发表机构
PhAI Labs, Inc.; The Chinese University of Hong Kong; New York University; Stanford University School of Medicine; Shanghai Jiao Tong University; Stanford University; Harvard University; Princeton University（PhAI实验室公司; 香港中文大学; 纽约大学; 斯坦福大学医学院; 上海交通大学; 斯坦福大学; 哈佛大学; 普林斯顿大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出免疫世界模型，一种多尺度动作条件模型，通过进化AI科学家构建，用于预测免疫干预效果并生成可测试的治疗假设，如IL-36γ加SIRPα抑制。
AI 中文摘要
免疫疗法作用于细胞内在程序、组织生态系统和患者特异性免疫状态，然而大多数预测器分别处理这些尺度。我们使用受治理的进化AI科学家构建了免疫世界模型，这是一种动作条件模型，学习干预如何在细胞、组织和个体层面移动免疫状态。构建免疫世界模型的科学家搜索了候选架构和工作流程，所得世界模型在独立确认之前被冻结。冻结后的模型泛化到未见过的干预和生物学情境，恢复了干预特异性的细胞程序，整合了细胞和组织信息以改善生态系统和患者反应预测，并预测了未见过的扰动组合。免疫世界模型引导的分析随后将实测扰动与跨轴推断相结合，提名IL-36γ加SIRPα抑制作为互补轴治疗假设，而受治理的自我修正审计拒绝了所有筛选的细胞因子对。免疫世界模型提供了一个多尺度免疫模拟框架，连接了AI科学家驱动的模型构建、干预预测和可前瞻性测试的治疗假设生成。
英文摘要
Immune therapies act across cell-intrinsic programs, tissue ecosystems, and patient-specific immune states, yet most predictors address these scales separately. We used a governed evolutionary AI Scientist to construct the Immune World Model, an action-conditioned model that learns how interventions move immune states across cellular, tissue, and individual levels. The Immune World Model--building Scientist searched candidate architectures and workflows, and the resulting world model was frozen before independent confirmation. The frozen model generalized to unseen interventions and biological contexts, recovered intervention-specific cellular programs, integrated cell and tissue information to improve ecosystem and patient-response prediction, and forecast unseen perturbation combinations. Immune World Model--guided analysis then combined measured perturbations with cross-axis inference to nominate IL-36$γ$ plus SIRP$α$ inhibition as a complementary-axis therapeutic hypothesis, whereas a governed self-correction audit rejected every screened cytokine pair. The Immune World Model provides a framework for multiscale immune simulation that connects AI Scientist-driven model construction, intervention forecasting, and the generation of prospectively testable therapeutic hypotheses.
