CC BY-NC-ND 4.0 · Semin Thromb Hemost 2021; 47(02): 129-138
DOI: 10.1055/s-0041-1722861
Review Article

The Art and Science of Building a Computational Model to Understand Hemostasis

Karin Leiderman
1  Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado
,
Suzanne S. Sindi
2  Department of Applied Mathematics, University of California, Merced, Merced, California
,
Dougald M. Monroe
3  Department of Medicine, UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
,
Aaron L. Fogelson
4  Departments of Mathematics and Biomedical Engineering, University of Utah, Salt Lake City, Utah
,
Keith B. Neeves
5  Department of Bioengineering, Department of Pediatrics, Section of Hematology, Oncology, and Bone Marrow Transplant, Hemophilia and Thrombosis Center, University of Colorado, Denver, Colorado
› Author Affiliations
Funding This work was supported in part by the National Institutes of Health (R01HL120728, R01HL151984), the National Science Foundation (CBET-1351672, DMS-1848221), and the Army Research Office (ARO-12369656).

Abstract

Computational models of various facets of hemostasis and thrombosis have increased substantially in the last decade. These models have the potential to make predictions that can uncover new mechanisms within the complex dynamics of thrombus formation. However, these predictions are only as good as the data and assumptions they are built upon, and therefore model building requires intimate coupling with experiments. The objective of this article is to guide the reader through how a computational model is built and how it can inform and be refined by experiments. This is accomplished by answering six questions facing the model builder: (1) Why make a model? (2) What kind of model should be built? (3) How is the model built? (4) Is the model a “good” model? (5) Do we believe the model? (6) Is the model useful? These questions are answered in the context of a model of thrombus formation that has been successfully applied to understanding the interplay between blood flow, platelet deposition, and coagulation and in identifying potential modifiers of thrombin generation in hemophilia A.

Note

[Figure 1] and [Table 1] schematic were created with BioRender.com.




Publication History

Publication Date:
26 February 2021 (online)

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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