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Adapting modeling and simulation credibility standards to computational systems biology

Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. The National Aeronautics and Space Administration (NASA) uses computational models to perform complex experiments that are otherwise prohibitively expensive or require a microgravity envi...

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Autores principales: Tatka, Lillian T., Smith, Lucian P., Hellerstein, Joseph L., Sauro, Herbert M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369698/
https://www.ncbi.nlm.nih.gov/pubmed/37496031
http://dx.doi.org/10.1186/s12967-023-04290-5
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author Tatka, Lillian T.
Smith, Lucian P.
Hellerstein, Joseph L.
Sauro, Herbert M.
author_facet Tatka, Lillian T.
Smith, Lucian P.
Hellerstein, Joseph L.
Sauro, Herbert M.
author_sort Tatka, Lillian T.
collection PubMed
description Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. The National Aeronautics and Space Administration (NASA) uses computational models to perform complex experiments that are otherwise prohibitively expensive or require a microgravity environment. Similarly, the Food and Drug Administration (FDA) and European Medicines Agency (EMA) have began accepting models and simulations as forms of evidence for pharmaceutical and medical device approval. It is crucial that computational models meet a standard of credibility when using them in high-stakes decision making. For this reason, institutes including NASA, the FDA, and the EMA have developed standards to promote and assess the credibility of computational models and simulations. However, due to the breadth of models these institutes assess, these credibility standards are mostly qualitative and avoid making specific recommendations. On the other hand, modeling and simulation in systems biology is a narrower domain and several standards are already in place. As systems biology models increase in complexity and influence, the development of a credibility assessment system is crucial. Here we review existing standards in systems biology, credibility standards in other science, engineering, and medical fields, and propose the development of a credibility standard for systems biology models.
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spelling pubmed-103696982023-07-27 Adapting modeling and simulation credibility standards to computational systems biology Tatka, Lillian T. Smith, Lucian P. Hellerstein, Joseph L. Sauro, Herbert M. J Transl Med Review Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. The National Aeronautics and Space Administration (NASA) uses computational models to perform complex experiments that are otherwise prohibitively expensive or require a microgravity environment. Similarly, the Food and Drug Administration (FDA) and European Medicines Agency (EMA) have began accepting models and simulations as forms of evidence for pharmaceutical and medical device approval. It is crucial that computational models meet a standard of credibility when using them in high-stakes decision making. For this reason, institutes including NASA, the FDA, and the EMA have developed standards to promote and assess the credibility of computational models and simulations. However, due to the breadth of models these institutes assess, these credibility standards are mostly qualitative and avoid making specific recommendations. On the other hand, modeling and simulation in systems biology is a narrower domain and several standards are already in place. As systems biology models increase in complexity and influence, the development of a credibility assessment system is crucial. Here we review existing standards in systems biology, credibility standards in other science, engineering, and medical fields, and propose the development of a credibility standard for systems biology models. BioMed Central 2023-07-26 /pmc/articles/PMC10369698/ /pubmed/37496031 http://dx.doi.org/10.1186/s12967-023-04290-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Review
Tatka, Lillian T.
Smith, Lucian P.
Hellerstein, Joseph L.
Sauro, Herbert M.
Adapting modeling and simulation credibility standards to computational systems biology
title Adapting modeling and simulation credibility standards to computational systems biology
title_full Adapting modeling and simulation credibility standards to computational systems biology
title_fullStr Adapting modeling and simulation credibility standards to computational systems biology
title_full_unstemmed Adapting modeling and simulation credibility standards to computational systems biology
title_short Adapting modeling and simulation credibility standards to computational systems biology
title_sort adapting modeling and simulation credibility standards to computational systems biology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369698/
https://www.ncbi.nlm.nih.gov/pubmed/37496031
http://dx.doi.org/10.1186/s12967-023-04290-5
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