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Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients.

Authors :
Stebbing J
Krishnan V
de Bono S
Ottaviani S
Casalini G
Richardson PJ
Monteil V
Lauschke VM
Mirazimi A
Youhanna S
Tan YJ
Baldanti F
Sarasini A
Terres JAR
Nickoloff BJ
Higgs RE
Rocha G
Byers NL
Schlichting DE
Nirula A
Cardoso A
Corbellino M
Source :
EMBO molecular medicine [EMBO Mol Med] 2020 Aug 07; Vol. 12 (8), pp. e12697. Date of Electronic Publication: 2020 Jun 24.
Publication Year :
2020

Abstract

Baricitinib is an oral Janus kinase (JAK)1/JAK2 inhibitor approved for the treatment of rheumatoid arthritis (RA) that was independently predicted, using artificial intelligence (AI) algorithms, to be useful for COVID-19 infection via proposed anti-cytokine effects and as an inhibitor of host cell viral propagation. We evaluated the in vitro pharmacology of baricitinib across relevant leukocyte subpopulations coupled to its in vivo pharmacokinetics and showed it inhibited signaling of cytokines implicated in COVID-19 infection. We validated the AI-predicted biochemical inhibitory effects of baricitinib on human numb-associated kinase (hNAK) members measuring nanomolar affinities for AAK1, BIKE, and GAK. Inhibition of NAKs led to reduced viral infectivity with baricitinib using human primary liver spheroids. These effects occurred at exposure levels seen clinically. In a case series of patients with bilateral COVID-19 pneumonia, baricitinib treatment was associated with clinical and radiologic recovery, a rapid decline in SARS-CoV-2 viral load, inflammatory markers, and IL-6 levels. Collectively, these data support further evaluation of the anti-cytokine and anti-viral activity of baricitinib and support its assessment in randomized trials in hospitalized COVID-19 patients.<br /> (© 2020 Eli Lilly and Company Published under the terms of the CC BY 4.0 license.)

Details

Language :
English
ISSN :
1757-4684
Volume :
12
Issue :
8
Database :
MEDLINE
Journal :
EMBO molecular medicine
Publication Type :
Academic Journal
Accession number :
32473600
Full Text :
https://doi.org/10.15252/emmm.202012697