Microfluidic-Based Molecular Diagnostics for Pathogen Detection in Urine Samples for Resource-Limited Settings: A Review
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Updated: Nov 1, 2026

Microfluidic Applications for Disposable Diagnostics
Published on: February 3, 2008
E Alperay Tarim1, Natish Kumar1, Michael Mauk1
1Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania19104, United States.
Abstract:
Urine is a convenient, noninvasive specimen for molecular diagnostics, offering advantages in scalability, patient compliance, and suitability for decentralized testing. However, its clinical adoption for molecular pathogen detection remains limited by intrinsic physicochemical variability, low target abundance, and the presence of inhibitors of enzymatic nucleic acid amplification that may seriously compromise assay sensitivity and reproducibility. In this review, we introduce a urine-first design paradigm in which device architecture and assay chemistry are codesigned around the unique biochemical constraints of urine rather than adapted from conventional blood-based workflows. This paradigm is built on three interdependent principles: matrix-aware sample processing with efficient inhibitor removal and multifraction nucleic acid capture; amplification chemistry with built-in tolerance to pH fluctuations, ionic variability, and residual urinary inhibitors; and closed, integrated microfluidic architectures that minimize contamination risk. We compare on-chip amplification strategies, including PCR, isothermal amplification methods such as LAMP and RPA, digital PCR, and CRISPR-assisted detection, and evaluate trade-offs in sensitivity, inhibitor tolerance, and deployability. Detection modalities, including fluorescence, colorimetric, electrochemical, and lateral-flow readouts, are assessed for analytical performance and compatibility with resource-limited settings. By integrating biological insight with engineering design, this review provides a practical roadmap for developing accessible, field-ready urine-based diagnostic platforms.

