Von Willebrand disease is one of the most severe inherited bleeding disorders in humans, characterized by qualitative and/or quantitative defects of the von Willebrand factor protein. Diagnosis is difficult due to the high heterogeneity of the disease. Pharmacokinetic models have been recently proposed and applied to help in the disease characterization and diagnosis. However, the complexity of the models requires long and invasive dynamic non-routine tests to be carried out on the subjects to achieve a statistically satisfactory estimate of the individual metabolic parameters. In this work, it is demonstrated how the use of basal clinical tests and a shorter dynamic clinical test may allow for the identification of a mechanistic model of the disease. An existing mechanistic model of von Willebrand disease has been modified to account for the basal tests, where new model equations are derived using response surface methodology. Results show a good agreement between the model response and the clinical data.

Towards the optimal design of a minimum set of clinical trials for the identification and characterization of VWD

TAVERNA, BEATRICE;Casonato, Alessandra;Bezzo, Fabrizio;
2018

Abstract

Von Willebrand disease is one of the most severe inherited bleeding disorders in humans, characterized by qualitative and/or quantitative defects of the von Willebrand factor protein. Diagnosis is difficult due to the high heterogeneity of the disease. Pharmacokinetic models have been recently proposed and applied to help in the disease characterization and diagnosis. However, the complexity of the models requires long and invasive dynamic non-routine tests to be carried out on the subjects to achieve a statistically satisfactory estimate of the individual metabolic parameters. In this work, it is demonstrated how the use of basal clinical tests and a shorter dynamic clinical test may allow for the identification of a mechanistic model of the disease. An existing mechanistic model of von Willebrand disease has been modified to account for the basal tests, where new model equations are derived using response surface methodology. Results show a good agreement between the model response and the clinical data.
2018
Computer Aided Chemical Engineering - 13th International Symposium on Process Systems Engineering (PSE 2018)
9780444642417
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3274449
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