Predicting cytokine kinetics during sepsis; a modelling framework from a porcine sepsis model with live Escherichia coli

Background: Describing the kinetics of cytokines involved as biomarkers of sepsis progression could help to optimise interventions in septic patients. This work aimed to quantitively characterise the cytokine kinetics upon exposure to live E. coli by developing an in silico model, and to explore predicted cytokine kinetics at different bacterial exposure scenarios. Methods: Data from published in vivo studies using a porcine sepsis model were analysed. A model describing the time courses of bacterial dynamics, endotoxin (ETX) release, and the kinetics of TNF and IL-6 was developed. The model structure was extended from a published model that quantifies the ETX-cytokines relationship. An external model evaluation was conducted by applying the model to literature data. Model simulations were performed to explore the sensitivity of the host response towards differences in the input rate of bacteria, while keeping the total bacterial burden constant. Results: The analysis included 645 observations from 30 animals. The blood bacterial count was well described by a one-compartment model with linear elimination. A scaling factor was estimated to quantify the ETX release by bacteria. The model successfully described the profiles of TNF, and IL-6 without a need to modify the ETXcytokines model structure. The kinetics of TNF, and IL-6 in the external datasets were well predicted. According to the simulations, the ETX tolerance development results in that low initial input rates of bacteria trigger the lowest cytokine release. Conclusion: The model quantitively described and predicted the cytokine kinetics triggered by E. coli exposure. The host response was found to be sensitive to the bacterial exposure rate given the same total bacterial burden