Previous Workshops — Summary and Publications Now Available +++

Previous Workshops — Summary and Publications Now Available Digital Twins in Heart, Lung, Blood, and Sleep Research In late 2025, NHLBI hosted a virtual workshop entitled, “Digital Twins in Heart, Lung, Blood, and Sleep Research Virtual Workshop” to highlight the latest accomplishments in heart, lung, blood, and sleep (HLBS) Digital Twins (DT) research and to identify gaps and opportunities in this cutting edge research. A multidisciplinary group of experts gathered to assess current DT technology and identify key opportunities for its growth and practical application in HLBS research. See summary and related publications below: Summary, Recordings, and Program Book Digital Twins in Heart, Lung, Blood, and Sleep Research Virtual Workshop https://www.nhlbi.nih.gov/events/2025/digital-twins-heart-lung-blood-and-sleep-research-virtual-workshop The Digital Twins in Heart, Lung, Blood and Sleep Research Workshop took place virtually on September 25–26, 2025. Engineering Fit-for-Implementation Digital Twins Across the Total Product Lifecycle of Next-Generation Dental Restorative Materials: A Translational Intelligence Strategy for Real-World Impact https://www.computer.org/csdl/proceedings-article/models-c/2025/799000a203/2ckIfkOCKFG Abstract A Digital Twin (DT) is a set of virtual information constructs that mimics the structure, context, and behavior of a natural, engineered, or system-of-systems. It is dynamically updated with data from its physical twin, possesses predictive capabilities and supports decision-making processes that garner value. Bidirectional interaction between the virtual and the physical systems is central to functionalizing a digital twin. Recently, Biomedical Digital Twins (BDTs) are poised to revolutionize biomedical innovation by enabling predictive, realtime modeling of complex biological and engineered systems. However, despite their potential, most BDTs fail to reach deployment due to a fundamental misalignment with clinical workflows, regulatory structures, usability requirements, and systems-level constraints. This paper introduces a new class of digital twins, termed Fit-for-Implementation Digital Twins (FiDTs), designed to address the translational gap through an engineering-informed, stakeholder-driven, and lifecycle-integrated strategy. The primary audience for this article includes biomedical digital twin innovators and clinical stakeholders (e.g. physicians, caregivers, and patient advocates). We present a novel translational framework that embeds three foundational constructs into the engineering of BDTs: Fit-for-Purpose for scientific and mechanobiological validation, Fit-for-Implementation for realworld deployment readiness, and Technology- and EngineeringReadiness for structured decision-making and maturity assessment across the Total Product Lifecycle. FiDTs evolve digital twins into dynamic, regulatory-aware, and context-sensitive ecosystems, capable of simulating system-to-system interactions, accelerating preclinical validation, informing adaptive trial design, and integrating with electronic health record infrastructure. To reliably maintain and sustain these biomedical DTs, we propose a Multi-Participatory Twin Engineering Model to anchor stakeholder co-development from ideation to implementation to ensure co-development with clinicians, regulators, payers, caregivers and patients from the outset. This paper outlines a scalable, modular approach that harmonizes simulation fidelity with deployment feasibility. It includes actionable tools for risk mitigation, accessibility modeling, and global context adaptability, enabling DT systems that are not only predictive, but also trusted, scalable, and ethically grounded. Furthermore, we present the application of the proposed framework for FiDTs to accelerate critical milestones in the end-to-end translation of next-generation dental restorative materials (e.g., composite resins, ceramics, smart materials, sealants) as a representative case study of BDTs in biomedical innovation. In advancing the FiDT concept for dental health, we offer a visionary yet pragmatic foundation for next-generation BDT engineering. This foundation supports translational science mandates, anticipates regulatory evaluation, and accelerates the delivery of accessible, sustainable innovations in oral health and beyond. Towards Credible Digital Twins for Basic and Preclinical Research https://www.nature.com/articles/s43586-025-00454-3 Digital twins are well established in industrial settings, but there has not been wide adoption in biomedical settings. Digital twins for biomedical applications are now possible with the inclusion of artificial intelligence and the potential to combine mechanistic and clinical models that learn and adjust for human variability.