Integrating cellular and tissue dynamics with cell fate decisions through computational modeling

There is a need for alternative methods to replace, reduce and refine (3R) animal experimentation. Combining experimental data from high-throughput in vitro studies with in silico modeling is a promising approach to unravel the effect of chemicals on living cells and to gain a better understanding of the processes leading to adverse effects. Exposure to chemicals can activate various stress response pathways that limit the amount of cellular damage, help cells to recover or orchestrate irreversible cell fates such as apoptosis. In this thesis, we use experimental data and current knowledge on stress pathway activation and cell fate to create different types of computational models. With these models, we mathematically describe intracellular protein signaling cascades activated upon exposure to various compounds and their link to cell fate. In this way, we integrate molecular-level biological processes to cell-level phenomena such as cell cycle progression, senescence and necrosis, and generate new hypotheses about the mechanisms underlying adversity.Toxicolog