Type 2 diabetes is a metabolic disease that profoundly affects energy homeostasis. The disease involves failure at several levels and subsystems and is characterized by insulin resistance in target cells and tissues (i.e. by impaired intracellular insulin signaling). We have previously used an iterative experimental-theoretical approach to unravel the early insulin signaling events in primary human adipocytes. That study, like most insulin signaling studies, is based on in vitro experimental examination of cells, and the in vivo relevance of such studies for human beings has not been systematically examined. Herein, we develop a hierarchical model of the adipose tissue, which links intracellular insulin control of glucose transport in human primary adipocytes with whole-body glucose homeostasis. An iterative approach between experiments and minimal modeling allowed us to conclude that it is not possible to scale up the experimentally determined glucose uptake by the isolated adipocytes to match the glucose uptake profile of the adipose tissue in vivo. However, a model that additionally includes insulin effects on blood flow in the adipose tissue and GLUT4 translocation due to cell handling can explain all data, but neither of these additions is sufficient independently. We also extend the minimal model to include hierarchical dynamic links to more detailed models (both to our own models and to those by others), which act as submodules that can be turned on or off. The resulting multilevel hierarchical model can merge detailed results on different subsystems into a coherent understanding of whole-body glucose homeostasis. This hierarchical modeling can potentially create bridges between other experimental model systems and the in vivo human situation and offers a framework for systematic evaluation of the physiological relevance of in vitro obtained molecular/cellular experimental data.

The Systems Biology Markup Language (SBML) is the leading modelling language within systems biology. It is a computer-readable format for representing models of biochemical reaction networks in software. SBML has been evolving since 2000 thanks to an international community of software developers and users. At the same time the Modelica language has evolved as the leading object-oriented modelling language for convenient, componentoriented modelling of complex physical systems. Modelica to SBML TranslatorA translator that converts Modelica to SBML [3], and vice versa, has been developed. The translator is able to convert SBML models that are compliant with SBML Level 2, version 3. The Modelica models created are Modelica 2.2 and 3 compliant. Modelica models are translated to SBML Level 2, version 1, 2 or 3. SBMLSBML is based on XML, making it more suitable to read and write by computers than by humans. SBML is a model representation format for systems biology, created with an objective to become a common intermediate format for software tools. The idea is that a large support for SBML enables the use of a wide range of different tools without having to rewrite models. In principle, a SBML model consists of a number of components, describing biochemical enti-

Purpose: To build a semi-physiologically based pharmacokinetic model describing the uptake, metabolism and efflux of paclitaxel and its metabolites and investigate the effect of hypothetical genetic polymorphisms causing reduced uptake, metabolism or efflux in the pathway by model simulation and sensitivity analysis. Methods: A previously described intracellular pharmacokinetic model was used as a starting point for model development. Kinetics for metabolism, transport, binding and systemic and output compartments were added to mimic a physiological model with hepatic elimination. Model parameters were calibrated using constraints postulated as ratios of concentrations and amounts of metabolites and drug in the systemic plasma and output compartments. The sensitivity in kinetic parameters was tested using dynamic sensitivity analysis.

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