Prevention and therapy of SARS-CoV-2 and the B.1.351 variant in mice.


Journal

Cell reports
ISSN: 2211-1247
Titre abrégé: Cell Rep
Pays: United States
ID NLM: 101573691

Informations de publication

Date de publication:
27 07 2021
Historique:
received: 27 01 2021
revised: 22 04 2021
accepted: 02 07 2021
pubmed: 22 7 2021
medline: 12 8 2021
entrez: 21 7 2021
Statut: ppublish

Résumé

Improving clinical care for individuals infected with SARS-CoV-2 variants is a global health priority. Small-molecule antivirals like remdesivir (RDV) and biologics such as human monoclonal antibodies (mAbs) have demonstrated therapeutic efficacy against SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19). It is not known whether combination RDV/mAb will improve outcomes over single-agent therapies or whether antibody therapies will remain efficacious against variants. Here, we show that a combination of two mAbs in clinical trials, C144 and C135, have potent antiviral effects against even when initiated 48 h after infection and have therapeutic efficacy in vivo against the B.1.351 variant of concern (VOC). Combining RDV and antibodies provided a modest improvement in outcomes compared with single agents. These data support the continued use of RDV to treat SARS-CoV-2 infections and the continued clinical development of the C144 and C135 antibody combination to treat patients infected with SARS-CoV-2 variants.

Identifiants

pubmed: 34289384
pii: S2211-1247(21)00867-6
doi: 10.1016/j.celrep.2021.109450
pmc: PMC8270748
mid: NIHMS1728470
pii:
doi:

Substances chimiques

Antibodies, Monoclonal 0
Antiviral Agents 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

109450

Subventions

Organisme : NIAID NIH HHS
ID : F32 AI152296
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA016086
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI132178
Pays : United States
Organisme : NIAID NIH HHS
ID : T32 AI007151
Pays : United States

Commentaires et corrections

Type : UpdateOf

Informations de copyright

Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests J.Y.F., E.B., D.P.P., and T.C. are employed by Gilead Sciences Inc.

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Auteurs

David R Martinez (DR)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: david.rafael.martinez@gmail.com.

Alexandra Schäfer (A)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Sarah R Leist (SR)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Dapeng Li (D)

Duke Human Vaccine Institute, Duke University, Durham, NC, USA.

Kendra Gully (K)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Boyd Yount (B)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Joy Y Feng (JY)

Gilead Sciences, Inc., Foster City, CA, USA.

Elaine Bunyan (E)

Gilead Sciences, Inc., Foster City, CA, USA.

Danielle P Porter (DP)

Gilead Sciences, Inc., Foster City, CA, USA.

Tomas Cihlar (T)

Gilead Sciences, Inc., Foster City, CA, USA.

Stephanie A Montgomery (SA)

Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.

Barton F Haynes (BF)

Duke Human Vaccine Institute, Duke University, Durham, NC, USA.

Ralph S Baric (RS)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Michel C Nussenzweig (MC)

The Rockefeller University, New York, NY, USA; The Howard Hughes Medical Institute, Chevy Chase, MD, USA.

Timothy P Sheahan (TP)

Department of Epidemiology, READDI Initiative, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: sheahan@email.unc.edu.

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Classifications MeSH