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.

There is a need to interpret in vitro concentration-viability data in terms of the actual concentration that the cells are exposed to, rather than the nominal concentration applied to the test system. We have developed a process-based model to simulate the kinetics and dynamics of a chemical compound in cell-based in vitro assays. In the present paper we describe the mathematical equations governing this model as well as the parameters that are needed to run the model. The Virtual Cell Based Assay (VCBA) is an integrated model composed of: [1] a fate and transport model; [2] a cell partitioning model; [3] a cell growth and division model; [4] a toxicity and effects model; [5] the experimental set up. The purpose of the VCBA is to simulate the medium and intracellular concentrations, which can be used on its own to design and interpret in vitro experiments, and in combination with physiologically based kinetic (PBK) models to perform in vitro to in vivo extrapolation. The results can be used in chemical risk assessment to link an external dose to an internal effect or vice versa, using solely in vitro and in silico tools and thereby avoiding animal testing.

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The threshold of toxicological concern (TTC) concept proposes that an exposure threshold value can be derived for chemicals, below which no significant risk to human health or the environment is expected. This concept goes further than setting acceptable exposure levels for individual chemicals, because it attempts to set a de minimis value for chemicals, including those of unknown toxicity, by taking the chemical's structure or mode of action (MOA) into consideration. This study examines the use of the TTC concern concept for endocrine active substances (EAS) with an estrogenic MOA. A case study formed the basis for a workshop of regulatory, industry and academic scientists held to discuss the use of the TTC in aquatic environmental risk assessment. The feasibility and acceptability, general advantages and disadvantages, and the specific issues that need to be considered when applying the TTC concept for EAS in risk assessment were addressed. Issues surrounding the statistical approaches used to derive TTCs were also discussed. This study presents discussion points and consensus findings of the workshop.

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