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

Journal: EMBO molecular medicine
PMID: 32473600

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.

Authors

  • Justin Stebbing
    Department of Surgery and Cancer, Imperial College, London, UK.
  • Venkatesh Krishnan
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Stephanie de Bono
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Silvia Ottaviani
    Department of Surgery and Cancer, Imperial College, London, UK.
  • Giacomo Casalini
    Luigi Sacco, Department of Clinical and Biomedical Sciences, University of Milan, Milan, Italy.
  • Peter J Richardson
    BenevolentAI, London, UK.
  • Vanessa Monteil
    Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
  • Volker M Lauschke
    Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
  • Ali Mirazimi
    Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
  • Sonia Youhanna
    Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
  • Yee-Joo Tan
    Infectious Diseases Programme, Immunology Programme, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore.
  • Fausto Baldanti
    Department of Clinical, Surgical, Diagnostics and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Antonella Sarasini
    Department of Clinical, Surgical, Diagnostics and Pediatric Sciences, University of Pavia, Pavia, Italy.
  • Jorge A Ross Terres
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Brian J Nickoloff
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Richard E Higgs
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Guilherme Rocha
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Nicole L Byers
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Douglas E Schlichting
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Ajay Nirula
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Anabela Cardoso
    Eli Lilly and Company, Indianapolis, IN, USA.
  • Mario Corbellino
    Division of Infectious Diseases, ASST Fatebenefratelli Sacco, Milan, Italy.

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