A Model-Based Investigation of Cytokine Storm for T-Cell Therapy. Issue 19 (2018)

• Record Type: Journal Article
• Authors: Hopkins, Brooks; Tucker, Matthew; Pan, Yiming; Fang, Nan; Huang, Zuyi (Jacky)
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 19(2018)
• Page Start: 76
• Page End: 79
• Publication Date: 2018
• Subjects: immunotherapy -- cytokine release syndrome -- sensitivity analysis -- Monte Carlo simulation -- principal component analysis; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.09.039
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: CAR-T cell therapy is a novel therapy which is used to treat blood-cancers like acute lymphoblastic leukemia. On the other hand, post-infusion of CAR-T cells yields increasing blood cytokine concentrations that rise proportionally to the immune system's response and cause the life-threatening side-effect called Cytokine Release Syndrome (CRS). Modern medical equipment has the capability to quantify cytokine concentrations which can be used to alert doctors what degree of inflammation the body is experiencing. Based on a mathematical model that can quantify the dynamics of 9 major cytokines for T cell therapy, we investigated the uncertainties of cytokines among patients using sensitivity analysis, Monte Carlo simulation, and principal component analysis. The efficacy of combined IL6 and IL2 inhibitors was also evaluated in this work. The simulation results show that IL12, different from other cytokines (including IFN-γ, IL1, IL8, TNFα, IL6, and IL2), has a small magnitude and uncertainty in its peak concentration during CRS. Our result also indicated that the simultaneous knockout of IL6 and IL2 can help patients recover from CRS faster. The simulation results from this work can be used to generate hypotheses to optimize cytokine inhibition approaches in future experiment research.