Cargando…
Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems
BACKGROUND: Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to pro...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721541/ https://www.ncbi.nlm.nih.gov/pubmed/34328030 http://dx.doi.org/10.1177/19322968211032249 |
_version_ | 1784625363412844544 |
---|---|
author | Schmitzer, Jana Strobel, Carolin Blechschmidt, Ronald Tappe, Adrian Peuscher, Heiko |
author_facet | Schmitzer, Jana Strobel, Carolin Blechschmidt, Ronald Tappe, Adrian Peuscher, Heiko |
author_sort | Schmitzer, Jana |
collection | PubMed |
description | BACKGROUND: Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to provide data about safety and efficacy of AndroidAPS, one of the most wide-spread do-it-yourself AP systems. However, the setup suffered from slow simulation speed. The objective of this work is to speed up simulation by implementing the algorithm directly in MATLAB(®)/Simulink(®). METHOD: Firstly, AndroidAPS is re-implemented in MATLAB(®) and verified. Then, the function is incorporated into T1DMS. To evaluate the new setup, a scenario covering 2 days in real time is run for 30 virtual patients. The results are compared to those presented in the literature. RESULTS: Unit tests and integration tests proved the equivalence of the new implementation and the original AndroidAPS code. Simulation of the scenario required approximately 15 minutes, corresponding to a speed-up factor of roughly 1000 with respect to real time. The results closely resemble those presented by Toffanin et al. Discrepancies were to be expected because a different virtual population was considered. Also, some parameters could not be extracted from and harmonized with the original setup. CONCLUSIONS: The new implementation facilitates extensive in silico trials of AndroidAPS due to the significant reduction of runtime. This provides a cheap and fast means to test new versions of the algorithm before they are shared with the community. |
format | Online Article Text |
id | pubmed-8721541 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-87215412022-01-04 Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems Schmitzer, Jana Strobel, Carolin Blechschmidt, Ronald Tappe, Adrian Peuscher, Heiko J Diabetes Sci Technol Special Section: The Artificial Pancreas: Predictive Algorithm Strategies BACKGROUND: Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to provide data about safety and efficacy of AndroidAPS, one of the most wide-spread do-it-yourself AP systems. However, the setup suffered from slow simulation speed. The objective of this work is to speed up simulation by implementing the algorithm directly in MATLAB(®)/Simulink(®). METHOD: Firstly, AndroidAPS is re-implemented in MATLAB(®) and verified. Then, the function is incorporated into T1DMS. To evaluate the new setup, a scenario covering 2 days in real time is run for 30 virtual patients. The results are compared to those presented in the literature. RESULTS: Unit tests and integration tests proved the equivalence of the new implementation and the original AndroidAPS code. Simulation of the scenario required approximately 15 minutes, corresponding to a speed-up factor of roughly 1000 with respect to real time. The results closely resemble those presented by Toffanin et al. Discrepancies were to be expected because a different virtual population was considered. Also, some parameters could not be extracted from and harmonized with the original setup. CONCLUSIONS: The new implementation facilitates extensive in silico trials of AndroidAPS due to the significant reduction of runtime. This provides a cheap and fast means to test new versions of the algorithm before they are shared with the community. SAGE Publications 2021-07-30 /pmc/articles/PMC8721541/ /pubmed/34328030 http://dx.doi.org/10.1177/19322968211032249 Text en © 2021 Diabetes Technology Society https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Special Section: The Artificial Pancreas: Predictive Algorithm Strategies Schmitzer, Jana Strobel, Carolin Blechschmidt, Ronald Tappe, Adrian Peuscher, Heiko Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title | Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title_full | Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title_fullStr | Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title_full_unstemmed | Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title_short | Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems |
title_sort | efficient closed loop simulation of do-it-yourself artificial pancreas systems |
topic | Special Section: The Artificial Pancreas: Predictive Algorithm Strategies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721541/ https://www.ncbi.nlm.nih.gov/pubmed/34328030 http://dx.doi.org/10.1177/19322968211032249 |
work_keys_str_mv | AT schmitzerjana efficientclosedloopsimulationofdoityourselfartificialpancreassystems AT strobelcarolin efficientclosedloopsimulationofdoityourselfartificialpancreassystems AT blechschmidtronald efficientclosedloopsimulationofdoityourselfartificialpancreassystems AT tappeadrian efficientclosedloopsimulationofdoityourselfartificialpancreassystems AT peuscherheiko efficientclosedloopsimulationofdoityourselfartificialpancreassystems |