Modeling of pancreas-liver interaction under controlled hemodynamics
Autonomous software (AS) was created to simulate the dynamics of the glucose-insulin-glycogen-glucagon relationship in a healthy person. Our AS is based on a quantitative mathematical model consisting of three components: a model describing the pancreas-liver and the pancreas-skeletal muscles relati...
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|---|---|
| author | Grygoryan, R.D. Sinitsyn, I.P. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. Strutynska, N.A. |
| author_facet | Grygoryan, R.D. Sinitsyn, I.P. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. Strutynska, N.A. |
| author_institution_txt_mv | [
{
"author": "R.D. Grygoryan",
"institution": "Institute of Software Systems NAS of Ukraine"
},
{
"author": "I.P. Sinitsyn",
"institution": "Institute of Software Systems NAS of Ukraine"
},
{
"author": "A.G. Degoda",
"institution": "Institute of Software Systems NAS of Ukraine"
},
{
"author": "T.V. Lyudovyk",
"institution": "Institute of Software Systems NAS of Ukraine"
},
{
"author": "O.I. Yurchak",
"institution": "Institute of Software Systems NAS of Ukraine"
},
{
"author": "N.A. Strutynska",
"institution": "Institute of Software Systems NAS of Ukraine"
}
] |
| author_sort | Grygoryan, R.D. |
| baseUrl_str | https://pp.isofts.kiev.ua/index.php/ojs1/oai |
| collection | OJS |
| datestamp_date | 2026-06-29T10:43:50Z |
| description | Autonomous software (AS) was created to simulate the dynamics of the glucose-insulin-glycogen-glucagon relationship in a healthy person. Our AS is based on a quantitative mathematical model consisting of three components: a model describing the pancreas-liver and the pancreas-skeletal muscles relationships; a model describing blood circulation in the branched cardiovascular system, taking into account neurohumoral regu lators of cardiac function, vascular tone and total blood volume; and a model describing blood filtration in the renal glomeruli and tubular reabsorption. A glucose tolerance test (GTT) was also programmed. Test simulations demonstrated adequate model responses. The program is integrated into a specialized computer simulator (SCS). It allows studying mechanisms that, depending on the dynamics of exogenous and endoge nous physicochemical variables, dynamically form multidimensional health landscape of biometric indica tors. The effect of extreme blood flow increase on the dynamics of the main variables of the model was also simulated without additional carbohydrate intake. AS is created in C#, and can be delivered as an Exe module for IBM-compatible computers. Medical students can be additional users of the AP as an additional didactic tool. The AS ensures the preservation of all simulation data for future reviews and publications. The AS can be used by future endocrinologists in their training. Physiologists interested in the integrative physi ology of cellular life support are recommended to use the SCS.Problems in programming 2026; 2: 49-57 |
| first_indexed | 2026-06-30T01:00:16Z |
| format | Article |
| fulltext |
Комп’ютерне моделювання
49
УДК 517.958:57 +519.711.3 + 612.51.001 https://doi.org/10.15407/pp2026.02.049
R.D. Grygoryan, I.P. Sinitsyn, A.G. Degoda, T.V. Lyudovyk, O.I. Yurchak, N.A. Strutynska
MODELING OF PANCREAS-LIVER INTERACTION UNDER
CONTROLED HEMODYNAMICS
Autonomous software (AS) was created to simulate the dynamics of the glucose-insulin-glycogen-glucagon
relationship in a healthy person. Our AS is based on a quantitative mathematical model consisting of three
components: a model describing the pancreas-liver and the pancreas-skeletal muscles relationships; a model
describing blood circulation in the branched cardiovascular system, taking into account neurohumoral regu-
lators of cardiac function, vascular tone and total blood volume; and a model describing b lood filtration in
the renal glomeruli and tubular reabsorption. A glucose tolerance test (GTT) was also programmed. Test
simulations demonstrated adequate model responses. The program is integrated into a specialized computer
simulator (SCS). It allows studying mechanisms that, depending on the dynamics of exogenous and endoge-
nous physicochemical variables, dynamically form multidimensional health landscape of biometric indica-
tors. The effect of extreme blood flow increase on the dynamics of the main variables of the model was also
simulated without additional carbohydrate intake. AS is created in C#, and can be delivered as an Exe-
module for IBM-compatible computers. Medical students can be additional users of the AP as an additional
didactic tool. The AS ensures the preservation of all simulation data for future reviews and publications. The
AS can be used by future endocrinologists in their training. Physiologists interested in the integrative physi-
ology of cellular life support are recommended to use the SCS.
