Improving patient outcome by integrating the generic with the personal

癌症是医疗保健面临的两大挑战之一：三分之一的人会在一生中患上癌症。将这一点转化为产生这项提案的创意工厂，大约有30人以不同的身份参加了创意工厂，因此其中约10人将在有生之年患上癌症。虽然在癌症治疗方面取得了许多进展，但仍有方法可以改进治疗。例如，它通常通过手术、放射治疗和/或化疗相结合的方式进行治疗，但对这些治疗方法的确切相互作用以及不同人对它们的反应方式知之甚少。这使得为个别患者开出最佳治疗策略几乎是不可能的。该项目解决的挑战是建立一个框架，在该框架中通过预测建模的个性化透镜来看待疾病，以便改进未来的联合治疗计划。我们计划通过一个史无前例的多学科项目来做到这一点：以数学为主导，但利用我们在生物学、物理学和计算机科学方面的专业知识。我们的项目通过分层、多尺度的描述来反映生命的结构，其中非常详细地处理重要部分，例如包含肿瘤的器官，同时以更分块的方式描述整体的其余部分，能够有效地捕捉必要细节的本质。我们的长期目标是使我们的模型框架成为通用的，并适用于一系列疾病和综合疗法。在这个项目中，将建立一个普遍适用的框架以及相关的相互关联的数学和计算模型和方法。经过生物实验的验证，这些模型将得到完善，并填充数据，为我们的胶质瘤(一种脑瘤)的联合化疗/放射治疗提供临床有用的预测。该项目的每个组成部分都借鉴了研究人员提供的具体专门知识：-药物输送和肿瘤生长的三维空间分辨数学模型，将质量传输与细胞反应结合起来，并使用快速计算算法进行模拟，提供了对治疗反应的详细、针对患者的表示；-放射相互作用建模，以及加速准确放射治疗计划的相关算法，提供了放射治疗影响的细节；-实验细胞生物学工作，提供了验证模型的数据；-数学建模和支持协同实验将全身效应与疾病和个人特定的模型结合在一起；-对细胞内部和之间的信号、旁观者效应和转移进行过程代数建模，提供了细胞反应的模型。这些都将有科学成果，但该项目真正获得多学科好处的地方是这些工作包的接口，以及通过我们联合解决问题的方法的组合。通过这个项目，我们将通过解决一个具体而重要的例子，为我们20年的综合治疗框架目标奠定基础：胶质瘤的放射/药物联合治疗。该项目很有可能成为一种宣传工具，能够以直观的方式展示数学的公共利益。将通过各种社交媒体(例如，通过YouTube播放的动画，显示当地和患者规模的药物和辐射输送的时空变化)和更传统的参与形式(例如，在网上展示、在当地学校和科学节上进行演讲)来利用这一点。

Cancer is one of the top two healthcare challenges: 1 in 3 people will have cancer in their lifetime. To translate that to the ideas factory that generated this proposal, about 30 people attended the ideas factory in various capacities, therefore about 10 of them will have cancer during their lifetime. While many advances have been made in cancer treatment, there are still ways in which therapy can be improved. It is, for example, usually treated by combinations of surgery, radiotherapy, and/or chemotherapy, but the precise interaction of these treatments and the ways in which different people react to them is poorly understood. This makes it virtually impossible to prescribe the best therapeutic strategy for an individual patient. The challenge addressed in this project is to build a framework in which to view disease through a personalised lens of predictive modelling, in order to improve future combination therapy planning. We propose to do this through an unprecedented multidisciplinary project: mathematics-led, but drawing on our expertise in biology, physics, and computer science. Our project reflects the structure of life through a stratified, multi-scale description which deals with the important parts, e.g. the organ containing the tumour, in great detail, whilst describing the remainder of the whole in a more chunked way, able to efficiently capture the essence of the necessary detail. Our longer term goal is for our modelling framework to be generic, and adaptable to a range of diseases and combined therapies. In this project, a generally adaptable framework and the associated interconnected mathematical and computational models and methods will be created. Having been validated by biological experiments, these models will be refined and populated with data to provide clinically useful predictions for our exemplar, combined chemo/radiotherapy of glioma (a type of brain tumour). Each component of the project draws on specific expertise provided by the investigators: - three-dimensional, spatially-resolved mathematical models of drug delivery and tumour growth, coupling mass transport with cell response, and simulated using fast computational algorithms, provides a detailed, patient-specific, representation of response to therapy; - radiation interaction modelling, with associated algorithms to speed-up accurate radiation therapy planning, provides details of the influence of radiotherapy; - experimental cell biology work, delivers data with which to validate the models; - mathematical modelling and supporting synergy experimentation integrates whole-body effects with disease- and person-specific models; - process algebra modelling of signalling inside and between cells, bystander effects, and metastasis, provides models of cell response.These will all have scientific outputs, but where the project really reaps the benefits of multi-disciplinarity is at the interfaces of these work packages, and through the combination of our joint approaches to problems.Through this project we will lay the foundations for our 20-year goal of a generic framework for combined therapies by addressing a specific and important example: combined radiation/drug therapies for glioma. The project is very amenable to becoming an outreach vehicle capable of demonstrating the public benefit of mathematics in a visual way. This will be exploited through a variety of social media (e.g. animations showing the spatio-temporal variation of drug and radiation delivery at the local and patient scales, delivered via YouTube) and more traditional forms of engagement (e.g. web presence, presentations to local schools and at Science festivals).