EDUCATIONAL RESOURCE FOR TUMOR HETEROGENEITY

肿瘤学家认为肿瘤的自然历史与 使用可能导致不正确的非正式推理的治疗 结论。肿瘤学家的生物学假设和假设 使用往往会产生违反直觉的后果。一大堆的 现有的研究文献描述了整个人的计算 假设在细胞水平上的后果，但这种知识具有 在很大程度上是肿瘤学家无法接触到的，而且通常未能 影响他们的思维或提高他们的直觉。因此， 肿瘤学家最佳利用现有资源的能力 抗癌药物受到阻碍。 因此，我们建议开发一个资源包，包括 生物数学建模软件、教程和文档。这个 目标是培训当前和未来研究肿瘤学家的理论 肿瘤细胞种群动力学应用于癌症治疗，领先 改进新假说的选择，以在临床和 实验室研究，以及对结果的改进解释。 目标1：为培养医学生，提供一个简短的入门模块 关于肿瘤异质性的研究将被开发用于课堂培训。 该单元将包括讲座材料、印刷学习材料和 基于模拟的练习。目标2：培训肿瘤学研究员， 将开发一套自我指导的学习模块。我们的目标是 开发了一组教程课程，完整贡献于 临床肿瘤学方面的杰出研究人员。教程将演示 肿瘤细胞动力学的关键课程，同时教授程序的使用 用于结合特定的生物现象(转移、 分化、非线性剂量反应和药物相互作用， 多效性耐药，多种耐药机制，血管生成， 治疗引起的突变、毒性等)。目标3：积极主动 癌症研究人员，一个灵活的假设中立的建模资源将 被开发出来。建立在为培训开发的教程的基础上 伙计们，我们将提供一个软件套件，让研究人员 面对一个特定的治疗问题来描述，在最自然的 方法，自己对疾病的自然病史的概念，并加以训练 他们自己，发展对其后果的洞察 假设。

Oncologists think about the natural history of tumors in interaction with treatments using informal reasoning that can lead to incorrect conclusions. The biological assumptions and hypotheses that oncologists use often have counterintuitive consequences. A substantial body of research literature exists describing the calculation of the whole-person consequences of hypotheses at the cellular level, but this knowledge has been largely inaccessible to oncologists, and has generally failed to affect their thinking or improve their intuition. As a result, the ability of oncologists to make optimal use of currently available anticancer agents has been impeded. Consequently, we propose the development of a resource package consisting of biomathematical modelling software, tutorials, and documentation. The goal is to train current and future research oncologists in the theory of tumor cell population kinetics as applied to cancer treatment, leading to improved selection of new hypotheses to test in clinical and laboratory studies, as well as improved interpretation of results. Objective 1: For training medical students, a short introductory module on tumor heterogeneity will be developed for use in classroom training. The module will consist of lecture materials, printed study materials and simulation-based exercises. Objective 2: For training oncology fellows, a suite of self-directed study modules will be developed. The goal is a set of tutorial lessons developed with integral contributions from outstanding researchers in clinical oncology. Tutorials will demonstrate key lessons in tumor cell kinetics, while teaching the use of the program for incorporating specific biological phenomena (metastasis, differentiation, nonlinear dose-response and drug interactions, pleiotropic resistance, multiple resistance mechanisms, angiogenesis, treatment-induced mutation, toxicity, etc.). Objective 3: For active cancer researchers, a flexible hypothesis-neutral modeling resource will be developed. Building on the tutorials developed for training of fellows, we will provide a software suite which will allow researchers facing a particular treatment question to describe, in a most natural way, their own conceptions of the disease natural history, and to train themselves, developing insights into the consequences of their hypotheses.