This review surveys recent advances in point-of-care testing (POCT) technologies for pesticide biomonitoring in human biofluids, with emphasis on urine and blood. We focus on electrochemical and colorimetric strategies that use functional nanomaterials to improve portability, reduce operational costs, and simplify sample handling relative to centralised laboratory immunoassays and chromatography–mass spectrometry. Progress in metallic nanoparticles, carbon-based and two-dimensional materials, conductive polymers, and reticular porous frameworks is discussed alongside hybrid architectures and antifouling interfaces. A comparative analysis highlights practical trade-offs among sensitivity, selectivity, time-to-result, and operational simplicity. Despite improved analytical performance, most POCT platforms remain at the proof-of-concept stage and lack validation under physiologically representative or field conditions, underscoring the need for standardised evaluation protocols and regulatory alignment. Finally, we discuss scalable manufacturing, sustainability, data governance, and the integration of machine learning and artificial intelligence as enabling routes for materials discovery, automated signal interpretation, and population-level surveillance of pesticide exposure.
Nanomaterial-enabled point-of-care technologies for pesticide biomonitoring in human biofluids: From detection strategies to real-world deployment
Felice Torrisi;
2026-01-01
Abstract
This review surveys recent advances in point-of-care testing (POCT) technologies for pesticide biomonitoring in human biofluids, with emphasis on urine and blood. We focus on electrochemical and colorimetric strategies that use functional nanomaterials to improve portability, reduce operational costs, and simplify sample handling relative to centralised laboratory immunoassays and chromatography–mass spectrometry. Progress in metallic nanoparticles, carbon-based and two-dimensional materials, conductive polymers, and reticular porous frameworks is discussed alongside hybrid architectures and antifouling interfaces. A comparative analysis highlights practical trade-offs among sensitivity, selectivity, time-to-result, and operational simplicity. Despite improved analytical performance, most POCT platforms remain at the proof-of-concept stage and lack validation under physiologically representative or field conditions, underscoring the need for standardised evaluation protocols and regulatory alignment. Finally, we discuss scalable manufacturing, sustainability, data governance, and the integration of machine learning and artificial intelligence as enabling routes for materials discovery, automated signal interpretation, and population-level surveillance of pesticide exposure.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
