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Engineering Innovative Interfaces for Point-of-Care Diagnostics.
Burrow, Damon T; Heggestad, Jacob T; Kinnamon, David S; Chilkoti, Ashutosh.
Afiliación
  • Burrow DT; Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708 USA.
  • Heggestad JT; Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708 USA.
  • Kinnamon DS; Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708 USA.
  • Chilkoti A; Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708 USA.
Curr Opin Colloid Interface Sci ; : 101718, 2023 Jun 08.
Article en En | MEDLINE | ID: mdl-37359425
ABSTRACT
The ongoing Coronavirus disease 2019 (COVID-19) pandemic illustrates the need for sensitive and reliable tools to diagnose and monitor diseases. Traditional diagnostic approaches rely on centralized laboratory tests that result in long wait times to results and reduce the number of tests that can be given. Point-of-care tests (POCTs) are a group of technologies that miniaturize clinical assays into portable form factors that can be run both in clinical areas --in place of traditional tests-- and outside of traditional clinical settings --to enable new testing paradigms. Hallmark examples of POCTs are the pregnancy test lateral flow assay and the blood glucose meter. Other uses for POCTs include diagnostic assays for diseases like COVID-19, HIV, and malaria but despite some successes, there are still unsolved challenges for fully translating these lower cost and more versatile solutions. To overcome these challenges, researchers have exploited innovations in colloid and interface science to develop various designs of POCTs for clinical applications. Herein, we provide a review of recent advancements in lateral flow assays, other paper based POCTs, protein microarray assays, microbead flow assays, and nucleic acid amplification assays. Features that are desirable to integrate into future POCTs, including simplified sample collection, end-to-end connectivity, and machine learning, are also discussed in this review.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2023 Tipo del documento: Article