Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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. и др.
в: Mathematical Biology and Bioinformatics, Том 18, № 1, 2023, стр. 228-250.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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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
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85168605951&origin=inward&txGid=9baab8ac6bc0b785766ada6f0d8f61cc
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