Reduced order modeling and analysis of the human complement system.

Area of Science:

• Immunology
• Computational Biology
• Systems Biology

Background:

• The complement system is vital in innate immunity, inflammation, and disease pathogenesis.
• Existing mathematical models of complement activation are often complex and lack experimental validation.
• There is a need for computationally inexpensive and predictive models of complement pathways.

Purpose of the Study:

• To develop and validate a reduced-order mathematical model for complement activation.
• To create a computationally efficient model integrating ordinary differential equations and logical rules.
• To analyze the robustness of complement activation to therapeutic interventions.

Main Methods:

• Developed a hybrid model combining ordinary differential equations with logical rules.
• Modeled the lectin and alternative pathways of complement activation.
• Estimated model parameters using in vitro dynamic measurements of C3a and C5a.
• Validated the model using independent experimental data.

Main Results:

• The developed model is an order of magnitude smaller than comparable existing models.
• The model accurately described experimental data for C3a and C5a formation.
• Global sensitivity analysis revealed complement activation is robust to single-point interventions.
• Simultaneous knockdown of C3 and C5 was predicted to effectively reduce C3a and C5a production.

Conclusions:

• A validated, computationally inexpensive mathematical model of complement activation was successfully developed.
• The model can be readily integrated into pharmacokinetic or immune system models.
• The findings suggest that comprehensive disruption of complement activation necessitates multi-target therapeutic strategies, specifically involving C3 and C5.