Bench-to-Bedside Core

从工作台到床边核心-摘要 使用力学模型来帮助理解实验结果和 为临床决策提供信息依赖于开发、分析、实现、 调整和展示模型和结果。此外，必须对模型进行校准，以便它们 根据它们的行为范围和临床观察总结实验和临床观察 结果的内在变异性，然后才能被用来具体影响一个或多个临床 决策(例如，预测新的治疗策略)。将理论转化为理论也有一个实际方面 将预测转化为可操作的临床决策，需要工具来生成患者队列，模拟 以直观且易于使用的方式提供临床试验和结果，以便临床医生可以立即 理解并操纵它们。因此，长凳到床边核心的中心焦点是 集成实验、临床数据和模型，以帮助生成、测试和 验证(项目1)，并使用与临床相关的工具将成功转化为临床环境 (项目2)。这将通过：目标1，探索统一原则的核心模型来实现 进化、异质性和对治疗的反应；目标2，放射组学、病理组学和一个普遍集 用于集成实验和临床数据以简化数学模型的分析工具 开发和校准；以及目标3，决策支持工具，包括“I”阶段试验和 用于临床试验的动态优化治疗。我们在这里开发的工具和方法是 泛化，因此适用于更广泛类别的实验和临床数据，并将用作 这个项目的一个关键遗产是推动从板凳到旁边的科学。

Bench to Bedside Core - Summary The process of using mechanistic models to assist with understanding experimental results and informing clinical decisions depends on a suitable framework for developing, analyzing, implementing, adjusting and presenting the models and results. Furthermore, models must be calibrated so that they recapitulate experimental and clinical observations both in terms of their range of behavior as well as the intrinsic variability of outcomes before they can be used to specifically impact one or more clinical decisions (e.g. predict novel treatment strategies). There is also a practical aspect of turning theoretical predictions into actionable clinical decisions that requires tools to generate patient cohorts, mimic clinical trials and present results in a visual and easy to use manner such that clinicians can immediately understand and manipulate them. The central focus of the Bench-to-Bedside Core is therefore to integrate experiments , clinical data, and models to assist with hypothesis generation, testing, and validation (Project 1), and translate successes into a clinical setting using clinically-relevant tools (Project 2). This will be accomplished through: Aim 1, core models that explore unifying principles of evolution, heterogeneity, and response to treatment; Aim 2, Radiomics, Pathomics, and a generalized set of analysis tools for integrating experimental and clinical data to facilitate mathematical model development and calibration; and Aim 3, decision support tools including Phase “i" trials and dynamically optimized therapy for use in clinical trials. The tools and methods we develop here are generalized and therefore suitable to a wider class of experimental and clinical data and will serve as a key legacy from this project to drive bench-to-beside science.