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

Karin Leiderman; Suzanne S. Sindi; Dougald M. Monroe; Aaron L. Fogelson; Keith B. Neeves

doi:10.1055/s-0041-1722861

Seminars in Thrombosis and Hemostasis, Inhaltsverzeichnis

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

¹Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado

,

Suzanne S. Sindi

²Department of Applied Mathematics, University of California, Merced, Merced, California

,

Dougald M. Monroe

³Department of Medicine, UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina

,

Aaron L. Fogelson

⁴Departments of Mathematics and Biomedical Engineering, University of Utah, Salt Lake City, Utah

,

Keith B. Neeves

⁵Department of Bioengineering, Department of Pediatrics, Section of Hematology, Oncology, and Bone Marrow Transplant, Hemophilia and Thrombosis Center, University of Colorado, Denver, Colorado

› Institutsangaben

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.

Keywords

blood coagulation - platelets - hemodynamics - theoretical models - computer simulation

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