Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibility of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. Here, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. The proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.
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June 2017
Research-Article
Applicability Analysis of Validation Evidence for Biomedical Computational Models
Pras Pathmanathan,
Pras Pathmanathan
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
e-mail: pras.pathmanathan@fda.hhs.gov
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
e-mail: pras.pathmanathan@fda.hhs.gov
Search for other works by this author on:
Richard A. Gray,
Richard A. Gray
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Search for other works by this author on:
Vicente J. Romero,
Vicente J. Romero
Sandia National Laboratories,
Albuquerque, NM 87185
Albuquerque, NM 87185
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Tina M. Morrison
Tina M. Morrison
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Search for other works by this author on:
Pras Pathmanathan
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
e-mail: pras.pathmanathan@fda.hhs.gov
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
e-mail: pras.pathmanathan@fda.hhs.gov
Richard A. Gray
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Vicente J. Romero
Sandia National Laboratories,
Albuquerque, NM 87185
Albuquerque, NM 87185
Tina M. Morrison
Office of Science and Engineering
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Laboratories (OSEL),
Center for Devices and Radiological
Health (CDRH),
U.S. Food and Drug Administration (FDA),
Silver Spring, MD 20993
Manuscript received March 1, 2017; final manuscript received August 1, 2017; published online September 7, 2017. Assoc. Editor: Marc Horner.This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.
1Corresponding author.
J. Verif. Valid. Uncert. Jun 2017, 2(2): 021005 (11 pages)
Published Online: September 7, 2017
Article history
Received:
March 1, 2017
Revised:
August 1, 2017
Citation
Pathmanathan, P., Gray, R. A., Romero, V. J., and Morrison, T. M. (September 7, 2017). "Applicability Analysis of Validation Evidence for Biomedical Computational Models." ASME. J. Verif. Valid. Uncert. June 2017; 2(2): 021005. https://doi.org/10.1115/1.4037671
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