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Abstract
In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy.
Highlights
The need to develop a virtual physiological human for clinical and pharmacological applications has stimulated the development of several physiological models that capture the interplay between different structures in tissues, organs, and the whole body (Fenner et al, 2008)
We focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model
Hunt and Ropella (2008) and Wambaugh and Shah (2010) made a comprehensive model for simple cells with a simple metabolism and developed a model that allows an estimation of the substance distribution in the lobule assuming that its structure resembles a network where each hepatocyte is located in each node of the network
Summary
The need to develop a virtual physiological human for clinical and pharmacological applications has stimulated the development of several physiological models that capture the interplay between different structures in tissues, organs, and the whole body (Fenner et al, 2008). Hunt and Ropella (2008) and Wambaugh and Shah (2010) made a comprehensive model for simple cells with a simple metabolism and developed a model that allows an estimation of the substance distribution in the lobule assuming that its structure resembles a network where each hepatocyte is located in each node of the network. Based on this description, the spatial distribution of the substance can be reproduced from the portal to the central vein. Only a few models have recently taken steps toward the integration of detailed cell mechanisms
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