Modeling and Parameter Subset Selection for Fibrin Polymerization Kinetics with Applications to Wound Healing

Area of Science:

• Biophysics
• Biochemistry
• Computational Biology

Background:

• Fibrin polymerization is essential for hemostasis and wound healing, involving fibrinogen conversion to fibrin by thrombin.
• Understanding fibrin matrix formation dynamics is critical for studying coagulation and bleeding disorders.

Purpose of the Study:

• To develop a cooperative enzyme kinetics model for in vitro fibrin matrix polymerization.
• To create a parameter subset selection technique for evaluating parameter identifiability in fibrin accumulation experiments.

Main Methods:

• Developed a kinetic model capturing interactions between fibrinogen, thrombin, fibrin, and intermediate complexes.
• Employed systematic analysis of eigenvalues/eigenvectors of the information matrix for parameter identifiability.
• Utilized a least squares objective function for optimization and simulations of fibrin accumulation.

Main Results:

• The developed approach significantly reduced objective function cost compared to traditional curve-fitting.
• Demonstrated the ability to integrate data subsets to enhance parameter identifiability evaluation.
• Successfully screened unidentifiable reaction rate parameters, enabling model simplification while maintaining low objective cost.

Conclusions:

• A single fibrin accumulation curve contains substantial information for kinetic modeling.
• The tailored model and parameter subset selection approach improves optimization and reduces complexity in polymerization studies.