Modeling drug retention as memory effects in obese patients using fractional and augmented models

Abstract Lipophilic anesthetic drugs accumulate in adipose tissue, leading to delayed release and prolonged effects, particularly in obese patients. This study proposes two novel physiologically motivated pharmacokinetic (PK) models to address these dynamics. The first is an augmented model with a t...

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Main Authors: Amani R. Ynineb, Erhan Yumuk, Dana Copot, Bora Ayvaz, Bouchra Khoumeri, Ghada Ben Othman, Marcian D. Mihai, Isabela R. Birs, Cristina I. Muresan, Clara M. Ionescu
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Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-10172-1
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author Amani R. Ynineb
Erhan Yumuk
Dana Copot
Bora Ayvaz
Bouchra Khoumeri
Ghada Ben Othman
Marcian D. Mihai
Isabela R. Birs
Cristina I. Muresan
Clara M. Ionescu
author_facet Amani R. Ynineb
Erhan Yumuk
Dana Copot
Bora Ayvaz
Bouchra Khoumeri
Ghada Ben Othman
Marcian D. Mihai
Isabela R. Birs
Cristina I. Muresan
Clara M. Ionescu
author_sort Amani R. Ynineb
collection DOAJ
description Abstract Lipophilic anesthetic drugs accumulate in adipose tissue, leading to delayed release and prolonged effects, particularly in obese patients. This study proposes two novel physiologically motivated pharmacokinetic (PK) models to address these dynamics. The first is an augmented model with a trap compartment to simulate retention, and the second is a fractional-order model using Partial-Caputo derivatives to capture memory effects. By applying a discrete-time Euler method to the augmented model, we reveal an inherent fading memory behavior, where the current drug release depends on a weighted influence of past drug concentrations in fat. Both models are integrated into a PK/PD framework. Their behavior is first explored in a single-input single-output (SISO) case using simulated Bispectral Index (BIS) responses under three common dosing protocols: single bolus, repeated boluses, and continuous infusion. Evaluation against real clinical data is then performed in a multiple-input single-output (MISO) case, where the simulated BIS responses are compared to recorded BIS measurements from a representative obese patient under total intravenous anesthesia (TIVA). During the awakening phase, both the augmented and fractional-order models reduce BIS prediction error compared to the classical model. The augmented model lowers RMSE by 22.5% (from 10.38 to 8.04), while the fractional model achieves a 21.4% reduction (to 8.16) (based on one obese patient case). Sensitivity analysis confirms the impact of the fractional-order parameter ( $$\alpha _{31}$$ ) on long-term BIS dynamics. These results and proposed models illustrate the potential role of memory-aware PK models for advanced patient-specific digital twin systems in healthcare.
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spelling doaj-art-aa045a4f9ea54a7a8effedd0cf1784fc2025-08-20T03:04:34ZengNature PortfolioScientific Reports2045-23222025-07-0115113510.1038/s41598-025-10172-1Modeling drug retention as memory effects in obese patients using fractional and augmented modelsAmani R. Ynineb0Erhan Yumuk1Dana Copot2Bora Ayvaz3Bouchra Khoumeri4Ghada Ben Othman5Marcian D. Mihai6Isabela R. Birs7Cristina I. Muresan8Clara M. Ionescu9Department of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityDepartment of Control and Automation Engineering, Istanbul Technical UniversityDepartment of Automation, Technical University of Cluj-NapocaDepartment of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityDepartment of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityDepartment of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityDepartment of Automation, Technical University of Cluj-NapocaDepartment of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityDepartment of Automation, Technical University of Cluj-NapocaDepartment of Electromechanics, Systems and Metal Engineering, Research Group on Dynamical Systems and Control, Ghent UniversityAbstract Lipophilic anesthetic drugs accumulate in adipose tissue, leading to delayed release and prolonged effects, particularly in obese patients. This study proposes two novel physiologically motivated pharmacokinetic (PK) models to address these dynamics. The first is an augmented model with a trap compartment to simulate retention, and the second is a fractional-order model using Partial-Caputo derivatives to capture memory effects. By applying a discrete-time Euler method to the augmented model, we reveal an inherent fading memory behavior, where the current drug release depends on a weighted influence of past drug concentrations in fat. Both models are integrated into a PK/PD framework. Their behavior is first explored in a single-input single-output (SISO) case using simulated Bispectral Index (BIS) responses under three common dosing protocols: single bolus, repeated boluses, and continuous infusion. Evaluation against real clinical data is then performed in a multiple-input single-output (MISO) case, where the simulated BIS responses are compared to recorded BIS measurements from a representative obese patient under total intravenous anesthesia (TIVA). During the awakening phase, both the augmented and fractional-order models reduce BIS prediction error compared to the classical model. The augmented model lowers RMSE by 22.5% (from 10.38 to 8.04), while the fractional model achieves a 21.4% reduction (to 8.16) (based on one obese patient case). Sensitivity analysis confirms the impact of the fractional-order parameter ( $$\alpha _{31}$$ ) on long-term BIS dynamics. These results and proposed models illustrate the potential role of memory-aware PK models for advanced patient-specific digital twin systems in healthcare.https://doi.org/10.1038/s41598-025-10172-1Fractional calculusPharmacokineticsCompartmental modelsMemory effectCaputo derivative
spellingShingle Amani R. Ynineb
Erhan Yumuk
Dana Copot
Bora Ayvaz
Bouchra Khoumeri
Ghada Ben Othman
Marcian D. Mihai
Isabela R. Birs
Cristina I. Muresan
Clara M. Ionescu
Modeling drug retention as memory effects in obese patients using fractional and augmented models
Scientific Reports
Fractional calculus
Pharmacokinetics
Compartmental models
Memory effect
Caputo derivative
title Modeling drug retention as memory effects in obese patients using fractional and augmented models
title_full Modeling drug retention as memory effects in obese patients using fractional and augmented models
title_fullStr Modeling drug retention as memory effects in obese patients using fractional and augmented models
title_full_unstemmed Modeling drug retention as memory effects in obese patients using fractional and augmented models
title_short Modeling drug retention as memory effects in obese patients using fractional and augmented models
title_sort modeling drug retention as memory effects in obese patients using fractional and augmented models
topic Fractional calculus
Pharmacokinetics
Compartmental models
Memory effect
Caputo derivative
url https://doi.org/10.1038/s41598-025-10172-1
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