Development of a Quantitative Systems Pharmacology (QSP) Model of the Complement System Capturing Crosstalk Between the Classical and Alternative Pathways

Objectives: The complement system, traditionally known for its role in pathogen clearance, is a crucial mediator of innate immunity and also a key modulator of the tumor microenvironment [ 1, 2]. The classical and alternative pathways are central to this process, with the alternative pathway acting as a major amplification loop that enhances the formation of downstream complement components [ 3]. A mechanistic understanding of these pathways and their regulation is essential for designing effective complement-targeted therapies. The goal of this study is to develop a mechanistic quantitative systems pharmacology (QSP) model of the in-vitro complement system that captures the dynamic interplay between the classical and alternative pathways when co-activated. Moreover, the model aims at evaluating the effect of membrane-bound complement regulatory proteins (mCRPs) and to identify key model parameters through parameter sensitivity analysis. Methods: A comprehensive QSP model was constructed based on literature-derived biochemical reactions of both classical and alternative pathways [ 4]. The model captures the dynamics of key components, including C3/C5 convertases and terminal pathway proteins and integrates known activators, regulators, and feedback mechanisms to simulate complement activation. Parameter values were obtained from literature and calibrated against experimental data where available. Sensitivity analysis was performed to identify parameters with the highest impact on pathway outputs. Results: The model reproduced characteristic activation profiles of both individual and combined pathway stimulations. It successfully captured the self-amplifying behavior of the alternative pathway and demonstrated how its amplification loop enhances overall complement activation as observed in experimental works [ 5]. When both pathways were co-activated, the model predicted a synergistic increase in effector molecules such as C3/C5 convertases and the membrane attack complex (MAC), exceeding the sum of individual responses. Using sensitivity analysis, we identified key modulators of system behavior. Conclusions: This QSP model provides a comprehensive and mechanistically grounded framework for studying complement activation and regulation. It highlights the critical role of the alternative pathway’s amplification loop and reveals synergistic interactions when classical and alternative pathways are simultaneously engaged. The sensitivity analysis offers insights into potential therapeutic targets and supports the model’s utility in simulating complement-driven responses in health and disease.