Journal
CHEMICAL REVIEWS
Volume 122, Issue 18, Pages 14881-14910Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.chemrev.1c01012
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Funding
- Instituto de Salud Carlos III (ISCIII)
- European Union
- MICROB-PREDICT project (European Union Horizon 2020 research and innovation program )
- Graphene Flagship Core 3 (European Union Horizon 2020 research and innovation program)
- CERCA programme, Generalitat de Catalunya
- MCIN/AEI
- FEDER Una manera de hacer Europa [AC21_2/00044]
- European Union NextGenerationEU/PRTR
- Consejo Superior de Investigaciones Cientificas (CSIC) [825694]
- MINECO [881603]
- Marie Sklodowska-Curie Actions Individual Fellowship
- European Union [AC21_2/00044, 825694, 881603]
- Spanish Ministry of Science and Innovation
- State Research Agency
- [SEV-2017-0706]
- [PID2021-124795NB-I00]
- [PLEC2021-007972]
- [FJC2020-043927-I]
- [795635]
- [CEX2018-000806-S]
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This article reviews the application of nanomaterial-based lateral flow assays (LFAs) in point-of-care diagnostics. By incorporating novel nanomaterials as signal transducers or receptor immobilization platforms, the analytical capabilities of LFAs have been improved. The article highlights strategies that can address the limitations of current LFAs and have shown commercial feasibility.
Lateral flow assays (LFAs) are currently the most used point-of-care sensors for both diagnostic (e.g., pregnancy test, COVID-19 monitoring) and environmental (e.g., pesticides and bacterial monitoring) applications. Although the core of LFA technology was developed several decades ago, in recent years the integration of novel nanomaterials as signal transducers or receptor immobilization platforms has brought improved analytical capabilities. In this Review, we present how nanomaterial-based LFAs can address t h e inherent challenges of point-of-care (PoC) diagnostics such as sensit i v i t y enhancement, lowering of detection limits, multiplexing, and quantification of analytes in complex samples. Specifically, we highlight the strategies that can synergistically solve the limitations of current LFAs and that have proven commercial feasibi l i t y . Finally, we discuss the barriers toward commercialization and the next generation of LFAs.
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