METEOR-Integrated Training Environment (METEORITE)

项目摘要 通过放射肿瘤学领域的现有进展，很明显，成功是最好的 这是生物学、物理学和临床医学专家合作的结果。然而，作为技术 治疗模式变得越来越复杂，专家们越来越难以 在自己的特定学科中保持尖端的专业化，同时， 促进多学科合作。虽然目前的研究生培训确实使受训者接触到 在他们自己之外，这种接触不足以在他们之间开展有意义的研究合作。 现代肿瘤学的劳动力。一个正式的培训计划，可以提供广度和深度， 肿瘤生物学、肿瘤免疫微环境、先进影像学和治疗等主题领域 技术和信息学是必要的，使受训者能够制定一套共同的跨学科 这些基础知识可用于加速放射肿瘤学的多学科研究。 考虑到癌症生物学、医学物理学和临床医学领域产生的大量数据， 放射肿瘤学，我们设想我们的罗宾计划交叉培训核心，METEORITE（METEOR 综合培训环境），将使用数据科学和信息学作为共同语言， 促进沟通，促进跨学科合作，最终目标是利用 在ROBIN网络中使用这种模式，以增加更大的肿瘤学工作人员之间的协作。 在目标1中，我们将首先在我们自己的METEOR ROBIN内开发跨学科培训计划 通过整合现有课程和已建立的培训计划来支持METEOR， 相关科学。学员将制定个性化的培训途径，使他们能够参与 在共同的课程，同时也定制他们的学习。在目标2中，我们将开发新的数字 关键高需求主题的内容资源，如临床试验设计和TME基础 在METEORITE中使用的非专业人员，也可以在更广泛的ROBIN中传播 网络最后，在目标3中，我们将开发和举办面对面和虚拟研讨会系列， 研讨会，以促进METEOR内部和整个ROBIN网络的学员凝聚力。的目标 这些系列研讨会和专题讨论会旨在培养ROBIN网络学员的领导技能， 同时，确保我们开发的内容可以传播和用于促进跨学科 在未来的劳动力市场中。通过对METEORITE的资助，我们将产生资源， 职业发展的专业知识，这将有助于未来的NIH T32应用程序集中在培训， 传播和促进多学科信息伙伴关系放射肿瘤学。

Project Summary Through existing advances in the field of radiation oncology, it has become clear that success is best achieved when experts in biology, physics, and clinical medicine collaborate. However, as technology and treatment paradigms grow more complex, it has become increasingly difficult for experts to maintain cutting-edge specialization in their own specific discipline and at the same time, converge to facilitate multi-disciplinary collaboration. While current graduate training does expose trainees to fields outside their own, this exposure is insufficient to develop meaningful research collaborations across the modern oncology workforce. A formal training program that can provide both breadth and depth in the theme areas of tumor biology, tumor immune microenvironment, advanced imaging and treatment technologies, and informatics is needed to allow trainees to develop a set of common cross-disciplinary fundamentals that can then be used to accelerate multidisciplinary research in radiation oncology. Given the amount of data generated in the fields of cancer biology, medical physics, and clinical radiation oncology, we envision that our ROBIN program cross training core, METEORITE (METEOR Integrated Training Environment), will use data science and informatics as the common language to facilitate communication and promote interdisciplinary collaboration, with the ultimate goal of leveraging this model across the ROBIN network to increase collaboration among the larger oncology workforce. In Aim 1, we will first develop an interdisciplinary training program within our own METEOR ROBIN Center by integrating pre-existing courses and established training programs to support METEOR and related science. Trainees will develop an individualized training pathway that will allow them to partake in common coursework while also customizing their learning. In Aim 2, we will develop new digital content resources for key high need topics such as clinical trial design and the fundamentals of TME for non-specialists to be used within METEORITE but also disseminated across the wider ROBIN network. Finally, in Aim 3, we will develop and host both in-person and virtual seminar series and symposia to promote trainee cohesion within METEOR and across the ROBIN network. The goal of these seminar series and symposia is to develop leadership skills among ROBIN network trainees and also to ensure our developed content can be disseminated and used to promote interdisciplinary collaboration in the future workforce. Through funding of METEORITE, we will generate resources and career development expertise that will facilitate a future NIH T32 application focused on training, disseminating and advancing multidisciplinary informatic partnerships radiation oncology.