Keywords: glucose homeostasis, physiological systems, mathematical model, visualization, students
Р.Д. Григорян, І.П. Сініцин, А.Г. Дегода, Т.В. Людовик, О.І. Юрчак, Н.А. Струтинська
МОДЕЛЮВАННЯ ВЗАЄМОДІЇ ПІДШЛУНКОВОЇ ЗАЛОЗИ
ТА ПЕЧІНКИ В УМОВАХ КОНТРОЛЬОВАНОЇ
ГЕМОДИНАМІКИ
Автономне програмне забезпечення (АПЗ) створено для моделювання динаміки взаємозв'язку ендо-
генних агентів глюкоза-інсулін-глікоген-глюкагон у здорової людини. АПЗ базується на кількісній
математичній моделі, що складається з трьох компонентів: моделі, що описує взаємозв'язок підшлун-
кова залоза-печінка; моделі, що описує кровообіг у розгалуженій серцево-судинній системі, врахо-
вуючи нейрогуморальні регулятори серцевої функції, судинного тонусу та загального об'єму крові;
та моделі, що описує фільтрацію крові в ниркових клубочках та канальцеву реабсорбцію. Також було
запрограмовано тест на толерантність до глюкози (ГТТ). Тестові симуляції продемонстрували адек-
ватні реакції моделі. Програма інтегрована у спеціалізований комп'ютерний симулятор (СКС). Він
дозволяє вивчати механізми, які, залежно від динаміки екзогенних та ендогенних фізико -хімічних
змінних, динамічно формують багатовимірній ландшафт здоров'я у просторі біометричних показ-
ників. Вплив екстремального збільшення кровообігу на динаміку основних змінних моделі також бу-
ло змодельовано без додаткового притока вуглеводів. АПЗ — це автономне програмне забезпечення
на C#, що постачається як Exe-модуль для IBM-сумісних комп'ютерів. Студенти-медики можуть ко-
ристуватися АПЗ як додатковим дидактичним засобом. АПЗ, що забезпечує збереження всіх даних
моделювання для майбутніх розглядів та публікацій, може бути використане ендокринологами у до-
слідженнях. Фізіологам, які цікавляться інтегративною фізіологією клітинного життєзабезпечення,
рекомендується використовувати СКС.
Ключові слова: гомеостаз глюкози, фізіологічні системи, математична модель, візуалізація, студенти
Introduction
Irregular intake of carbohydrates can create
energy problems in human sensitive cells like
neurons, kidney cells, hepatocytes, and myo-
cytes. Special mechanisms smoothing out the
flow of glucose into the blood and providing
glucose homeostasis evolved. Important roles
in glucose homeostasis play the pancreas pro-
ducing insulin, hepatocytes, and myocytes that
© Р.Д. Григорян, І.П. Сініцин, А.Г. Дегода, Т.В. Людовик, О.І. Юрчак, Н.А. Струтинська, 2026
ISSN 1727-4907. Проблеми програмування. 2026. №2
https://pp.isofts.kiev.ua
CC BY 4.0
Комп’ютерне моделювання
50
transform the exec amount of blood glucose
into liver and muscle glycogen. However,
namely the liver, accumulating up to 120 g gly-
cogen and capable of its reverse transformation
to blood glucose when its concentration essen-
tially drops, is the main organ dynamically re-
acting to blood glucose lack. Normally, the
urine does not contain essential concentration of
glucose. At the same time, the mechanism re-
sponsible for blood glucose homeostasis has of
limited power. Therefore, even under physio-
logical conditions, extreme glucose intakes lead
to elevated concentrations of glucose in the
urine which finally removes serious volumes of
glucose. In endocrinology, special glucose tol-
erance test (GTT) is applied to assess the effi-
ciency of mechanisms providing glucose home-
ostasis [1].
The main product of the pancreas is the
hormone insulin. It performs two functions:
first, it promotes the entry of glucose into the
cell; second, it activates the transformation of
excess glucose into glycogen and its accumula-
tion in the liver and muscles. An additional
product of the pancreas is the hormone gluca-
gon. Its production is activated when there is
not enough glucose in the blood.
