Development of a Flow-Free Magnetic Actuation Platform for an Automated Microfluidic ELISA.

There is a need to create an easily deployable and point-of-care (POC) diagnostic platform for disease outbreaks and for monitoring and maintenance of chronic illnesses. Such platforms are useful in regions where access to clinical laboratories may be limited or constrained using cost-effective solutions to quickly process high numbers of samples. Using oil and water liquid-liquid interphase separation, immunoassays developed for microfluidic chips can potentially meet this need when leveraged with electromagnetic actuation and antibody-coated superparamagnetic beads. We have developed a microfluidic immunoassay detection platform, which enables assay automation and maintains successful liquid containment for future use in the field. The assay was studied through a series of magnetic and fluid simulations to demonstrate these optimizations, and an optimized chip was tested using a target model for HIV-1, the p24 capsid antigen. The use of minimal reagents further lowers the cost of each assay and lowers the required sample volume for testing (<50 µL), that can offer easy turnaround for sample collection and assay results. The developed microfluidic immunoassay platform can be easily scaled for multiplex or multi-panel specific testing at the POC.

Point-of-care Colorimetric Analysis through Smartphone Video.

Point-of-care (POC) tests often rely on smartphone image methods for colorimetric analysis, but the results of such methods are frequently difficult to reproduce or standardize. The problem is aggravated by unpredictable image capture conditions, which pose a significant challenge when low limits of detection (LOD) are needed. Application-specific smartphone attachments are often used to standardize imaging conditions, but there has recently been an interest in equipment-free POC colorimetric analysis. Improved output metrics and preprocessing methods have been developed, but equipment-free imaging often has a high LOD and is inappropriate for quantitative tasks. Additional work is necessary to replace external smartphone attachments with algorithms. Towards this end, we have developed a video processing method that synthesizes many images into a single output metric. We use image features to select the best inputs from a large set of video frames and demonstrate that the resulting output values have a stronger correlation with laboratory methods and a lower standard error. The developed algorithm only requires 20 seconds of video and can easily be integrated with existing processing methods. We apply our algorithm to the NS1-based sandwich ELISA for Zika detection and show that the LOD is two times lower when our video-based method is used.

Cell phone based colorimetric analysis for point-of-care settings.

Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue-saturation-value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results.

Strategies in Ebola virus disease (EVD) diagnostics at the point of care.

Ebola virus disease (EVD) is a devastating, highly infectious illness with a high mortality rate. The disease is endemic to regions of Central and West Africa, where there is limited laboratory infrastructure and trained staff. The recent 2014 West African EVD outbreak has been unprecedented in case numbers and fatalities, and has proven that such regional outbreaks can become a potential threat to global public health, as it became the source for the subsequent transmission events in Spain and the USA. The urgent need for rapid and affordable means of detecting Ebola is crucial to control the spread of EVD and prevent devastating fatalities. Current diagnostic techniques include molecular diagnostics and other serological and antigen detection assays; which can be time-consuming, laboratory-based, often require trained personnel and specialized equipment. In this review, we discuss the various Ebola detection techniques currently in use, and highlight the potential future directions pertinent to the development and adoption of novel point-of-care diagnostic tools. Finally, a case is made for the need to develop novel microfluidic technologies and versatile rapid detection platforms for early detection of EVD.

Advances in Candida detection platforms for clinical and point-of-care applications.

Invasive candidiasis remains one of the most serious community and healthcare-acquired infections worldwide. Conventional Candida detection methods based on blood and plate culture are time-consuming and require at least 2-4 days to identify various Candida species. Despite considerable advances for candidiasis detection, the development of simple, compact and portable point-of-care diagnostics for rapid and precise testing that automatically performs cell lysis, nucleic acid extraction, purification and detection still remains a challenge. Here, we systematically review most prominent conventional and nonconventional techniques for the detection of various Candida species, including Candida staining, blood culture, serological testing and nucleic acid-based analysis. We also discuss the most advanced lab on a chip devices for candida detection.