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Mathematical Modeling of Antihypertensive Therapy with Azilsartan Medoxomil on the Example of Clinical Data of a Real Patient. / Borodulina, A. D.; Kutumova, E. O.; Lifshits, G. I. et al.

In: Mathematical Biology and Bioinformatics, Vol. 18, No. 1, 2023, p. 228-250.

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Borodulina AD, Kutumova EO, Lifshits GI, Kolpakov FA. Mathematical Modeling of Antihypertensive Therapy with Azilsartan Medoxomil on the Example of Clinical Data of a Real Patient. Mathematical Biology and Bioinformatics. 2023;18(1):228-250. doi: 10.17537/2023.18.228

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Borodulina, A. D. ; Kutumova, E. O. ; Lifshits, G. I. et al. / Mathematical Modeling of Antihypertensive Therapy with Azilsartan Medoxomil on the Example of Clinical Data of a Real Patient. In: Mathematical Biology and Bioinformatics. 2023 ; Vol. 18, No. 1. pp. 228-250.

BibTeX

@article{28b9c123289e46de985f4a372b865cbb,
title = "Mathematical Modeling of Antihypertensive Therapy with Azilsartan Medoxomil on the Example of Clinical Data of a Real Patient",
abstract = "Hypertension is a pathology caused by increased systolic and/or diastolic blood pressure. The disease can be controlled by various antihypertensive drugs. This study simulates the response of the human cardiovascular and renal systems to the action of the angiotensin II receptor blocker azilsartan medoxomil, taking into account dual combinations of this drug with the thiazide diuretic hydrochlorothiazide, the β-blocker bisoprolol and the calcium channel blocker amlodipine. For this purpose, we consider an agent-based mathematical model of blood pressure regulation, previously developed in the BioUML software and including pharmacodynamic functions for hydrochlorothiazide, bisoprolol, and amlodipine. To simulate the effect of azilsartan, we extended the model with a dose-dependent constant that reduces the rate of binding of angiotensin II to AT1 receptors in accordance with the pharmacological action of the drug. The identification of this constant was carried out on the basis of known clinical trials of azilsartan. The model was tested on a population of virtual patients (equilibrium parametrizations of the model within the specified physiological constraints) with uncomplicated hypertension and uniformly distributed values of systolic/diastolic blood pressure and heart rate. Then, a methodological issue of adapting the model to the clinical parameters of a real patient was considered.",
keywords = "BioUML, antihypertensive drugs, arterial hypertension, cardiovascular system, renal system, virtual patients",
author = "Borodulina, {A. D.} and Kutumova, {E. O.} and Lifshits, {G. I.} and Kolpakov, {F. A.}",
note = "Публикация для корректировки.",
year = "2023",
doi = "10.17537/2023.18.228",
language = "English",
volume = "18",
pages = "228--250",
journal = "Mathematical Biology and Bioinformatics",
issn = "1994-6538",
publisher = "Institute of Mathematical Problems of Biology",
number = "1",

}

RIS

TY - JOUR

T1 - Mathematical Modeling of Antihypertensive Therapy with Azilsartan Medoxomil on the Example of Clinical Data of a Real Patient

AU - Borodulina, A. D.

AU - Kutumova, E. O.

AU - Lifshits, G. I.

AU - Kolpakov, F. A.

N1 - Публикация для корректировки.

PY - 2023

Y1 - 2023

N2 - Hypertension is a pathology caused by increased systolic and/or diastolic blood pressure. The disease can be controlled by various antihypertensive drugs. This study simulates the response of the human cardiovascular and renal systems to the action of the angiotensin II receptor blocker azilsartan medoxomil, taking into account dual combinations of this drug with the thiazide diuretic hydrochlorothiazide, the β-blocker bisoprolol and the calcium channel blocker amlodipine. For this purpose, we consider an agent-based mathematical model of blood pressure regulation, previously developed in the BioUML software and including pharmacodynamic functions for hydrochlorothiazide, bisoprolol, and amlodipine. To simulate the effect of azilsartan, we extended the model with a dose-dependent constant that reduces the rate of binding of angiotensin II to AT1 receptors in accordance with the pharmacological action of the drug. The identification of this constant was carried out on the basis of known clinical trials of azilsartan. The model was tested on a population of virtual patients (equilibrium parametrizations of the model within the specified physiological constraints) with uncomplicated hypertension and uniformly distributed values of systolic/diastolic blood pressure and heart rate. Then, a methodological issue of adapting the model to the clinical parameters of a real patient was considered.

AB - Hypertension is a pathology caused by increased systolic and/or diastolic blood pressure. The disease can be controlled by various antihypertensive drugs. This study simulates the response of the human cardiovascular and renal systems to the action of the angiotensin II receptor blocker azilsartan medoxomil, taking into account dual combinations of this drug with the thiazide diuretic hydrochlorothiazide, the β-blocker bisoprolol and the calcium channel blocker amlodipine. For this purpose, we consider an agent-based mathematical model of blood pressure regulation, previously developed in the BioUML software and including pharmacodynamic functions for hydrochlorothiazide, bisoprolol, and amlodipine. To simulate the effect of azilsartan, we extended the model with a dose-dependent constant that reduces the rate of binding of angiotensin II to AT1 receptors in accordance with the pharmacological action of the drug. The identification of this constant was carried out on the basis of known clinical trials of azilsartan. The model was tested on a population of virtual patients (equilibrium parametrizations of the model within the specified physiological constraints) with uncomplicated hypertension and uniformly distributed values of systolic/diastolic blood pressure and heart rate. Then, a methodological issue of adapting the model to the clinical parameters of a real patient was considered.

KW - BioUML

KW - antihypertensive drugs

KW - arterial hypertension

KW - cardiovascular system

KW - renal system

KW - virtual patients

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UR - https://www.mendeley.com/catalogue/b50908aa-3a94-344b-b64f-aeac563a2400/

U2 - 10.17537/2023.18.228

DO - 10.17537/2023.18.228

M3 - Article

VL - 18

SP - 228

EP - 250

JO - Mathematical Biology and Bioinformatics

JF - Mathematical Biology and Bioinformatics

SN - 1994-6538

IS - 1

ER -

ID: 59172833