At the Cluster Breakfast held at Sano, participants discussed how the concept of the digital twin\u2014a computer\u2011based, personalized model of a patient\u2014translates into real clinical decisions and the organization of healthcare. The event emphasized that a digital twin is not just modeling; above all, it is a tool that supports diagnosis, therapy planning, and real\u2011time monitoring of treatment effectiveness.<\/p>\n\n\n\n
Marian Bubak<\/a> (Scientific Affairs Director at Sano) outlined the center\u2019s mission: to develop computational methods and reliable simulations and transfer them into clinical practice, including through collaboration with universities, hospitals, and industry partners not only in Krakow and across Europe, but worldwide. Within this ecosystem, the digital twin becomes connective tissue linking patient data, disease models, and AI tools, shortening the path from research to the patient\u2019s bedside.<\/p>\n\n\n\n Magdalena Otta<\/a> (PhD Student in Extreme\u2011scale Data and Computing) presented applications of digital twins in cardiovascular disorders, with a focus on personalizing models for diagnostics and intervention selection. Clinically, the key elements are risk modeling, forecasting disease trajectories, and testing therapeutic strategies without exposing the patient to risk, thereby enhancing safety and treatment effectiveness.<\/p>\n\n\n\n Why clinics need digital twins<\/strong><\/p>\n\n\n Implementation conditions: trustworthiness, data, integration The upcoming Krakow Conference on Computational Medicine 2025 focuses on the \u201cVirtual Human Twin\u201d and the role of AI methods in linking clinical data with multiscale models, emphasizing ethics, trustworthiness, and reproducibility. For clinics, this means growing access to tools that combine imaging, physiological signals, and EHR into coherent, interpretable recommendations.<\/p>\n\n\n\n Digital twins can reduce unnecessary procedures by steering care toward the most promising therapeutic options and streamlining eligibility for interventions. From a system perspective, they offer better resource allocation and the creation of care pathways grounded in real\u2011world evidence, not only in population\u2011average trial results.<\/p>\n\n\n\n Where to start: implementation recommendations<\/strong><\/p>\n\n\n The Cluster Breakfast served as a forum for exchange and for announcing initiatives, including a conference on computational medicine. Organizers encourage following upcoming meetings and the post\u2011event video materials. The recording is available on the official Klaster LifeScience Krak\u00f3w channel<\/a>.<\/p>\n\n\n\n Why now<\/strong><\/p>\n\n\n\n The convergence of mature computational infrastructure, AI methods, and the growing availability of clinical data means the digital twin is moving beyond the concept stage. European initiatives around the Virtual Human Twin point to collaboration and standards that will accelerate adoption in practice.<\/p>\n\n\n\n Watch a short video created within the InSilicoHealth<\/strong> program, where young researchers explain what Digital Twins<\/strong> are and how they can support the development of personalized healthcare.<\/p>\n\n\n\nCardiology case: DVT and the cardiovascular system<\/h2>\n\n\n\n
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Effective deployment requires trustworthy, clinically validated models, access to standardized data, and integration with existing hospital systems. The organizational dimension also includes the competencies of medical teams and clear accountability pathways for decisions made with the support of simulations.<\/p>\n\n\n\nAI and the Virtual Human Twin<\/h2>\n\n\n\n
Value for patients and the health system<\/h2>\n\n\n\n
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Event context and what\u2019s next<\/h2>\n\n\n\n
Discover the concept of digital twins in medicine<\/strong><\/h3>\n\n\n\n