2026 Theses Doctoral

Advancing point-of-care blood diagnostics: Methods for streamlined sample processing and molecular biomarker detection

Victoriano, Christia M.

Blood tests are central to modern medicine, providing a broad window into human physiology and disease. Plasma-based molecular diagnostics enable the detection and monitoring of conditions ranging from infectious diseases to cancer. However, plasma-based molecular tests remain largely confined to centralized laboratories due to requirements for specialized equipment and trained personnel. In point-of-care settings such as outpatient clinics, community health centers, and rural areas, these constraints contribute to long turnaround times, delayed treatment decisions, and loss to patient follow-up. A key bottleneck is rapid, reliable processing of whole blood into assay-ready components– including plasma separation and biomarker extraction– without laboratory infrastructure. This dissertation addresses these challenges by developing simple, low-cost tools for blood processing and molecular detection, aiming to enable sensitive diagnostics across diverse clinical applications and sample volumes.

Aim 1 develops an integrated platform for processing fingerstick blood samples for point-of-care detection of infectious diseases. The system combines a dual-membrane filter for centrifuge-free plasma separation with a user-guided, magnet-actuated module for nucleic acid extraction. This low-cost, modular approach eliminates the need for electricity and complex instrumentation, enabling a streamlined, rapid workflow suitable for minimally trained users. Plasma purity, extraction efficiency, and detection sensitivity matched conventional laboratory methods, supporting the feasibility of the system for decentralized diagnostics.

Aim 2 extends this approach to enable automated, centrifuge-free plasma separation from larger venous blood volumes for higher sensitivity applications. The system integrates magnetic removal of red blood cells with dual-membrane filtration to enable efficient processing of milliliter-scale samples. The system requires minimal user intervention, is robust to sample variability, and achieves cell separation, hemolysis, and biomarker recovery comparable to centrifugation. This platform addresses a key barrier to high-sensitivity blood diagnostics in decentralized settings and improves sample stability for broader clinical use and accessibility.

Aim 3 develops molecular assay chemistry for detecting lung cancer-associated DNA methylation markers. The core contribution is a blocker-enhanced methylation-specific PCR assay that enables sensitive, specific methylation detection using simplified, cost-effective assay chemistry. In parallel, supporting technologies were developed to enable future workflow integration, including a methylation-preserving pre-amplification strategy and a magnet-actuated bisulfite conversion module. These advances establish a modular foundation for point-of-care epigenetic testing and support broader applications in cancer detection and monitoring.

Altogether, this work advances scalable solutions for decentralized blood-based molecular diagnostics by developing streamlined, low-cost tools for sample preparation and molecular detection. Across plasma separation, nucleic acid extraction, and detection chemistries, these platforms demonstrate how laboratory workflows can be simplified for point-of-care use and designed with sample-to-answer integration in mind. These advances support a shift toward more accessible diagnostics, enabling faster turnaround times and broader reach in both resource-limited and routine clinical settings. More broadly, this dissertation establishes a foundation for adaptable blood diagnostic technologies that can be extended to diverse biomarkers and disease applications, supporting the future of decentralized molecular testing.