Abstract
Computational models of liver metabolism are gaining an increasing importance within the research community. Moreover, their first clinical applications have been reported in recent years in the context of personalised and systems medicine. Herein, we survey selected experimental models together with the computational modelling approaches that are used to describe the metabolic processes of the liver in silico. We also review the recent developments in the large-scale hepatic computational models where we focus on object-oriented models as a part of our research. The object-oriented modelling approach is beneficial in efforts to describe the interactions between the tissues, such as how metabolism of the liver interacts with metabolism of other tissues via blood. Importantly, this modelling approach can account as well for transcriptional and post-translational regulation of metabolic reactions which is a difficult task to achieve. The current and potential clinical applications of large-scale hepatic models are also discussed. We conclude with the future perspectives within the systems and translational medicine research community.
Highlights
Novel high throughput technologies and advanced computation impact the medicine quickly and influentially
The disease is manifested by a spectrum of liver pathologies ranging from simple steatosis to liver cell injury with fibrosis and can end in cirrhosis or liver cancer
Non-alcoholic fatty liver disease (NAFLD) presents an initial step of a serious condition called non-alcoholic steatohepatitis (NASH), which includes fibrosis and is the fastest growing cause of HCC.[3]
Summary
Novel high throughput technologies and advanced computation impact the medicine quickly and influentially. We still face a number of multifactorial diseases where the diagnosis and treatment remain a hurdle This is the case as well for the multifactorial liver pathologies where the combinations of poorly defined genetic factors, together with environmental factors, interplay with each other and result in distinct disease phenotypes. Due to individuality of humans and the combinatorial effects, it is virtually impossible to predict all combinations that can lead to a liver disease phenotype It appears that in each individual a different combination of genetic and environmental factors might be responsible for the multifactorial disease appearance and progression. At present we do not understand the mechanisms and pathways that define a particular liver disease stage, we cannot predict the fate of disease progression nor can we treat NAFLD To solve such complex questions we must apply innovative systems solutions that in addition to experimentation include modelling and validation in clinical samples. These will be described in more details in the following chapters of the paper
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