Nonlinear Model Predictive Control For Circadian Entrainment Using Small-Molecule Pharmaceuticals.

Area of Science:

• Chronobiology
• Pharmacology
• Computational Biology

Background:

• Mammalian circadian clocks regulate daily physiological rhythms.
• Light is the primary external cue for circadian clock entrainment.
• Small-molecule pharmaceuticals offer a novel, less invasive method for circadian clock control.

Purpose of the Study:

• To develop and evaluate a mechanistic model for predicting circadian oscillator phase dynamics under pharmaceutical influence.
• To design a constrained model predictive controller (MPC) for optimizing drug dosing for circadian clock re-entrainment.
• To investigate the impact of drug-specific phase response curves (PRCs) on controller performance.

Main Methods:

• Development of a mechanistic model to simulate mammalian circadian oscillator phase dynamics.
• Formulation of a constrained model predictive controller (MPC) informed by mechanistic model predictions.
• In-silico experiments to test the efficacy of the MPC under varying conditions and drug-specific PRCs.

Main Results:

• The mechanistic model accurately predicts phase dynamics influenced by pharmaceuticals.
• The constrained MPC effectively computes dosing strategies for clock re-entrainment.
• Non-intuitive phase response effects due to oscillator nonlinearity necessitate careful controller tuning.
• Optimal phase manipulation requires MPC parameter adjustment based on drug-specific PRCs.

Conclusions:

• Pharmaceuticals represent a promising, less invasive approach to circadian clock manipulation.
• Model predictive control, informed by mechanistic models and drug-specific PRCs, is essential for precise circadian clock re-entrainment.
• Tuning MPC parameters to individual drug PRCs is critical for successful therapeutic outcomes.