It is under such conditions that the re-
verse transformation of glycogen into glucose
occurs in hepatocytes. Glucagon enhances the
action of the heart pump and affects blood
pressure. Therefore, we model these physio-
logical processes, since they are an important
link in the energy supply of cell metabolism.
The model of glucose homeostasis
Various models have been proposed
for an in-depth study of the glucose homeo-
stasis mechanism and its possible disturb-
ances (for examples, [2-8]). The models [5,6]
help understand the mechanisms of type 2
diabetes by demonstrating how disruptions at
the cellular level lead to impaired glucose
regulation throughout the body.
The model we proposed describes
dynamic interactions of blood glucose ( ( ))G t ,
insulin ( ( )I t ), liver glycogen ( ( ))Lg t , muscle
glycogen ( ( ))Mg t , and glucagon ( ( ))Gg t de-
pending on velocities of glucose incomes (
( ))Gv t+ and consumption ( ( ))Gv t− . The model
takes into account that in certain cells
(hepatocytes, fats, and skeletal myocytes)
glucose consumption is associated with insu-
lin concentration while other specialized cells
directly consume glucose.
( ) ( ) ( ) ( )G
dG tT G t I t W t
dt
= + − , (1)
In (1), GT is the time constant of glu-
cose dynamics, ( )W t - presents the power of
general biological work, coefficient 0 on-
ly for hepatocytes, fats, and skeletal myo-
cytes. Virtually, by altering the value of coef-
ficient , the user can simulate nuances of
glucose consumption dynamics in chosen cell
types.
The dynamics of insulin is described
by following differential equation:
( ) ( ) ( )I
dI tT G t I t
dt
= − , (2)
In (2), and are approximation
constants.
Special mechanism providing blood
glucose homeostasis is modeled using the
differential equation describing excess glu-
cose transformation into ( )Lg t and ( )Mg t , and
reverse transformation of ( )Lg t to ( )G t .
( ( ) ) ( ), ( )( )
0, ( )
g
G cr L crL
gL
cr
k G t G g t G t Gdg t
T
dt G t G
− −
=
, (3)
max
( ) ( ( ) ( )) ( ),
( ) ; ( )
MgM
gM G cr M M
cr M M
dg tT k G t G g t g t
dt
G t G g t g
= − − −
, (4)
In (4), gMT , Mg
Gk , and max
Mg are ap-
proximation constants.
The next equation describes the dy-
namics of glucagon:
( ( ) ) ( ) , ( )( )
( ( )) ( ), ( )
cr G u crG
gG
cr G cr
G t G g t g G t Gdg t
T
G G t g t G t Gdt
− − −
= − −
, (5)
In (5), gGT , , and ug are approxima-
tion constants.
So, the equation system (1)-(5) de-
scribes the dynamics of the glucose-insulin-
glycogen-glucagon relationships in a healthy
individual.
Autonomic software (AS) was cre-
ated for the numerical solution of this sys-
tem of equations on a computer. The prima-
ry user of this program was intended to be a
Комп’ютерне моделювання
51
specialist (endocrinologist), so a problem-
oriented, user-friendly interface (UI) was
developed. In parallel, a simulator was de-
veloped that reproduces the integrative re-
sponses of human internal organs to a wide
range of endogenous and exogenous dynam-
ic factors [9,10]. They are subdivided into
eight clusters. The appearance of a special
screen form that allows the user to operate
with the simulation results is shown in Fig-
ure 1. The user can arbitrarily generate the
desired set of characteristics for graphical
visualization. Initially, these characteristics
are grouped by related features into eight
clusters on the left side of the window. On
the right side of the window are two sub-
windows where the variables to be analyzed
are collected. These sub-windows allow the
model's input and output variables to be
separated. By opening each cluster one by
one, the user selects a variable in it and
moves it to one of the sub-windows on the
right side. This quickly generates a set of
analyzed variables in the form of graphs.
