A Novel Approach to Multi-Compartmental Model Implementation to Achieve Metabolic Model Identifiability on Patient's CGM Data
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966174" target="_blank" >RIV/49777513:23520/22:43966174 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S1877050922015848" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050922015848</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2022.10.127" target="_blank" >10.1016/j.procs.2022.10.127</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A Novel Approach to Multi-Compartmental Model Implementation to Achieve Metabolic Model Identifiability on Patient's CGM Data
Popis výsledku v původním jazyce
Diabetes is a widespread civilization disease. When developing a new treatment method, in-silico benefits the development process by reducing the need for in-vivo subjects. In-silico evaluation requires a reliable metabolic model, often created as a multi-compartmental model. A common approach to implementing a multi-compartmental model is to use a system of ordinary differential equations. This approach utilises exponential transfer functions to transfer substances among the compartments. Using other than an exponential function is complex. Therefore, we propose a novel approach based on a direct, numeric integration of separated compartments, which can be further divided into individual depots. This enables to model substance transfer as a separate process with non-exponential characteristics, e.g.; when modelling carbohydrate absorption from the gut. As another benefit, the approach obeys the law of mass conservation on both the computational and architectural levels. This is a key feature when identifying a model on data, that are not measured within a controlled, isolated environment. Moreover, we actually transform the set of equations, i.e.; computer-code functions, into a component model to reduce the total maintenance costs – readability, testing, verification and deployment. We demonstrate the proposed approach by converting the Samadi model to it and enhancing it with a non-exponential transfer function.
Název v anglickém jazyce
A Novel Approach to Multi-Compartmental Model Implementation to Achieve Metabolic Model Identifiability on Patient's CGM Data
Popis výsledku anglicky
Diabetes is a widespread civilization disease. When developing a new treatment method, in-silico benefits the development process by reducing the need for in-vivo subjects. In-silico evaluation requires a reliable metabolic model, often created as a multi-compartmental model. A common approach to implementing a multi-compartmental model is to use a system of ordinary differential equations. This approach utilises exponential transfer functions to transfer substances among the compartments. Using other than an exponential function is complex. Therefore, we propose a novel approach based on a direct, numeric integration of separated compartments, which can be further divided into individual depots. This enables to model substance transfer as a separate process with non-exponential characteristics, e.g.; when modelling carbohydrate absorption from the gut. As another benefit, the approach obeys the law of mass conservation on both the computational and architectural levels. This is a key feature when identifying a model on data, that are not measured within a controlled, isolated environment. Moreover, we actually transform the set of equations, i.e.; computer-code functions, into a component model to reduce the total maintenance costs – readability, testing, verification and deployment. We demonstrate the proposed approach by converting the Samadi model to it and enhancing it with a non-exponential transfer function.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/EF19_073%2F0016931" target="_blank" >EF19_073/0016931: Zvyšování kvality interních grantových schémat na ZČU</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Procedia Computer Science
ISBN
—
ISSN
1877-0509
e-ISSN
—
Počet stran výsledku
8
Strana od-do
116-123
Název nakladatele
Elsevier
Místo vydání
—
Místo konání akce
Leuven, Belgium
Datum konání akce
26. 10. 2022
Typ akce podle státní příslušnosti
EUR - Evropská akce
Kód UT WoS článku
—