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dc.contributor.authorRamakrishnan, Boopathy
dc.contributor.authorViswanathan, Karthik
dc.contributor.authorTharakaraman, Kannan
dc.contributor.authorDančík, Vlado
dc.contributor.authorRaman, Rahul
dc.contributor.authorBabcock, Gregory J.
dc.contributor.authorShriver, Zachary
dc.contributor.authorSasisekharan, Ram
dc.date.accessioned2018-09-11T18:12:50Z
dc.date.available2018-09-11T18:12:50Z
dc.date.issued2016-10
dc.identifier.issn0966-842X
dc.identifier.urihttp://hdl.handle.net/1721.1/117715
dc.description.abstractBroadly neutralizing monoclonal antibodies (bNAbs) for viral infections, such as HIV, respiratory syncytial virus (RSV), and influenza, are increasingly entering clinical development. For influenza, most neutralizing antibodies target influenza virus hemagglutinin. These bNAbs represent an emerging, promising modality for treatment and prophylaxis of influenza due to their multiple mechanisms of antiviral action and generally safe profile. Preclinical work in other viral diseases, such as dengue, has demonstrated the potential for antibody-based therapies to enhance viral uptake, leading to enhanced viremia and worsening of disease. This phenomenon is referred to as antibody-dependent enhancement (ADE). In the context of influenza, ADE has been used to explain several preclinical and clinical phenomena. Using structural and viral kinetics modeling, we assess the role of ADE in the treatment of influenza with a bNAb.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Merit Award R37 GM057073-13)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant RO1 AI111395-03)en_US
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/J.TIM.2016.09.003en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcePMCen_US
dc.titleA Structural and Mathematical Modeling Analysis of the Likelihood of Antibody-Dependent Enhancement in Influenzaen_US
dc.typeArticleen_US
dc.identifier.citationRamakrishnan, Boopathy, et al. “A Structural and Mathematical Modeling Analysis of the Likelihood of Antibody-Dependent Enhancement in Influenza.” Trends in Microbiology, vol. 24, no. 12, Dec. 2016, pp. 933–43.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.mitauthorTharakaraman, Kannan
dc.contributor.mitauthorRaman, Rahul
dc.contributor.mitauthorSasisekharan, Ram
dc.relation.journalTrends in Microbiologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-09-10T19:08:59Z
dspace.orderedauthorsRamakrishnan, Boopathy; Viswanathan, Karthik; Tharakaraman, Kannan; Dančík, Vlado; Raman, Rahul; Babcock, Gregory J.; Shriver, Zachary; Sasisekharan, Ramen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-2085-7840
mit.licensePUBLISHER_CCen_US


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