(696h) A Model-Based Investigation of Cytokine Storm for T-Cell Therapy
In 2006, a Phase 1 clinical trial of a CD28 monoclonal antibody superagonist was introduced to 6 healthy patients, all male subjects (7). The drug had previously been tested in other animal studies and had been successful (8). In less than an hour, all the patients exposed to the superagonist had spiked cytokine levels, where some of the markers of cell death and inflammation, such as cytokines Interferon-Î³ and TNF-Î± were at rising at a dangerous rate (7). Doctors stepped in and delivered analgesic drugs and an IL2 receptor antagonist antibody to blunt the reaction. Although all 6 patients survived, all of them had permanent effects from only 8mg of the CD28 superagonist. Doctors captured frequent blood samples and measured cytokine levels using cytobeads, as well as levels of T-cells, macrophages and other indicators of inflammation (7). Half a decade later, Stengelâs group at Princeton University developed the first human multi-cytokine computational model in an article entitled, Dynamics of a Cytokine Storm (6). It is the only model to date which models human cytokine levels on this scale. The researchers developed a second order linear system of equations, both uncoupled and coupled for all nine cytokines monitored. This model illustrated the positive and negative relationship between cytokines; it was an 18 variable, 90 parameter model.
In this work, we further simulated Stengelâs CRS model to: 1) study the variation ranges (i.e., uncertainties) of TNF-Î±, IFN-Î³, IL1, IL2, IL4, IL6, IL8, IL10 and IL12 from 5,000 in silico patients treated by the T-Cell therapy; and 2) test the synergistic effect of simultaneous inhibitions of multiple cytokines on reducing CRS. Specifically, a local sensitivity analysis was conducted to determine the most sensitive parameters out of the 90 parameters in the model. Each parameter was changed -50% and 50% and the change of the peak values of all 9 cytokines was recorded. Parameters were then ranked based on their sensitivity values. It is found that 7 of 10 of the most sensitive parameters in the model were related to IL12 and IL12 coupling with other cytokines. This gave insight to look into IL12 interactions. From the learnings of the sensitivity analysis, a Monte Carlo simulation was conducted with variation in these 10 parameters to simulate 5,000 in-silico patients and obtain the corresponding peak cytokine levels. The results enabled the team to conduct a principal component analysis (PCA) as well as hierarchical clustering, which is different from the original model developed in the Yiu article (6). The original article looked at the wave function profile of just the patients from the clinical trial, while this PCA took a look at the variation in the in-silico patients generated in MATLAB. In addition, the PCA enabled the team to utilize current drugs out on the market to simulate in-silico individual cytokine knockouts using the model from the original Yiu paper. The results demonstrate the effect that IL2 and IL6 have on the relationship with other cytokines, which confirms the positive and negative relationships from other models and literature reviews (5).
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