Monitoring the coagulation time and regulating the administration of unfractionated heparin (UFH) during cardiopulmonary bypass (CPB) are challenging activities. The manuscript focuses on the development of a mathematical model to predict the activated clotting time (ACT) during CPB following an intravenous administration of heparin. The overall mathematical tool features a physiologically-based pharmacokinetic (PBPK) model and a pharmacodynamic (PD) model. The PBPK model describes the human circulatory system and employs correlations from the literature to estimate its physiological parameters from individual characteristics (i.e. age, sex, race, weight, height, serum creatinine, and hematocrit) to yield a prediction of heparin plasma concentration as a function of time. The PD model predicts the ACT as a function of heparin concentration thanks to several differential equations that describe the coagulation cascade. The combined PBPK/PD model produces, for each patient, an individualized prediction of the resulting ACT dynamics, using either a population or an individualized approach. The model can be used to help monitoring the ACT trend during CPB and to optimize heparin administration in order to reach and maintain the therapeutic goal of 480 s.

Physiologically-Based Pharmacokinetic and Pharmacodynamic Modeling of Unfractionated Heparin to Predict Activated Clotting Time

Pesenti, G.;Manca, D.
2020-01-01

Abstract

Monitoring the coagulation time and regulating the administration of unfractionated heparin (UFH) during cardiopulmonary bypass (CPB) are challenging activities. The manuscript focuses on the development of a mathematical model to predict the activated clotting time (ACT) during CPB following an intravenous administration of heparin. The overall mathematical tool features a physiologically-based pharmacokinetic (PBPK) model and a pharmacodynamic (PD) model. The PBPK model describes the human circulatory system and employs correlations from the literature to estimate its physiological parameters from individual characteristics (i.e. age, sex, race, weight, height, serum creatinine, and hematocrit) to yield a prediction of heparin plasma concentration as a function of time. The PD model predicts the ACT as a function of heparin concentration thanks to several differential equations that describe the coagulation cascade. The combined PBPK/PD model produces, for each patient, an individualized prediction of the resulting ACT dynamics, using either a population or an individualized approach. The model can be used to help monitoring the ACT trend during CPB and to optimize heparin administration in order to reach and maintain the therapeutic goal of 480 s.
2020
30th European Symposium on Computer Aided Process Engineering
978-0-12-823377-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1158087
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