为了进一步优化放射治疗，需要针对个体患者的风险状况进行更加个性化的治疗，剖析患者特异性肿瘤和正常组织对多模式治疗的反应。放射生物学的新进展，使用类似于 3D 模型的体外患者特异性复杂组织和空间单细胞水平的多组学方法，可能会为肿瘤和正常组织的放射反应提供前所未有的见解。在这里，我们描述了必要的团队努力，包括放射肿瘤学的所有学科，将这些数据整合到临床预测模型中，并将来自临床实践的相对“大数据”链接起来，从而实现准确的患者分层以实现个性化治疗方法。版权所有 © 2024作者。由爱思唯尔公司出版。保留所有权利。

To further optimize radiotherapy, a more personalized treatment towards individual patient's risk profiles, dissecting both patient-specific tumor and normal tissue response to multimodality treatments is needed. Novel developments in radiobiology, using in vitro patient-specific complex tissue resembling 3D models and multiomics approaches at a spatial single-cell level, may provide unprecedented insight into the radiation responses of tumors and normal tissue. Here, we describe the necessary team effort, including all disciplines in radiation oncology, to integrate such data into clinical prediction models and link the relatively "big data" from the clinical practice, allowing accurate patient stratification for personalized treatment approaches.Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.