Related Experiment Video

Updated: Oct 8, 2025

Author Spotlight: Advancing Thrombolytic Testing by Integrating Flow Dynamics in In Vitro Models
06:16

Author Spotlight: Advancing Thrombolytic Testing by Integrating Flow Dynamics in In Vitro Models

Published on: April 19, 2024

1.2K

The Utility and Potential of Mathematical Models in Predicting Fibrinolytic Outcomes

Brittany E Bannish1,2, Nathan E Hudson3

  • 1Department of Mathematics and Statistics, University of Central Oklahoma, Edmond, OK 73034, USA.

Current Opinion in Biomedical Engineering
|December 27, 2021
PubMed

The enzymatic degradation of blood clots, fibrinolysis, is an important part of a healthy hemostatic system. If intrinsic fibrinolysis is ineffective, thrombolysis - the clinically-induced enzymatic degradation of blood clots - may be necessary to treat life-threatening conditions. In this review we discuss recent models of fibrinolysis and thrombolysis, and open questions that could be resolved through modeling and modeling-experimental collaboration. In particular, we focus on 2- and 3-dimensional models that can be used to study effects of fibrin network structure and realistic blood vessel geometries on the phenomena underlying lytic outcomes. Significant open questions such as the role of clot contraction, network and inherent fiber tension, and fibrinolytic inhibitors in lysis could benefit from mathematical models aimed at understanding the underlying biological mechanisms.

Keywords:
clot contractionfiber tensionfibrinolysisinhibitorsmathematical modelthrombolysis

More Related Videos

Experimental and Imaging Techniques for Examining Fibrin Clot Structures in Normal and Diseased States07:09

Experimental and Imaging Techniques for Examining Fibrin Clot Structures in Normal and Diseased States

Published on: April 1, 2015

11.6K
A Fibrin-Enriched and tPA-Sensitive Photothrombotic Stroke Model09:42

A Fibrin-Enriched and tPA-Sensitive Photothrombotic Stroke Model

Published on: June 4, 2021

3.0K

Related Concept Videos

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.3K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
168
Clot Retraction and Fibrinolysis01:16

Clot Retraction and Fibrinolysis

After a fibrin clot is formed, the next step is clot retraction, a vital process facilitated by platelet contractile proteins, such as actin and myosin. These proteins pull the fibrin strands closer together and condense the clot. This action reduces the size of the clot, creating a smaller, denser structure that effectively seals off the damaged vessel. Clot retraction consolidates the clot and helps with wound healing by bringing the edges of the damaged blood vessel closer together.
7.4K
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
167
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
140
Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
99