Mathematical Modeling of Systemic Sclerosis and Its Treatment

Area of Science:

• Mathematical Biology
• Computational Biology
• Immunology

Background:

• Systemic sclerosis (SSc) is an autoimmune disease characterized by excessive extracellular matrix (ECM) deposition.
• Myofibroblast overpopulation drives SSc pathogenesis and potential organ damage, particularly in the lungs.
• Current therapeutic strategies explore myofibroblast reduction via imatinib (N) and TGF-β inhibition with fresolimumab (S).

Purpose of the Study:

• To develop and utilize a mathematical model to investigate the efficacy of different treatment strategies for SSc.
• To explore the impact of fractional administration of fresolimumab (S) on ECM density in SSc.
• To determine optimal dosing regimens for reducing ECM accumulation in SSc patients.

Main Methods:

• Development of a mathematical model using partial differential equations to simulate SSc.
• Simulation of treatment strategies involving imatinib (N) and fresolimumab (S).
• Analysis of ECM density (ρ(t)) dynamics under fractional fresolimumab administration.

Main Results:

• The model predicted that fractional fresolimumab (S) administration can lead to a continuous, oscillating decrease in ECM density.
• The smallest effective fractional dose of S was identified to reduce ECM density from 2ρ⁰ to approximately 1.19ρ⁰ within months.
• ECM density was shown to stabilize near 1.19ρ⁰, remaining above the healthy level (ρ⁰).

Conclusions:

• Mathematical modeling provides a framework for optimizing SSc treatment strategies.
• Fractional fresolimumab administration presents a viable approach to manage excessive ECM deposition in SSc.
• These findings can inform the design of future clinical trials for SSc therapeutics.