Literature DB >> 29948884

Evaluation and Calibration of In Silico Models of Thrombin Generation Using Experimental Data from Healthy and Haemophilic Subjects.

Pierre Chelle1, Claire Morin2, Aurélie Montmartin3, Michèle Piot3, Michel Cournil1, Brigitte Tardy-Poncet3.   

Abstract

The coagulation cascade comprises numerous chemical reactions between many proteins, that finally lead to the formation of a clot to stop bleeding. Many numerical models have attempted to translate understanding of this cascade into mathematical equations that simulate the chain reactions. However, their predictions have not been validated against clinical data stemming from patients. In this paper, we propose an extensive validation of five available models, by comparing in healthy and haemophilic subjects, thrombin generation measured in vitro to thrombin generation predicted by the models in silico. In order to render the models more predictive, we calibrated the models to have an acceptable agreement between the experimental and estimated data. Optimization processes based on genetic algorithms were developed to search for those calibrated kinetic parameters. Our results show that the thrombin generation kinetics are so complex that they cannot be predicted by a unique set of kinetic parameters for all patients: the calibration of only three parameters in a subject-specific way allows reaching good model estimations for different experimental conditions realized on the same patient.

Entities:  

Keywords:  Coagulation dynamics; Computational modelling. In vitro assay kinetics . Sensitivity analysis

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Year:  2018        PMID: 29948884     DOI: 10.1007/s11538-018-0440-4

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  2 in total

1.  Use of population PK/PD approach to model the thrombin generation assay: assessment in haemophilia A plasma samples spiked by a TFPI antibody.

Authors:  Raphaël Crépin; Claire Morin; Aurélie Montmartin; Brigitte Tardy-Poncet; Pierre Chelle
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-04-12       Impact factor: 2.745

2.  Patient-Specific Modelling of Blood Coagulation.

Authors:  N Ratto; A Bouchnita; P Chelle; M Marion; M Panteleev; D Nechipurenko; B Tardy-Poncet; V Volpert
Journal:  Bull Math Biol       Date:  2021-03-27       Impact factor: 1.758

  2 in total

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