Cargando…

Mapping the use of computational modelling and simulation in clinics: A survey

In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&...

Descripción completa

Detalles Bibliográficos
Autores principales: Lesage, Raphaëlle, Van Oudheusden, Michiel, Schievano, Silvia, Van Hoyweghen, Ine, Geris, Liesbet, Capelli, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150234/
https://www.ncbi.nlm.nih.gov/pubmed/37138727
http://dx.doi.org/10.3389/fmedt.2023.1125524
_version_ 1785035326698291200
author Lesage, Raphaëlle
Van Oudheusden, Michiel
Schievano, Silvia
Van Hoyweghen, Ine
Geris, Liesbet
Capelli, Claudio
author_facet Lesage, Raphaëlle
Van Oudheusden, Michiel
Schievano, Silvia
Van Hoyweghen, Ine
Geris, Liesbet
Capelli, Claudio
author_sort Lesage, Raphaëlle
collection PubMed
description In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants (n = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise (i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms “Personalised medicine” and “Patient-specific modelling” were the most well-known within the respondents. “In silico clinical trials” and “Digital Twin” were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community.
format Online
Article
Text
id pubmed-10150234
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-101502342023-05-02 Mapping the use of computational modelling and simulation in clinics: A survey Lesage, Raphaëlle Van Oudheusden, Michiel Schievano, Silvia Van Hoyweghen, Ine Geris, Liesbet Capelli, Claudio Front Med Technol Medical Technology In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants (n = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise (i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms “Personalised medicine” and “Patient-specific modelling” were the most well-known within the respondents. “In silico clinical trials” and “Digital Twin” were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community. Frontiers Media S.A. 2023-04-17 /pmc/articles/PMC10150234/ /pubmed/37138727 http://dx.doi.org/10.3389/fmedt.2023.1125524 Text en © 2023 Lesage, Van Oudheusden, Schievano, Van Hoyweghen, Geris and Capelli. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medical Technology
Lesage, Raphaëlle
Van Oudheusden, Michiel
Schievano, Silvia
Van Hoyweghen, Ine
Geris, Liesbet
Capelli, Claudio
Mapping the use of computational modelling and simulation in clinics: A survey
title Mapping the use of computational modelling and simulation in clinics: A survey
title_full Mapping the use of computational modelling and simulation in clinics: A survey
title_fullStr Mapping the use of computational modelling and simulation in clinics: A survey
title_full_unstemmed Mapping the use of computational modelling and simulation in clinics: A survey
title_short Mapping the use of computational modelling and simulation in clinics: A survey
title_sort mapping the use of computational modelling and simulation in clinics: a survey
topic Medical Technology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150234/
https://www.ncbi.nlm.nih.gov/pubmed/37138727
http://dx.doi.org/10.3389/fmedt.2023.1125524
work_keys_str_mv AT lesageraphaelle mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey
AT vanoudheusdenmichiel mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey
AT schievanosilvia mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey
AT vanhoyweghenine mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey
AT gerisliesbet mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey
AT capelliclaudio mappingtheuseofcomputationalmodellingandsimulationinclinicsasurvey