医疗设备的复杂性增加,迫切需要考虑制造商的设计思维和专业培训,医疗保健和消毒供应商,和监管者。适当解决这一考虑将为端到端供应链和物流提供积极的信息,生产,processing,灭菌,安全,regulation,教育,可持续性和循环性。创新和开发适当的数字工具有重要的机会,以帮助释放这些重要领域的效率。这是第一篇论文,旨在从整体端到端生命周期的角度创建并定义不同的数字技术,以通知和实现医疗设备生产。它描述了使用数字创新来满足许多一次性和可重复使用的医疗设备的新兴机会的附加值。它解决了访问和使用结合学术界的集成多参与者HUB的价值,工业,healthcare,监管机构和社会帮助满足这些机会。例如,以具有成本效益的方式获得融合数字创新的专业试点设施和专业知识,材料科学,生物相容性,不育保证,商业模式和可持续性。它强调了学术研发活动(PRISMA审查2010年1月至2024年1月期间进行的最佳出版物)和美国FDA批准和销售的人工智能/机器学习(AI/ML)的实际列表中的明显差距。和增强现实/虚拟现实(AR/VR)-用于不同医疗保健应用的医疗设备。未来使用数字工具的潜在好处示例包括机器学习的潜在实施,通过有效监控关键过程数据(符合ISO11135:2014)来支持和实现灭菌产品的参数化发布,这将使利益相关者受益。本文还重点介绍了将数字孪生与扩展现实创新相结合的变革潜力,以提高医疗设备设计思维的效率。供应链和培训,以告知患者安全,循环性和可持续性。
Medical 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.