Utilising an in silico model to predict outcomes in senescence-driven acute liver injury

Currently liver transplantation is the only treatment option for liver disease, but organ availability cannot meet demand and transplant recipients require lifelong immunosuppression. The identification of alternative treatments, e.g. cell therapies, able to tip resolution of injury from inflammation to regeneration requires an understanding of the host response to the degree of injury. We adopt a combined in vivo-in silico approach and develop a mathematical model of acute liver disease able to predict the host response to injury. We utilise the Mdm2fl/fl mouse model together with a single Cre induction through intravenous injection of the hepatotropic Adeno-associated Virus Serotype 8 Cre (AAV8.Cre) to model acute liver injury. We derive a complementary ordinary differential equation model to capture the dynamics of the key cell players in the injury response together with the extracellular matrix. We show that the mathematical model is able to predict the host response to moderate injury via qualitative comparison of the model predictions with the experimental data. We then use the model to predict the host response to mild and severe injury, and test these predictions in vivo , obtaining good qualitative agreement. ### Competing Interest Statement CAH, EA, RA, TYM, SMF, AS, WYL, VLG, SLW declare no conflicts of interest. SJF is a founder and scientific advisor of Resolution Therapeutics Ltd and SensiBile (not related to this study). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.