Fig. 1. The screen form of UI for actualizing sets of input-output variables
In particular, our complex model that
also describes the overall circulation includes
special equations concerning hemodynamic
effects of glucagon through its dilating influ-
ence on coronary arteries and increase of cor-
onary circulation. The latter effect elevates
the myocardium power. Besides, assistant
equations describing velocities of glucose
incomes ( )Gv t+ and consumption ( )Gv t− create
an opportunity to simulate different scenarios
of glucose dynamics depending on given
( )Gv t+ and ( )Gv t− .
Naturally, current rates of glucose
incomes ( )Gv t+ and consumption ( )Gv t− are
unpredictable variables. Our software pro-
vides with special options to simulate both
these variables using a list of analytical func-
tions and screen forms for modifying values
of coefficients. Two examples below illustrate
this modification by actualizing values of
constants (0),v 1, 2 3 2, , ,and v .
1 1
2 2
(0) , ( )
( )
(0) , ( )
G
G
G
v t v t v
v t
v t v t v
+
+
+
+
= −
,
3 1( ) (0) sin( ), 0 ( )Gv t v t t t + = + .
Комп’ютерне моделювання
52
In contrast, ( )Gv t− depends on or-
gans’ activities generally correlating with
regional blood flows. Therefore, the equation
describing this dependency looks like (6):
1 2
3 4
5 6
( ) ( )
( ) (1 ( ))
( ( ) ( )
G
b h
k kr
h lm
dv a q t a q t
dt
a q t a q t
a I c q t a q t
− = +
+ +
+ +
, (6)
Here, ( )bq t is the summary brain
flow, ( )hq t is the coronary blood flow, ( )kq t
is the kidney glomeruli blood flow, ( )krq t re-
absorption fraction, ( )hq t and ( )lmq t represent
blood flows in insulin-depended organs, while
1 6a a− are approximation constants.
11
12 13
14 15
16 17
( ) ( ) ( )
( ( ) ( )) ( )
( ) (1 ( ))
( ) ( ( ) ( )
L
L
h lm h
k kr
h lm
dv C t a W t I t
dt
c q t a q t a q t
a q t a q t
a I t c q t a q t
= +
+ +
+ +
+ +
, (7)
In (7), , 11a - 17a , and c are approximation
constants.
Food glucose velocity ( )FGv t+ is pro-
portional to the volume GF + of glucose intake,
so ( ) /FG g Gv t k F t+ += , where gk characteriz-
es the average intensity of glucose entry from
the gastrointestinal tract into the blood.
Glucagon altering the lumen of coro-
nary arteries modulates their resistance
( )CR t relatively to initial value of (0)CR char-
acteristic for basal coronary flow (0)Cq :
6( ) (0) (1 (0) / ( ))C C C CR t R q q t= − , (6)
This elevates the ventricle contractility ( )k t
4( ) (0) ( ( ) (0))C Ck t k q t q= + − . (7)
In (6) and (7), 4 6, , (0)and k are
constants.
Fig. 2. The screen-form indicating a part of options for configuring the actual model and construct-
ing the simulation scenario (left) and information concerning the chosen model configuration (right)
Examples of simulations
Our simulator has two versions: AS
and extended simulator (ES). The latter in-
cludes models of the functionally integrated
internal organs that optimize cell life support
(see [9,10]).
Simulations presented further are ad-
dressed both to programmers and experts mod-
eling human physiology. At the same time, the
reader's belief in the simulator depends in no
small part on the adequacy of the simulations.
Комп’ютерне моделювання
53
ES can simulate effects caused by other or-
gans and physiological systems. Therefore, be-
fore to consider simulations provided AS, it is
useful to look at Figure 3. It presents main he-
modynamic characteristics simulated ES. They
show that transient processes in the system re-
solve quickly: a steady-state circulation regime
is observed for almost the entire ten-minute
exposure period. This guarantees that the dy-
namics of all variables in the glucose homeosta-
sis model provided by AS are determined by the
dynamics of variables specific to the glucose
homeostasis model. Naturally, if the characteris-
tics of the coupled models change, the dynamics
of the glucose homeostasis model variables will
also change.
