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dc.contributor.authorRowan, Neil J.
dc.date.accessioned2024-04-03T09:19:43Z
dc.date.available2024-04-03T09:19:43Z
dc.date.copyright2024
dc.date.issued2024-03-12
dc.identifier.citationRowan, N.J. (2024). Digital technologies to unlock safe and sustainable opportunities for medical device and healthcare sectors with a focus on the combined use of digital twin and extended reality applications: a review. Science of the Total Environment. 926, 171672. https://doi.org/10.1016/j.scitotenv.2024.171672en_US
dc.identifier.issn0048-9697
dc.identifier.urihttps://research.thea.ie/handle/20.500.12065/4778
dc.description.abstractMedical devices have increased in complexity where there is a pressing need to consider design thinking and specialist training for manufacturers, healthcare and sterilization providers, and regulators. Appropriately addressing this consideration will positively inform end-to-end supply chain and logistics, production, processing, sterilization, safety, regulation, education, sustainability and circularity. There are significant opportunities to innovate and to develop appropriate digital tools to help unlock efficiencies in these important areas. This constitutes the first paper to create an awareness of and to define different digital technologies for informing and enabling medical device production from a holistic end-to-end life cycle perspective. It describes the added-value of using digital innovations to meet emerging opportunities for many disposable and reusable medical devices. It addresses the value of accessing and using integrated multi-actor HUBs that combine academia, industry, healthcare, regulators and society to help meet these opportunities. Such as cost-effective access to specialist pilot facilities and expertise that converges digital innovation, material science, biocompatibility, sterility assurance, business model and sustainability. It highlights the marked gap in academic R&D activities (PRISMA review of best publications conducted between January 2010 and January 2024) and the actual list of U.S. FDA’s approved and marketed artificial intelligence/machine learning (AI/ML), and augmented reality/virtual reality (AR/VR) enabled-medical devices for different healthcare applications. Bespoke examples of benefits underlying future use of digital tools includes potential implementation of machine learning for supporting and enabling parametric release of sterilized products through efficient monitoring of critical process data (complying with ISO 11135:2014) that would benefit stakeholders. This paper also focuses on the transformative potential of combining digital twin with extended reality innovations to inform efficiencies in medical device design thinking, supply chain and training to inform patient safety, circularity and sustainability.en_US
dc.formatPDFen_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofScience of the Total Environmenten_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectMedical devicesen_US
dc.subjectDigital transformationen_US
dc.subjectDesign thinkingen_US
dc.subjectSterilizationen_US
dc.subjectSustainabilityen_US
dc.subjectCircularityen_US
dc.titleDigital technologies to unlock safe and sustainable opportunities for medical device and healthcare sectors with a focus on the combined use of digital twin and extended reality applications: a reviewen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.contributor.affiliationTechnological University of the Shannon: Midlands Midwesten_US
dc.description.peerreviewyesen_US
dc.identifier.doi10.1016/j.scitotenv.2024.171672en_US
dc.identifier.eissn1879-1026
dc.identifier.orcidhttps://orcid.org/0000-0003-1228-3733en_US
dc.identifier.volume926en_US
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessen_US
dc.subject.departmentCentre for Sustainable Disinfection and Sterilisatiion, TUS Midlandsen_US
dc.type.versioninfo:eu-repo/semantics/publishedVersionen_US


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Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States