Intravenous glucose tolerance tests (IVGTTs) are typically used to assess insulin resistance and insulin secretion activities in subjects affected by type 2 diabetes by adopting minimal models. However, the amount of information that can be obtained from IVGTTs for the purpose of model identification is intrinsically related to the dynamics triggered by the intravenous glucose infusion and to the individual specificity. This paper shows how the information content of clinical data from conventional IVGTTs can be handled by model-based design of experiments (MBDoE) techniques when the goal is to estimate the set of parameters of a complex model of type 2 diabetes. MBDoE allows to analyse and improve the information content of IVGTTs by optimising the sample allocation in such a way as to decrease the degree of correlation between critical parameters. © 2013 Elsevier B.V.

Identification of complex models of type 2 diabetes from IVGTT data by model-based design of experiments / Galvanin, F.; Barolo, M.; Bonadonna, R. C.; Bezzo, F.. - 32(2013), pp. 133-138. [10.1016/B978-0-444-63234-0.50023-3]

Identification of complex models of type 2 diabetes from IVGTT data by model-based design of experiments

Bonadonna R. C.;
2013

Abstract

Intravenous glucose tolerance tests (IVGTTs) are typically used to assess insulin resistance and insulin secretion activities in subjects affected by type 2 diabetes by adopting minimal models. However, the amount of information that can be obtained from IVGTTs for the purpose of model identification is intrinsically related to the dynamics triggered by the intravenous glucose infusion and to the individual specificity. This paper shows how the information content of clinical data from conventional IVGTTs can be handled by model-based design of experiments (MBDoE) techniques when the goal is to estimate the set of parameters of a complex model of type 2 diabetes. MBDoE allows to analyse and improve the information content of IVGTTs by optimising the sample allocation in such a way as to decrease the degree of correlation between critical parameters. © 2013 Elsevier B.V.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2885262
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