Fig. 3. Hemodynamics in control simulation
Fig. 4. Simulated dynamics of glucose, insulin, glucagon, and urine glucose (upper curves) and liver
glycogen (bottom) in a healthy person model under stable glucose production (0.07 mmol/min) and
consumption (0.05 mmol. /min) rates for 4.15 hours real time exposure
Комп’ютерне моделювання
54
Fig. 5. Simulated dynamics of glucose, insulin, glucagon, and urine glucose (upper curves) and liver
glycogen (bottom curve) in a healthy person model under stable glucose production (0.07
mmol/min) and consumption (0.075 mmol. /min) rates for 4.15 hours real time exposure
Fig. 6. Simulated dynamics of glucose, insulin, glucagon, and urine glucose (upper curves) and liver
glycogen (bottom curve) in a healthy person model under periodic changes in the rate of glucose
production according to a sinusoidal law and stable consumption (0.075 mmol. /min) rate for 4.15
hours real time exposure
Figures 3-6 demonstrate that our simulator is mainly adequate at least in the time intervals
considered. This gives us the opportunity to simulate specific medical GTT-test.
Комп’ютерне моделювання
55
Simulating glucose tolerance test - GTT
Pictures 7 and 8 illustrate simulations of standard GTT for different healthy persons and
persons diseased with type 1 diabetes.
Fig. 7. Two simulated GTT (glucose tolerance tests) on models of the same healthy person. The left
picture displays dynamics of glucose, insulin, glucagon, and urine glucose (upper curves) and liver
glycogen and test glucose income (bottom curve) under stable glucose consumption rate of 0.06
mmol. /min but for glucose production rate of 0.085 mmol. /min. The right picture displays these
same curves for the case of 0.095 mmol. /min glucose production rate and stable consumption rate
of 0.06 mmol. /min.
Fig. 8. Two simulated GTT (glucose tolerance tests) on models of persons having problems with
glucose homeostasis. The left picture displays dynamics of glucose, insulin, glucagon, and urine
glucose (upper curves) and liver glycogen and test glucose income (bottom curve) under stable glu-
cose consumption rate of 0.06 mmol. /min. but for glucose production rate of 0.085 mmol. /min but
with two-times weak homeostasis while the right picture displays these same curves for the uncon-
trolled blood glucose.
Комп’ютерне моделювання
56
The graphs in the last figure should
be compared with those on the left side of
Figure 7. The most significant difference is
evident when comparing the dynamics of
urine glucose: as blood glucose homeostasis
weakens, the amount of glucose in the urine
increases. Under providing of real GTT, this
is an objective indicator for the diagnosis of
type 1 diabetes.
Discussion
In a real organism, most of biological
variables are also influenced by other endoge-
nous factors not accounted for in our model or
in simulations demonstrated. Therefore, the
proposed model is limited in its simulation
capabilities. At the same time, an analysis of
available clinical data shows that our model is
generally adequate. This conclusion is also
true during comparison of simulation results
provided by our model with similar models by
other authors (e.g., [1-7]), Moreover, our
model offers a number of new possibilities for
theoretical research aimed at understanding of
fundamental physiological mechanisms and
practical consideration of their nuances. For
example, the inclusion of a muscle-mediated
mechanism of glycogen storage, control of
excess urinary glucose excretion, and the abil-
ity to model different pathways that deplete
liver glycogen make our model a useful tool
capable of providing insight into the uncon-
trolled underlying mechanisms that drive in-
dividual differences during GTT.
When performing a glucose tolerance
test, the physician has no information on the
levels of residual glycogen in the liver or
muscles. The rate of accumulation of one of
these products influences the rate of accumu-
lation of the other. However, we were unable
to find quantitative data on these residual
products in the literature, and therefore cannot
confirm the accuracy of the modeled rate dy-
namics. However, we note that incorporation
of this model into an extended model describ-
ing the interaction of human internal organs
has provided the first tool for theoretically
studying the role of neuroendocrine modula-
tors in glucose homeostasis.
To improve the effectiveness of our
simulator, we plan to model the effects of
lactate, adrenaline, and fat concentrations. In
particular, it is well known that under low
insulin, the body breaks down fats, creating
ketone bodies (acetoacetate and β-
hydroxybutyrate) for energy. Blood ketones
normally less than 0.6 mmol/L, under Type 1
diabetes can elevate up to danger level of 3
mmol/L with symptoms extreme thirst, fre-
quent urination, nausea, vomiting, abdominal
pain, and fruity-smelling breath, requiring
emergence care. As our complex model de-
scribes cardiovascular and kidney-urinary
systems, its proper advancement could make
the simulator usable for deeper study of
pathological scenarios too.
