Literature DB >> 30973403

Assessing Computational Model Credibility Using a Risk-Based Framework: Application to Hemolysis in Centrifugal Blood Pumps.

Tina M Morrison1, Prasanna Hariharan1, Chloe M Funkhouser2, Payman Afshari3, Mark Goodin4, Marc Horner5.   

Abstract

Medical device manufacturers using computational modeling to support their device designs have traditionally been guided by internally developed modeling best practices. A lack of consensus on the evidentiary bar for model validation has hindered broader acceptance, particularly in regulatory areas. This has motivated the US Food and Drug Administration and the American Society of Mechanical Engineers (ASME), in partnership with medical device companies and software providers, to develop a structured approach for establishing the credibility of computational models for a specific use. Charged with this mission, the ASME V&V 40 Subcommittee on Verification and Validation (V&V) in Computational Modeling of Medical Devices developed a risk-informed credibility assessment framework; the main tenet of the framework is that the credibility requirements of a computational model should be commensurate with the risk associated with model use. This article provides an overview of the ASME V&V 40 standard and an example of the framework applied to a generic centrifugal blood pump, emphasizing how experimental evidence from in vitro testing can support computational modeling for device evaluation. Two different contexts of use for the same model are presented, which illustrate how model risk impacts the requirements on the V&V activities and outcomes.

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Year:  2019        PMID: 30973403      PMCID: PMC6493688          DOI: 10.1097/MAT.0000000000000996

Source DB:  PubMed          Journal:  ASAIO J        ISSN: 1058-2916            Impact factor:   2.872


  11 in total

Review 1.  The use of computational fluid dynamics in the development of ventricular assist devices.

Authors:  Katharine H Fraser; M Ertan Taskin; Bartley P Griffith; Zhongjun J Wu
Journal:  Med Eng Phys       Date:  2010-11-13       Impact factor: 2.242

Review 2.  An FDA Viewpoint on Unique Considerations for Medical-Device Clinical Trials.

Authors:  Owen Faris; Jeffrey Shuren
Journal:  N Engl J Med       Date:  2017-04-06       Impact factor: 91.245

3.  FDA Benchmark Medical Device Flow Models for CFD Validation.

Authors:  Richard A Malinauskas; Prasanna Hariharan; Steven W Day; Luke H Herbertson; Martin Buesen; Ulrich Steinseifer; Kenneth I Aycock; Bryan C Good; Steven Deutsch; Keefe B Manning; Brent A Craven
Journal:  ASAIO J       Date:  2017 Mar/Apr       Impact factor: 2.872

4.  Estimation of shear stress-related blood damage in heart valve prostheses--in vitro comparison of 25 aortic valves.

Authors:  M Giersiepen; L J Wurzinger; R Opitz; H Reul
Journal:  Int J Artif Organs       Date:  1990-05       Impact factor: 1.595

5.  Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

Authors:  Tarek Haddad; Adam Himes; Laura Thompson; Telba Irony; Rajesh Nair
Journal:  J Biopharm Stat       Date:  2017-03-21       Impact factor: 1.051

6.  Multilaboratory study of flow-induced hemolysis using the FDA benchmark nozzle model.

Authors:  Luke H Herbertson; Salim E Olia; Amanda Daly; Christopher P Noatch; William A Smith; Marina V Kameneva; Richard A Malinauskas
Journal:  Artif Organs       Date:  2014-09-02       Impact factor: 3.094

7.  Verification Benchmarks to Assess the Implementation of Computational Fluid Dynamics Based Hemolysis Prediction Models.

Authors:  Prasanna Hariharan; Gavin D'Souza; Marc Horner; Richard A Malinauskas; Matthew R Myers
Journal:  J Biomech Eng       Date:  2015-07-09       Impact factor: 2.097

8.  The Role of Computational Modeling and Simulation in the Total Product Life Cycle of Peripheral Vascular Devices.

Authors:  Tina M Morrison; Maureen L Dreher; Srinidhi Nagaraja; Leonardo M Angelone; Wolfgang Kainz
Journal:  J Med Device       Date:  2017-01-23       Impact factor: 0.582

9.  Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations.

