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

Stebbing, Justin; Krishnan, Venkatesh; de Bono, Stephanie; Ottaviani, Silvia; Casalini, Giacomo; Richardson, Peter J.; Monteil, Vanessa; Lauschke, Volker M.; Mirazimi, Ali; Youhanna, Sonia; Tan, Yee‐Joo; Baldanti, Fausto; Sarasini, Antonella; Terres, Jorge A. Ross; Nickoloff, Brian J.; Higgs, Richard E.; Rocha, Guilherme; Byers, Nicole L.; Schlichting, Douglas E.; Nirula, Ajay; Cardoso, Anabela; Corbellino, Mario

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 a 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 supports its assessment in randomized trials in hospitalized COVID‐19 patients.