Conclusion
A quantitative mathematical model of human
glucose homeostasis has been developed. The
model is implemented as a C# program. The
program can function both as a standalone
executable module and as part of a newly
proposed integrated program that simulates
the fundamental physiological patterns of the
dynamic interactions of human internal or-
gans. The program can serve as an additional
didactic tool for visualization of the glucose-
insulin-glycogen-glucagon dynamic relation-
ships in a healthy individual.
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10. Grygoryan R.D., Sinitsin I.P., Degoda A.G.,
Lyudovyk T.V., Yurchak O.I. A simulator
providing theoretical research of human
integrative physiology. Problems in
programing, 2025,4,77-88.
DOI: 10.15407/pp2025.04.077.
Дата першого надходження до видання:
05.03.2026
Внутрішня рецензія отримана: 23.03.2026
Зовнішня рецензія отримана: 02.04.2026
Дата рекомендації до друку: 05.06.2026
Дата публікації: 29.06.2026
About authors:
Grygoryan Rafik,
Ph.D., Doctor (biology),
Department chief
Григорян Рафік Давидович,
доктор біологічних наук,
завідувач відділу
http://orcid.org/0000-0001-8762-733X
Sinitsyn Igor,
Ph.D., Doctor (technical sciences),
Professor, Director
Сініцин Ігор Петрович,
доктор технічних наук,
профессор, директор
http://orcid.org/0000-0002-4120-0784
Degoda Anna,
Senior scientist, Ph.D.
Дегода Анна,
доктор наук,
старший науковий співробітник
http://orcid.org/0000-0001-6364-5568.
Lyudovyk Tetyana,
Senior scientist, Ph.D.
Людовик Тетяна,
доктор наук,
старший науковий співробітник
https://orcid.org/0000-0003-0209-2001
Yurchak Oksana,
Leading software engineer
Юрчак Оксана,
Провідний інженер з програмування
https://orcid.org/0000-0003-3941-1555
Strutynska Natalia,
Leading scientist, Ph.D.
Струтинська Наталія,
доктор наук,
провідний науковий співробітник
http://orcid.org/0000-0001-7993-2705
Place of work:
Institute of Software Systems
of the National Academy of
Sciences of Ukraine
Інститут програмних систем
НАН України
03187, Кyїv, Acad. Glushkov avenue, 40,
Е-mail:
rgrygoryan@gmail.com,
ips2014@ukr.net,
anna@silverlinecrm.com,
tetyana.lyudovyk@gmail.com,
daravatan@gmail.com.
|
| id | pp_isofts_kiev_ua-article-1025 |
| institution | Problems in programming |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2026-06-30T01:00:16Z |
| publishDate | 2026 |
| publisher | PROBLEMS IN PROGRAMMING |
| record_format | ojs |
| resource_txt_mv | ppisoftskievua/e9/2d5a63662c6ee857563f18f9d02389e9.pdf |
| spelling | pp_isofts_kiev_ua-article-10252026-06-29T10:43:50Z Modeling of pancreas-liver interaction under controlled hemodynamics Моделювання взаємодії підшлункової залози та печінки в умовах контрольованої гемодинаміки Grygoryan, R.D. Sinitsyn, I.P. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. Strutynska, N.A. glucose homeostasis; physiological systems; mathematical model; visualization; students UDC 517.958:57 +519.711.3 + 612.51.001 гомеостаз глюкози; фізіологічні системи; математична модель; візуалізація; студенти УДК 517.958:57 +519.711.3 + 612.51.001 Autonomous software (AS) was created to simulate the dynamics of the glucose-insulin-glycogen-glucagon relationship in a healthy person. Our AS is based on a quantitative mathematical model consisting of three components: a model describing the pancreas-liver and the pancreas-skeletal muscles relationships; a model describing blood circulation in the branched cardiovascular system, taking into account neurohumoral regu lators of cardiac function, vascular tone and total blood volume; and a model describing blood filtration in the renal glomeruli and tubular reabsorption. A glucose tolerance test (GTT) was also programmed. Test simulations demonstrated adequate model responses. The program is integrated into a specialized computer simulator (SCS). It allows studying mechanisms that, depending on the dynamics of exogenous and endoge nous physicochemical variables, dynamically form multidimensional health landscape of biometric indica tors. The effect of extreme blood flow increase on the dynamics of the main