Bench-to-Bedside Core

工作台至床边核心-总结 使用机械模型来帮助理解实验结果的过程， 告知临床决策取决于用于开发、分析、实施 调整和展示模型和结果。此外，必须对模型进行校准， 概括实验和临床观察，无论是在他们的行为范围，以及 结果的内在可变性，然后才能用于具体影响一个或多个临床 决策（例如，预测新的治疗策略）。理论转向也有一个实际的方面 将预测转化为可行的临床决策，需要工具来生成患者队列，模拟 临床试验，并以可视化和易于使用的方式呈现结果，以便临床医生可以立即 理解并操纵它们。因此，“从工作台到床边”核心的核心重点是 整合实验、临床数据和模型，以协助假设生成、检验和 验证（项目1），并使用临床相关工具将成功转化为临床环境 （项目2）。这将通过以下方式实现：目标1，探索统一原则的核心模式， 演变、异质性和治疗反应;目标2，放射组学、病理组学和广义集 用于整合实验和临床数据以促进数学模型的分析工具 目标3：决策支持工具，包括“i”期试验， 用于临床试验的动态优化疗法。我们在这里开发的工具和方法是 因此适用于更广泛的实验和临床数据，并将作为 这个项目的一个重要遗产是推动实验室到旁边的科学。

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.