Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.

摘要: IL-6 is a central mediator of the immediate induction hepatic acute phase proteins (APP) in liver during infection and after injury, but increased activity has been associated with multiple pathological conditions. In hepatocytes, activates JAK1-STAT3 signaling that induces negative feedback regulator SOCS3 expression APPs. While different inhibitors IL-6-induced JAK1-STAT3-signaling have developed, understanding their precise impact on dynamics requires systems biology approach. Here we present mathematical model quantitatively links physiological concentrations to signal transduction target genes hepatocytes. The consists coupled ordinary differential equations (ODE) parameters were estimated by maximum likelihood approach, whereas identifiability dynamic was ensured Profile Likelihood. Using simulations experimental validation could optimize long-term JAK-inhibitor Ruxolitinib, therapeutic compound quickly metabolized. Model-predicted doses timing treatments helps improve reduction inflammatory APP gene primary mouse hepatocytes close levels observed regenerative concept improved efficacy inhibitor through at optimized time intervals confirmed human Thus, combining quantitative data generation modeling suggests repetitive treatment Ruxolitinib required effectively excessive responses without exceeding recommended clinical guidelines.