Coping with time scales in disease systems analysis: application to bone remodeling

Area of Science:

• Biomathematics
• Systems biology
• Bone physiology

Background:

• Complex dynamic systems require accurate mathematical models for characterization.
• Bone remodeling is a complex physiological process influenced by various factors.
• Existing mechanistic models can be computationally intensive.

Purpose of the Study:

• To demonstrate the value of mathematical model reduction for dynamic systems.
• To simplify the Lemaire et al. RANK-RANKL-OPG bone remodeling model.
• To assess the reduced model's ability to represent physiological changes and interventions.

Main Methods:

• Model reduction techniques applied to the Lemaire et al. mechanistic model.
• Comparative analysis of the full and reduced models.
• Simulation of four key physiological scenarios: estrogen changes, Vitamin D deficiency, aging, and glucocorticoid treatment.

Main Results:

• The reduced model approximates the full model's dynamics with high accuracy.
• Both models showed similar responses to physiological changes and therapeutic interventions.
• Negligible differences in dynamic properties were observed on relevant timescales.
• The simpler model aided in understanding qualitative dynamics like overshoot and washout.

Conclusions:

• Mathematical model reduction is valuable for characterizing complex dynamic systems like bone remodeling.
• The simplified RANK-RANKL-OPG model effectively represents bone cell dynamics under various conditions.
• Reduced models offer a computationally efficient approach for studying bone health and therapeutic impacts.