Ruijin Hospital Leads Establishment of Healthcare Digital Twin Alliance, Launches "50 Million Human Health Digital Twin Plan"

The Healthcare Digital Twin Alliance was established. How can health information accumulated through repeated examinations, long-term follow-up, and daily monitoring be connected to detect disease risks earlier? This is the question that healthcare digital twins hope to answer. By integrating longitudinal health data with dynamic models, researchers attempt to map the trajectories of individual health changes, providing a basis for disease prevention and personalized diagnosis and treatment. On October 30, the Healthcare Digital Twin Alliance was officially established at Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. Experts in related fields and editors of top international journals jointly explored, around the integration of population health and artificial intelligence, the development pathways of healthcare digital twins in disease mechanism research, dynamic monitoring, risk prediction, scientific evaluation, and clinical translation. Building an individual "digital life" health coordinate. It is reported that the Healthcare Digital Twin Alliance (ICDT-HM), initiated under the leadership of Ruijin Hospital, brings together research forces from universities, medical institutions, and related fields at home and abroad. At the seminar, experts and scholars from universities and medical institutions such as Stanford University, the University of Oxford, Macau University of Science and Technology, Wenzhou Medical University, and Duke-NUS Medical School, as well as editors of the Nature series of journals, participated in exchanges both on-site and online. The alliance will promote the deep integration of large-scale longitudinal population cohorts with artificial intelligence, build international consensus on data standards, cross-population validation, and data governance, and gradually construct predictable and simulatable digital twins of human health. Ning Guang, academician of the Chinese Academy of Engineering and president of Ruijin Hospital, introduced that a "global digital navigation" should be built for human health: reflecting the present, tracking the future, guiding intervention, and continuously learning. The significance of navigation lies not in predicting the endpoint, but in enabling people to choose a path before arrival. "Perhaps the most profound value of digital twins lies precisely in this: first walking through the future in the virtual world, so that diseases that could have been avoided need not occur in reality." Ruijin Hospital has proposed the concept of an "AI-native hospital," making AI the coding gene of a new type of hospital and health service system. By gathering multidimensional data such as biological, physiological, psychological, behavioral, social, and environmental data, it explores the construction of an individual's "digital life" coordinate, shifting health from the binary judgment of "sick" and "not sick" to a measurable, predictable, and navigable continuous trajectory. Speaking of open sharing, Ning Guang said, "Our principle is to comply with the law and regulations, keep data securely local, and let models and knowledge go global. However, no matter how precise a twin is, it is only a mirror image; no matter how massive the data, it is only a projection. The original aspiration of medicine is always the warm human being in front of the mirror." Deepening international cooperation to promote the translation and application of healthcare digital twin achievements. Promoting the translation of healthcare digital twin achievements. Luo Dajin, director of the Shanghai Municipal Science and Technology Commission, introduced that healthcare digital twins stand at the intersection of artificial intelligence, life sciences, and data elements. He expects that the alliance, bringing together first-class universities, medical institutions, and builders of national population cohorts at home and abroad, can focus on major diseases such as metabolic diseases, cardiovascular and cerebrovascular diseases, and tumors, integrate multidimensional data such as clinical diagnosis and treatment, long-term follow-up, multi-omics, and wearable devices, and strengthen basic research and clinical validation; promote the construction of large population cohorts, unify data standards, and explore effective pathways for privacy protection, compliant authorization, trusted circulation, and security governance; and deepen international cooperation to promote the translation and application of healthcare digital twin achievements. Francesca Cesari, senior editor for biological, clinical, and social sciences at Nature, noted that study design, data quality, external validation, and reproducibility are as important as data scale, and that predictive performance cannot replace clinical evidence. Which populations and scenarios a model applies to, what limitations exist, and whether it can improve patient outcomes all require careful evaluation. "The value of digital twins should be reflected in better-grounded clinical decisions, more equitable and effective medical services, and a reduction in the burden of disease." Zhang Kang, vice dean of the Faculty of Medicine at Macau University of Science and Technology and chief scientist of the National Clinical Research Center for Eye Diseases, introduced the alliance's development blueprint and core work, with a focus on sharing the "50M Human Health Digital Twin Initiative." This initiative is a long-term scientific research plan proposed by the alliance for precision health, aiming to gradually build, through multi-party collaboration, a research system integrating longitudinal health data with dynamic models, providing support for disease prediction, precision prevention, and personalized medicine. "Fifty million is the planning target, and the related construction will be explored and advanced in stages. The alliance will promote the deep integration of large-scale longitudinal population cohorts with artificial intelligence, build international consensus on data standards, cross-population validation, and data governance, and gradually construct predictable and simulatable digital twins of human health." It is reported that Ruijin Hospital has already accumulated considerable experience for this plan in the earlier stage. Among them, Wang Weiqing, director of the Department of Endocrine and Metabolic Diseases, introduced the research foundation and latest progress of the China Metabolic Analytics Project (ChinaMAP). The official website and digital hub deeply integrate deep whole-genome sequencing data from more than 10,000 cases, large prospective cohort studies, landmark national multicenter RCT studies, and nationally representative metabolic disease surveillance data. Through this digital sharing portal, ChinaMAP has achieved centralized display of data results across regions, studies, and omics, creating an open ecosystem for the global scientific research community. The open sharing of this major metabolic disease research resource will provide core strategic support for revealing the pathogenesis of metabolic diseases specific to the Chinese population, formulating precision intervention strategies, and promoting the leapfrog development of China's precision medicine cause.