Background and Aims: Hyperammonemia after drug-induced peri-central liver lobule damage, as from overdosing acetaminophen (paracetamol), and can lead to encephalopathy and dead of the patient. Guided by mathematical models, the consensus set of chemical reactions for detoxification of liver from ammonia has recently been shown to fail in explaining ammonia-detoxification after drug-induced peri-central damage (Schliess et. al., 2014). Our aim is to demonstrate how integrated and spatial-temporal models mimicking detoxification of the blood from ammonia in virtual tissue samples can assist in guiding identification of missing molecular mechanisms, or predicting the impact of micro-architectural alterations due to acute or chronic damage on ammonia detoxification. Our modeling methodology is very general.
Method:The consensus and alternative detoxification mechanisms have been implemented within mathematical integrated and spatial-temporal multi-scale models to test various hypotheses on potentially missing mechanisms in ammonia detoxification during liver regeneration after drug-induced pericentral damage in silicoin a virtual liver lobule (Drasdo et. al., J. Hepat. 2014).
The multi-scale model simulates blood flow and molecular transport in the spatial lobule micro-architecture and displays each individual hepatocyte in space and time. Detoxification reactions are executed in each virtual hepatocyte. This makes in silicotesting of hypothesized mechanisms feasible from the molecular up to the tissue scale. The results are directly compared to experiments in mouse. Finally, fibrotic streets have been added to the model to predict the possible impact of architectural distortions and micro-shunts.
Results:We demonstrate how multiscale and multilevel models guided experiments towards identification of a previously unrecognized ammonia detoxification mechanism, that has the potential of improving treatment in hyperammonemia (Ghallab et. al., J. Hepat. 2016). The same model predicts for CCl4-induced fibrosis a reduced detoxification capacity for ammonia. Finally we outline how the whole body scale can be included to arrive at a model spanning molecular up to whole body scale permitting to study the relation of molecular changes and micro-architecture on whole body blood circulation, and briefly summarize results of integration of APAP toxic pathway as HGF signaling.
Conclusion:Refined multi-scale models increasingly permit realistic prediction of liver function as well as of toxic injury in acute and chronic damage states. Those models can integrate data from various sources, in vitro, different animal models or human data. The direct representation of liver micro-architecture in those models will open up the future perspective to feed these models with patient-specific data, hence generating a virtual twin of a patients’ liver to guide personalized diagnosis and therapy planning.
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