All chronic hepatitis are associated with the development of fibrosis, which results in abnormal deposition of the extracellular matrix (ECM) leading to severe liver dysfunction. Fibrosis final stage, called cirrhosis, is the main risk of development of hepatocellular carcinoma (HCC). At the cellular level, hepatic stellate cells (HSCs) are major actors of fibrosis and tumor progression. Upon liver injury, HSCs are activated to repair tissue and are subsequently eliminated through three mechanisms: apoptosis, senescence and reversion, leading to a return to healthy status [5]. However, when the injury persists, HSCs remain activated with a myobroblastic phenotype, and extracellular matrix accumulates, leading to fibrosis, cirrhosis and cancer. Understanding the dynamics of HSC activation and their regulation by TGFB1 is essential to identify markers and therapeutic targets that may favor the resolution of fibrosis at the expense of its progression. For this purpose, we are developing a modelling approach using the Kappa language. Kappa is a rule-based language used for the rewriting of site graphs [1, 2, 4, 3] aiming at describing networks of interactions between occurrences of components, using a syntax inspired by chemistry. In this model, the components are occurrences of HSC in different states, and occurrences of the TGFB1 protein. Our preliminary results suggest a high plasticity of the HSC response to TGFB1 stimulation. Future work will focus on the integration of the ECM component networks that regulate TGFB1 availability. References: [1] O. Andrei and H. Kirchner. A rewriting calculus for multigraphs with ports. Electr. Notes Theor. Comput. Sci., 219:67–82, 2008. [2] V. Danos and C. Laneve. Formal molecular biology. Theoretical Computer Science, 325(1):69 – 110, 2004. Computational Systems Biology. [3] A. Ehrlich, D. Duche, G. Ouedraogo, and Y. Nahmias. Challenges and opportunities in the design of liver-on-chip microdevices. Annual Review of Biomedical Engineering, 21(1):219–239, 2019. PMID: 31167098. [4] J. R. Faeder, M. L. Blinov, B. Goldstein, and W. S. Hlavacek. Rule-based modeling of biochemical networks. Complexity, 10(4):22–41, 2005. [5] T. Kisseleva and D. Brenner. Molecular and cellular mechanisms of liver fibrosis and its regression. Nature Reviews Gastroenterology & Hepatology, pages 1–16, 2020.