Authors:  Prasanna Hariharan; Gavin A D'Souza; Marc Horner; Tina M Morrison; Richard A Malinauskas; Matthew R Myers
Journal:  PLoS One       Date:  2017-06-08       Impact factor: 3.240

10.  Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories.

Authors:  Tina M Morrison; Pras Pathmanathan; Mariam Adwan; Edward Margerrison
Journal:  Front Med (Lausanne)       Date:  2018-09-25
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  12 in total

1.  Towards a comprehensive assessment of QSP models: what would it take?

Authors:  Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2022-08-13       Impact factor: 2.410

2.  Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation.

Authors:  Alfonso Santiago; Constantine Butakoff; Beatriz Eguzkitza; Richard A Gray; Karen May-Newman; Pras Pathmanathan; Vi Vu; Mariano Vázquez
Journal:  PLoS Comput Biol       Date:  2022-06-13       Impact factor: 4.779

3.  Computational modeling of the Food and Drug Administration's benchmark centrifugal blood pump.

Authors:  Bryan C Good; Keefe B Manning
Journal:  Artif Organs       Date:  2020-02-16       Impact factor: 3.094

4.  Mechanisms underlying pro-arrhythmic abnormalities arising from Pitx2-induced electrical remodelling: an in silico intersubject variability study.

Authors:  Yijie Zhu; Jieyun Bai; Andy Lo; Yaosheng Lu; Jichao Zhao
Journal:  Ann Transl Med       Date:  2021-01

5.  In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products.

Authors:  Marco Viceconti; Francesco Pappalardo; Blanca Rodriguez; Marc Horner; Jeff Bischoff; Flora Musuamba Tshinanu
Journal:  Methods       Date:  2020-01-25       Impact factor: 3.608

Review 6.  Biomechanical modelling of the facet joints: a review of methods and validation processes in finite element analysis.

Authors:  Marlène Mengoni
Journal:  Biomech Model Mechanobiol       Date:  2020-11-22

Review 7.  Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm.

Authors:  Vijayalakshmi Chelliah; Georgia Lazarou; Sumit Bhatnagar; John P Gibbs; Marjoleen Nijsen; Avijit Ray; Brian Stoll; R Adam Thompson; Abhishek Gulati; Serguei Soukharev; Akihiro Yamada; Jared Weddell; Hiroyuki Sayama; Masayo Oishi; Sabine Wittemer-Rump; Chirag Patel; Christoph Niederalt; Rolf Burghaus; Christian Scheerans; Jörg Lippert; Senthil Kabilan; Irina Kareva; Natalya Belousova; Alex Rolfe; Anup Zutshi; Marylore Chenel; Filippo Venezia; Sylvain Fouliard; Heike Oberwittler; Alix Scholer-Dahirel; Helene Lelievre; Dean Bottino; Sabrina C Collins; Hoa Q Nguyen; Haiqing Wang; Tomoki Yoneyama; Andy Z X Zhu; Piet H van der Graaf; Andrzej M Kierzek
Journal:  Clin Pharmacol Ther       Date:  2020-08-14       Impact factor: 6.875

8.  Distribution and history of extensional stresses on vWF surrogate molecules in turbulent flow.

Authors:  Oanh L Pham; Samuel E Feher; Quoc T Nguyen; Dimitrios V Papavassiliou
Journal:  Sci Rep       Date:  2022-01-07       Impact factor: 4.996

9.  Consideration of a Credibility Assessment Framework in Model-Informed Drug Development: Potential Application to Physiologically-Based Pharmacokinetic Modeling and Simulation.

Authors:  Colleen Kuemmel; Yuching Yang; Xinyuan Zhang; Jeffry Florian; Hao Zhu; Million Tegenge; Shiew-Mei Huang; Yaning Wang; Tina Morrison; Issam Zineh
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-11-10

10.  How to Validate in silico Deployment of Coronary Stents: Strategies and Limitations in the Choice of Comparator.

Authors:  Francesca Berti; Luca Antonini; Gianluca Poletti; Constantino Fiuza; Ted J Vaughan; Francesco Migliavacca; Lorenza Petrini; Giancarlo Pennati
Journal:  Front Med Technol       Date:  2021-08-17
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