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Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers
A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases. We used a systems model to better understand the effect of modulating various components on blood coagulation. A computational model of the coagulation network...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544053/ https://www.ncbi.nlm.nih.gov/pubmed/26312163 http://dx.doi.org/10.1002/psp4.50 |
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author | Nayak, S Lee, D Patel-Hett, S Pittman, DD Martin, SW Heatherington, AC Vicini, P Hua, F |
author_facet | Nayak, S Lee, D Patel-Hett, S Pittman, DD Martin, SW Heatherington, AC Vicini, P Hua, F |
author_sort | Nayak, S |
collection | PubMed |
description | A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases. We used a systems model to better understand the effect of modulating various components on blood coagulation. A computational model of the coagulation network was built to match in-house in vitro thrombin generation and activated Partial Thromboplastin Time (aPTT) data with various concentrations of recombinant factor VIIa (FVIIa) or factor Xa added to normal human plasma or factor VIII-deficient plasma. Sensitivity analysis applied to the model revealed that lag time, peak thrombin concentration, area under the curve (AUC) of the thrombin generation profile, and aPTT show different sensitivity to changes in coagulation factors’ concentrations and type of plasma used (normal or factor VIII-deficient). We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment. |
format | Online Article Text |
id | pubmed-4544053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-45440532015-08-26 Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers Nayak, S Lee, D Patel-Hett, S Pittman, DD Martin, SW Heatherington, AC Vicini, P Hua, F CPT Pharmacometrics Syst Pharmacol Original Articles A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases. We used a systems model to better understand the effect of modulating various components on blood coagulation. A computational model of the coagulation network was built to match in-house in vitro thrombin generation and activated Partial Thromboplastin Time (aPTT) data with various concentrations of recombinant factor VIIa (FVIIa) or factor Xa added to normal human plasma or factor VIII-deficient plasma. Sensitivity analysis applied to the model revealed that lag time, peak thrombin concentration, area under the curve (AUC) of the thrombin generation profile, and aPTT show different sensitivity to changes in coagulation factors’ concentrations and type of plasma used (normal or factor VIII-deficient). We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment. John Wiley & Sons, Ltd 2015-07 2015-06-19 /pmc/articles/PMC4544053/ /pubmed/26312163 http://dx.doi.org/10.1002/psp4.50 Text en © 2015 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Articles Nayak, S Lee, D Patel-Hett, S Pittman, DD Martin, SW Heatherington, AC Vicini, P Hua, F Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title | Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title_full | Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title_fullStr | Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title_full_unstemmed | Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title_short | Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers |
title_sort | using a systems pharmacology model of the blood coagulation network to predict the effects of various therapies on biomarkers |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544053/ https://www.ncbi.nlm.nih.gov/pubmed/26312163 http://dx.doi.org/10.1002/psp4.50 |
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