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Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients.
EMBO Mol Med. 2020 08 07; 12(8):e12697.EM

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+Show Affiliations

Department of Surgery and Cancer, Imperial College, London, UK.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Department of Surgery and Cancer, Imperial College, London, UK.Luigi Sacco, Department of Clinical and Biomedical Sciences, University of Milan, Milan, Italy.BenevolentAI, London, UK.Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden. Department of Physiology and Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden. Department of Physiology and Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden. Department of Physiology and Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden. Department of Physiology and Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.Infectious Diseases Programme, Immunology Programme, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore. Institute of Molecular and Cell Biology (IMCB), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.Department of Clinical, Surgical, Diagnostics and Pediatric Sciences, University of Pavia, Pavia, Italy. Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.Department of Clinical, Surgical, Diagnostics and Pediatric Sciences, University of Pavia, Pavia, Italy. Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Eli Lilly and Company, Indianapolis, IN, USA.Division of Infectious Diseases, ASST Fatebenefratelli Sacco, Milan, Italy.No affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

32473600

Citation

Stebbing, Justin, et al. "Mechanism of Baricitinib Supports Artificial Intelligence-predicted Testing in COVID-19 Patients." EMBO Molecular Medicine, vol. 12, no. 8, 2020, pp. e12697.
Stebbing J, Krishnan V, de Bono S, et al. Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients. EMBO Mol Med. 2020;12(8):e12697.
Stebbing, J., Krishnan, V., de Bono, S., Ottaviani, S., Casalini, G., Richardson, P. J., Monteil, V., Lauschke, V. M., Mirazimi, A., Youhanna, S., Tan, Y. J., Baldanti, F., Sarasini, A., Terres, J. A. R., Nickoloff, B. J., Higgs, R. E., Rocha, G., Byers, N. L., Schlichting, D. E., ... Corbellino, M. (2020). Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients. EMBO Molecular Medicine, 12(8), e12697. https://doi.org/10.15252/emmm.202012697
Stebbing J, et al. Mechanism of Baricitinib Supports Artificial Intelligence-predicted Testing in COVID-19 Patients. EMBO Mol Med. 2020 08 7;12(8):e12697. PubMed PMID: 32473600.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients. AU - Stebbing,Justin, AU - Krishnan,Venkatesh, AU - de Bono,Stephanie, AU - Ottaviani,Silvia, AU - Casalini,Giacomo, AU - Richardson,Peter J, AU - Monteil,Vanessa, AU - Lauschke,Volker M, AU - Mirazimi,Ali, AU - Youhanna,Sonia, AU - Tan,Yee-Joo, AU - Baldanti,Fausto, AU - Sarasini,Antonella, AU - Terres,Jorge A Ross, AU - Nickoloff,Brian J, AU - Higgs,Richard E, AU - Rocha,Guilherme, AU - Byers,Nicole L, AU - Schlichting,Douglas E, AU - Nirula,Ajay, AU - Cardoso,Anabela, AU - Corbellino,Mario, AU - ,, Y1 - 2020/06/24/ PY - 2020/05/16/received PY - 2020/05/22/revised PY - 2020/05/28/accepted PY - 2020/5/31/pubmed PY - 2020/8/22/medline PY - 2020/5/31/entrez KW - COVID-19 KW - anti-cytokine KW - anti-viral KW - baricitinib KW - case series SP - e12697 EP - e12697 JF - EMBO molecular medicine JO - EMBO Mol Med VL - 12 IS - 8 N2 - 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. SN - 1757-4684 UR - https://www.unboundmedicine.com/medline/citation/32473600/Mechanism_of_baricitinib_supports_artificial_intelligence_predicted_testing_in_COVID_19_patients_ L2 - https://doi.org/10.15252/emmm.202012697 DB - PRIME DP - Unbound Medicine ER -