Developing a Paper-Based Diagnostic Kit for the Detection of a Malaria Biomarker in Serum

The prevalence of malaria across the globe creates the need for the development of diagnostic devices, as many deaths caused by malaria could be prevented by early diagnosis and treatment. Since typical symptoms of malaria, such as fever and chills, are challenging to distinguish from other diseases, diagnostic tests are crucial for allowing patients to receive the appropriate medical care. While current gold-standard methods such as microscopy are able to identify the presence and species of malaria parasites, the sensitivity achieved with these methods depends on the microscopist’s training, as well as access to resources such as lab equipment and power. Disparities in supplies and training lead to late or incorrect diagnosis in resource-limited areas across the globe. This has led to the development of point-of-care devices, which provide more rapid results without the need for expensive lab equipment or training. One example of such a device is the lateral-flow immunoassay (LFA), which has commonly found use as at-home pregnancy tests and recently as COVID-19 tests. Although the LFA is simple to use and provides easy-to-read results, currently available LFAs for malaria detection suffer from lower sensitivity compared to laboratory tests. In this thesis, I investigate methods for improving the detection of the malaria antigen Plasmodium falciparum lactate dehydrogenase (pLDH). Methods to improve the detection of the LFA include biomarker preconcentration and signal enhancement. Biomarker preconcentration can be achieved using aqueous two-phase systems (ATPSs), which are liquid-liquid extraction systems composed mostly of water. Molecules that are added into an ATPS can be concentrated into the smaller of the two phases. In addition, the sensitivity of the LFA can be improved through the use of signal enhancement, which aims to increase the intensity at the detection zone with the use of additional or modified colorimetric indicators. In Chapter 2, we focus on us