for resource-poor settings. Current lateral-flow immunoassay (LFA) devices detect Plasmodium lactate dehydrogenase (pLDH), Plasmodium-specific histidine-rich protein (HRP-2), and/or Plasmodium aldolase, all of which are found in an infected individual, but their sensitives are below the recommended World Health Organization threshold of 95% sensitivity. The goal of the proposed work is to improve the sensitivity of the conventional LFA, by integrating two methods of enhancement into a single, automated paper-based device. The first method utilizes aqueous two-phase system (ATPS) separation on paper, in which a well-mixed ATPS solution rapidly separates into its macroscopic phases and concentrates the target biomarker as it flows through a paper membrane. The second method incorporates a signal enhancement reaction that utilizes engineered nanoparticles with enzymatic activity. The proposed work will investigate a new approach for controlling fluid flow through the extension of ATPS separation on paper in order to sequentially deliver signal enhancement reagents to the LFA detection zone. Additionally, to maximize shelf-life and ease-of-use, all required assay components will be dehydrated on the LFA test strip. It is anticipated that the seamless coupling of the LFA with pre-concentration and signal enhancement capabilities will result in significant sensitivity when compared to the traditional LFA, while maintaining the same user-friendliness.

Project Start
Project End
Budget Start
2017-07-01
Budget End
2021-06-30
Support Year
Fiscal Year
2017
Total Cost
$300,000
Indirect Cost
Name
University of California Los Angeles
Department
Type
DUNS #
City
Los Angeles
State
CA
Country
United States
Zip Code
90095