Optimal enhancement of immune response

Area of Science:

• Immunology
• Control Theory
• Mathematical Biology

Background:

• The innate immune response to microbial invasion is modeled using four non-linear ordinary differential equations.
• The model simulates pathogen, plasma cell, antibody concentrations, and organic health, predicting various outcomes without therapy.
• Therapeutic agents can augment immune response by targeting pathogens, stimulating immune cells, or enhancing organ health.

Purpose of the Study:

• To explore therapeutic enhancement of the innate immune response using optimal control theory.
• To demonstrate the effectiveness of neighboring-optimal feedback control in dynamic disease models.
• To investigate combined open-loop and closed-loop control strategies for disease treatment.

Main Methods:

• Utilizing a dynamic system model with four non-linear ordinary differential equations.
• Applying open-loop optimal control solutions to defeat pathogens and preserve health.
• Implementing neighboring-optimal feedback control to adapt therapies for unknown initial conditions and pathogen persistence.

Main Results:

• Neighboring-optimal feedback control effectively adjusts therapy in response to perturbations and unknown initial conditions.
• Combined therapies, integrating open-loop and closed-loop control, were examined.
• The study demonstrates the potential of optimal control theory to guide new disease treatment protocols.

Conclusions:

• Optimal control theory provides a framework for enhancing innate immune responses.
• Neighboring-optimal feedback control offers adaptive therapeutic strategies for dynamic biological systems.
• This research highlights the potential for developing novel treatment and cure protocols for human diseases.