Viceconti, M., Juarez, M., Curreli, C. et al. (3 more authors) (2020) POSITION PAPER : Credibility of in silico trial technologies - a theoretical framing. IEEE Journal of Biomedical and Health Informatics, 24 (1). pp. 4-13. ISSN 2168-2194
Abstract
Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for problem of model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research community might not be appropriate. In this position paper we propose a theoretical framing for the problem of assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | In silico medicine; in silico trials; in silico-augmented clinical trials; credibility of predictive models; regulatory science; biomedical products |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Funding Information: | Funder Grant number European Commission - Horizon 2020 777123 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 Oct 2019 13:56 |
Last Modified: | 17 Dec 2021 10:31 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/jbhi.2019.2949888 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152863 |