Recombinase polymerase amplification (RPA) has become a central amplification strategy for decentralized molecular diagnostics because it operates rapidly at mild temperatures and requires far less thermal control than PCR. Its analytical value increases substantially when paired with microfluidic and paper-based platforms, where sample handling, reagent delivery, amplification, and signal readout can be organized within compact, low-power, and field-compatible formats. This review examines recent progress in microfluidic and paper-based RPA systems across biomedical diagnostics, food safety testing, environmental monitoring, and One Health biosurveillance. Particular attention is given to integrated device architectures, including centrifugal chips, capillary-driven platforms, microfluidic paper-based analysis devices (μPADs), electrochemical biosensors, CRISPR-assisted assays, digital microfluidic systems, and sample-to-answer cartridges. Biomedical applications now span respiratory viruses, reproductive and emerging infections, bacterial and parasitic diseases, pharmacogenomic markers, and cancer-related biomarkers. RPA-enabled platforms are moving steadily into food safety and environmental surveillance, covering pathogen detection, seafood and dairy monitoring, agricultural disease control, antimicrobial-resistance tracking, and airborne pathogen screening. At the same time, the field is shifting toward more intelligent diagnostic formats. Smartphone imaging, artificial intelligence (AI)-assisted interpretation, digital partitioning, cloud connectivity, and automated quality control are increasingly being built into rapid testing workflows, giving these systems greater portability, consistency, and decision-making value. Despite this progress, practical deployment still depends on robust sample preparation, multiplex stability, quantitative reliability, reagent storage, scalable fabrication, and regulatory validation. Continued convergence of RPA chemistry with microfluidics, paper devices, CRISPR recognition, electrochemical readout, and data-assisted interpretation is expected to support more robust and accessible molecular diagnostic workflows.
Full article
