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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Nature Portfolio
2025-07-01
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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. |
| format | Article |
| id | doaj-art-aa045a4f9ea54a7a8effedd0cf1784fc |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| 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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