Abstract
As measurement devices become more sophisticated, it is possible to design more complex input-output studies, i.e., studies where data are obtained from several sites in the system under study. To interpret the resulting data requires models which can integrate known information about the system under study while simultaneously describing the data. In this chapter, we will illustrate how to develop and test a model structure for a single-input multiple-output study using the SAAM II software system. This system has been designed to make the use of sound modeling principles easy.
It will be assumed that a known amount of a radiolabeled substance was injected as a bolus into plasma, that this substance can bind to and be taken up by red cells, that its. only route of elimination is through the urine, and that external measurements are possible over a target organ. The steps in developing a model structure will make use of SAAM II’s forcing function capability to show how the system can be decoupled; this will permit us to postulate model structures for the various subsystems accessible to measurement. We will then show how to use this information to postulate a model describing all the data, and how to test this model structure. This will permit us to comment on those parts of the system not accessible for experimental measurement. We will end with a general discussion of how to test for goodness-of-fit and model order.
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© 1998 Springer Science+Business Media New York
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Foster, D.M. (1998). Developing and Testing Integrated Multicompartment Models to Describe a Single-Input Multiple-Output Study Using the SAAM II Software System. In: Clifford, A.J., Müller, HG. (eds) Mathematical Modeling in Experimental Nutrition. Advances in Experimental Medicine and Biology, vol 445. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1959-5_4
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DOI: https://doi.org/10.1007/978-1-4899-1959-5_4
Publisher Name: Springer, Boston, MA
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