Tuberculosis (TB) continues to pose a major global health threat, causing over a million deaths annually and disproportionately affecting populations in low- and middle-income countries. Drug resistance, diagnostic delays, and inconsistent access to care further complicate control efforts. Existing diagnostic methods are often too slow, too expensive, or too infrastructure-dependent to be practical in frontline settings where rapid case identification and treatment initiation are essential.

To address these challenges, we have developed a compact, low-cost diagnostic platform that integrates sample processing and biomarker detection into a single 3D microfluidic strip. Each strip contains eight self-contained microcells (9×9×14 mm), pre-loaded with all necessary reagents, and is designed for direct loading of up to eight raw sputum or swab samples—eliminating the need for upstream processing or laboratory support.

The test uses a small, USB-powered reader to apply an electrical voltage that separates and captures both pathogen-specific and host immune response DNA, RNA, and protein biomarkers to zones of immobilized probes and antibodies, producing a unique molecular fingerprint that provides sensitive TB detection and insights into disease stage, severity, and potential resistance profiles—enabling data-driven decisions at the point of care.

With an estimated cost of ~$1 per test and minimal training requirements, this small platform is ideally suited for community clinics, mobile health units, and outbreak response settings. It supports simultaneous testing of up to eight individuals per strip, allowing scalable screening even in resource-constrained environments. By enabling rapid, decentralized detection of TB using both pathogen and host-response biomarkers, our solution empowers global health initiatives to accelerate case finding, improve treatment targeting, and strengthen surveillance efforts—contributing directly to WHO End TB Strategy goals.