Document Type

Article

Source of Publication

Mathematical Biosciences and Engineering

Publication Date

7-22-2025

Abstract

This study introduces a novel multivariable optimal control framework for hemodialysis, which uniquely integrates five physiological states (blood urea concentration, fluid volume, blood pressure, electrolytes, and hemoglobin) with three clinically adjustable inputs (ultrafiltration rate, blood flow, and dialysate composition). By employing the limited-memory Broyden-Fletcher-Goldfarb-Shanno-B (L-BFGS-B) algorithm with patient-specific box constraints, the model enforces patient-specific physiological safety limits while dynamically balancing clinical targets. Numerical simulations demonstrate the stabilization of key parameters within ±5% of clinical benchmarks (e.g., KDIGO guidelines), though deviations in the hemodynamic responses underscore the need for adaptive control in real-world scenarios. Urea clearance trajectories align with efficacy patterns observed in practice, while blood pressure fluctuations reveal systematic offsets that require protocol refinement. This work bridges control theory with hemodialysis dynamics, thus offering a simulation-driven foundation for future clinical validation and personalized treatment optimization.

ISSN

1547-1063

Publisher

American Institute of Mathematical Sciences (AIMS)

Volume

22

Issue

9

First Page

2409

Last Page

2433

Disciplines

Physical Sciences and Mathematics

Keywords

hemodialysis modeling, L-BFGS-B algorithm, optimal control, personalized treatment, physiological variables

Scopus ID

105012203684

Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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