variables of the model was also simulated without additional carbohydrate intake. AS is created in C#, and can be delivered as an Exe module for IBM-compatible computers. Medical students can be additional users of the AP as an additional didactic tool. The AS ensures the preservation of all simulation data for future reviews and publications. The AS can be used by future endocrinologists in their training. Physiologists interested in the integrative physi ology of cellular life support are recommended to use the SCS.Problems in programming 2026; 2: 49-57 Автономне програмне забезпечення (АПЗ) створено для моделювання динаміки взаємозв'язку ендо генних агентів глюкоза-інсулін-глікоген-глюкагон у здорової людини. АПЗ базується на кількісній математичній моделі, що складається з трьох компонентів: моделі, що описує взаємозв'язок підшлун кова залоза-печінка; моделі, що описує кровообіг у розгалуженій серцево-судинній системі, врахо вуючи нейрогуморальні регулятори серцевої функції, судинного тонусу та загального об'єму крові; та моделі, що описує фільтрацію крові в ниркових клубочках та канальцеву реабсорбцію. Також було запрограмовано тест на толерантність до глюкози (ГТТ). Тестові симуляції продемонстрували адек ватні реакції моделі. Програма інтегрована у спеціалізований комп'ютерний симулятор (СКС). Він дозволяє вивчати механізми, які, залежно від динаміки екзогенних та ендогенних фізико-хімічних змінних, динамічно формують багатовимірній ландшафт здоров'я у просторі біометричних показ ників. Вплив екстремального збільшення кровообігу на динаміку основних змінних моделі також бу ло змодельовано без додаткового притока вуглеводів. АПЗ — це автономне програмне забезпечення на C#, що постачається як Exe-модуль для IBM-сумісних комп'ютерів. Студенти-медики можуть ко ристуватися АПЗ як додатковим дидактичним засобом. АПЗ, що забезпечує збереження всіх даних моделювання для майбутніх розглядів та публікацій, може бути використане ендокринологами у до слідженнях. Фізіологам, які цікавляться інтегративною фізіологією клітинного життєзабезпечення, рекомендується використовувати СКС.Problems in programming 2026; 2: 49-57 PROBLEMS IN PROGRAMMING ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ ПРОБЛЕМИ ПРОГРАМУВАННЯ 2026-06-29 Article Article application/pdf https://pp.isofts.kiev.ua/index.php/ojs1/article/view/1025 PROBLEMS IN PROGRAMMING; No 2 (2026); 49-57 ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ; No 2 (2026); 49-57 ПРОБЛЕМИ ПРОГРАМУВАННЯ; No 2 (2026); 49-57 1727-4907 en https://pp.isofts.kiev.ua/index.php/ojs1/article/view/1025/1093 Copyright (c) 2026 PROBLEMS IN PROGRAMMING |
| spellingShingle | glucose homeostasis physiological systems mathematical model visualization students UDC 517.958:57 +519.711.3 + 612.51.001 Grygoryan, R.D. Sinitsyn, I.P. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. Strutynska, N.A. Modeling of pancreas-liver interaction under controlled hemodynamics |
| title | Modeling of pancreas-liver interaction under controlled hemodynamics |
| title_alt | Моделювання взаємодії підшлункової залози та печінки в умовах контрольованої гемодинаміки |
| title_full | Modeling of pancreas-liver interaction under controlled hemodynamics |
| title_fullStr | Modeling of pancreas-liver interaction under controlled hemodynamics |
| title_full_unstemmed | Modeling of pancreas-liver interaction under controlled hemodynamics |
| title_short | Modeling of pancreas-liver interaction under controlled hemodynamics |
| title_sort | modeling of pancreas-liver interaction under controlled hemodynamics |
| topic | glucose homeostasis physiological systems mathematical model visualization students UDC 517.958:57 +519.711.3 + 612.51.001 |
| topic_facet | glucose homeostasis physiological systems mathematical model visualization students UDC 517.958:57 +519.711.3 + 612.51.001 гомеостаз глюкози фізіологічні системи математична модель візуалізація студенти УДК 517.958:57 +519.711.3 + 612.51.001 |
| url | https://pp.isofts.kiev.ua/index.php/ojs1/article/view/1025 |
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