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dc.contributor.authorBlevins, Morgan G.
dc.contributor.authorFernandez-Galiana, Alvaro
dc.contributor.authorHooper, Milo J.
dc.contributor.authorBoriskina, Svetlana V.
dc.date.accessioned2021-10-28T13:38:26Z
dc.date.available2021-10-28T13:38:26Z
dc.date.issued2021-08-20
dc.identifier.urihttps://hdl.handle.net/1721.1/136694
dc.description.abstractThe COVID-19 pandemic has made it abundantly clear that the state-of-the-art biosensors may not be adequate for providing a tool for rapid mass testing and population screening in response to newly emerging pathogens. The main limitations of the conventional techniques are their dependency on virus-specific receptors and reagents that need to be custom-developed for each recently-emerged pathogen, the time required for this development as well as for sample preparation and detection, the need for biological amplification, which can increase false positive outcomes, and the cost and size of the necessary equipment. Thus, new platform technologies that can be readily modified as soon as new pathogens are detected, sequenced, and characterized are needed to enable rapid deployment and mass distribution of biosensors. This need can be addressed by the development of adaptive, multiplexed, and affordable sensing technologies that can avoid the conventional biological amplification step, make use of the optical and/or electrical signal amplification, and shorten both the preliminary development and the point-of-care testing time frames. We provide a comparative review of the existing and emergent photonic biosensing techniques by matching them to the above criteria and capabilities of preventing the spread of the next global pandemic.en_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.relation.isversionofhttp://dx.doi.org/10.3390/photonics8080342en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceMultidisciplinary Digital Publishing Instituteen_US
dc.titleRoadmap on Universal Photonic Biosensors for Real-Time Detection of Emerging Pathogensen_US
dc.typeArticleen_US
dc.identifier.citationPhotonics 8 (8): 342 (2021)en_US
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-08-26T13:28:04Z
dspace.date.submission2021-08-26T13:28:04Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US
mit.metadata.statusAuthority Work and Publication Information Needed


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