DECISION-SUPPORT INDICATORS FOR SIMULATION-BASED EVALUATION OF INDIVIDUALIZED LEVODOPA DOSING IN PARKINSON’S DISEASE

Information from the abstract

This paper presents a simulation-based decision-support framework for evaluating individualized levodopa dosing strategies in Parkinson’s disease. Building on pharmacokinetic–pharmacodynamic simulation, the study organizes model outputs into interpretable decision indicators that compare alternative schedules under patient variability. The pharmacokinetic–pharmacodynamic component describes gastrointestinal absorption, central and peripheral distribution, elimination, effect-site exposure, and nonlinear therapeutic response. Representative dosing schedules are evaluated using peak–trough fluctuation, mean effect-site exposure, time within a therapeutic reference window, response deviation, exposure variability, and an overall decision score. Numerical simulations illustrate how changes in dose size, dosing interval, and dose fractionation may alter exposure–response patterns and decision-indicator profiles. Under the selected parameter setting and equal-weight decision score, the standard four-hour schedule gives the lowest overall decision score among the three representative schedules. The framework is intended for scenario-based interpretation and hypothesis generation rather than direct clinical prescription. It provides a computational basis for future model-informed and data-driven approaches to personalized Parkinson’s disease treatment.

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Related topics: Parkinson's Disease Mechanisms and Treatments · Statistical Methods in Clinical Trials · Optimal Experimental Design Methods