大型队列已成为生物医药与公共卫生领域重要的开放性科研基础设施和卫生决策支撑平台，其意义不断凸显，多国已布局大型队列建设。聚焦典型的多主体协作的联盟式大型队列——欧洲癌症与营养前瞻性调查（EPIC）项目，分析其组织机制、经费来源、建设模式、标准化方案、资源管理与共享策略等，剖析其成功实施与运行的关键。分析显示，多主体协作的联盟分布式大型队列建设需要持续的投入和长效科研机制的保障，且通过前瞻顶层设计、建立协调统一的管理机制、开展标准全面的数据和生物样本收集、建立完善的政策保障体系，才可确保其持续、高质量建设。建议中国由政府主导规划并科学设计，建立一体化的大型队列组织和管理体系；设立专项进行长期稳定支持，确保大型队列的持续、高质量建设；建立标准统一的建设与管理方案，保证大型队列资源的规范化和系统化；提高数据资源规模、类型和质量，建立开放共享的高质量大型队列；探索建立合理的人类遗传资源保护和知识产权管理制度。

Large cohort study has become an important open scientific research infrastructure and health decision-making support platform in the field of biomedicine and public health. With increasingly highlighted significance, large cohort construction has been laid out in many countries. In this paper, by focusing on the organizational mechanism, funding source, construction mode, standardization scheme, resource management and sharing strategy, etc. of the European Prospective Investigation into Cancer and Nutrition (EPIC-Europe), the key to its successful implementation and operation was deeply analyzed, in order to provide experience reference for the construction of a comprehensive, shared and open large cohort with multi-agent collaboration. Results show that continuous input and long-term scientific research mechanism guarantee is indispensable to the construction of multi-agent collaborative alliance distributed large-scale cohort, and its sustainable and high-quality construction also requires forward-looking top-level design, a coordinated and unified management mechanism, standard and comprehensive data and biological sample collection, and a sound policy guarantee system. The following suggestions are made: the government should take a leading role in the planning and scientific design to establish an integrated large-scale cohort organization and management system; special projects with long-term stable support should be set up to ensure the continuous and high-quality construction of large cohorts; a standard and unified construction and management scheme need to be established to ensure the standardization and systematization of large cohort resources; the scale, type and quality of data resources should be improved to establish, open and share high-quality large cohorts; reasonable systems for the protection of human genetic resources and the management of intellectual property rights should be further explored.