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The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity).
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Computational models provide insight into how mental representations might be organized and transformed.
Additionally, univariate models provided insight on the magnitude and direction of NTZ effects.
More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters.
Full kinetic models provide insight into enzyme mechanism and kinetics and also support bioconversion process design and feasibility assessment.
QSAR and molecular docking models provide insight into the mechanism of inhibition and indicate the optimal direction of future synthetic efforts.
Animal models provide insight into psychosomatic factors in diabetes.
The migratory nature of antigen-stimulated LCs has been well characterized in rodent models, providing insight into the behavior of this cell type [14], [15].
Both models provide insight into the syndrome.
Models provide insight into the effect of interventions given a set of underlying mechanistic assumptions.
4, 5 Simulations with PBPK models provide insight on appropriate dosage regimens to be used.
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