Integrating data-driven biophysical models into respiratory medicine - BIOREME

将数据驱动的生物物理模型整合到呼吸医学中 - BIOREME

• 批准号: EP/W000490/1
• 负责人: Bindi Brook
• 金额: $ 97.27万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW000490%2F1
• 关键词: Integrating; data; driven; biophysical; models

Lung diseases such as Asthma and Chronic Obstructive Pulmonary Disease affect one in five people in the UK and kill someone every 5 minutes. The number of patients with these lung diseases was increasing in the NHS even before COVID-19. We are also learning about serious long-term effects of COVID-19 that will add to the existing burden on the NHS.There have been huge advances in technologies that allow scientists to see inside the lungs and measure what we breathe out. While this information has taught us quite a lot, it is still very difficult to combine different sources of information and turn it into new or improved treatments. Getting that useful information out of large amounts of medical test results requires sophisticated physics-based mathematical and statistical models run on powerful computers - a combination of techniques called data-driven biophysical multiscale modelling. The ability to develop those kinds of models will allow us to better understand how diseases start and how they progress.Our BIOREME network will support new research that uses these techniques to mimic biological and mechanical processes that occur throughout the lung. Using the information from thousands of lung tests, the idea is then to get these models to mimic real diseased lungs. In order to improve and build trust in these models, some of our projects will be focused on comparing their outputs to results from other lung tests. Medical scientists can then use such models to test what might happen in a particular type of lung disease, and to investigate possible responses to new treatments before testing these in patients. Most importantly, this will lead to the design of new drugs and improved trials for new treatments. The first step will be to get medics, imaging experts and mathematicians together with industry and patient group representatives to decide on which specific research areas to prioritise, where this form of modelling will make the most difference. This NetworkPlus award will then allow us to organise multiple events, in different formats, designed to help researchers to collaborate, and to come up with the best initial projects to help achieve our goals. We will then help the researchers to develop these into larger projects that will attract funding from other sources and continue the research into the future. Even after this funding runs out, BIOREME will provide a lively forum for lung researchers to continue solving problems using these advanced computational tools. Finally, BIOREME will support outreach activities to engage and educate communities and young people in the role that mathematics can play in medicine and healthcare, and to inspire a new generation of respiratory scientists from diverse backgrounds.

在英国，哮喘和慢性阻塞性肺疾病等肺部疾病影响着五分之一的人，每5分钟就会有人死亡。甚至在新冠肺炎之前，国民健康保险制度中患有这些肺部疾病的患者数量就在增加。我们还了解到新冠肺炎的严重长期影响，这将增加美国国家卫生研究院现有的负担。技术已经取得了巨大进步，使科学家能够看到肺部内部并测量我们呼出的东西。虽然这些信息教会了我们很多，但将不同的信息来源结合起来并将其转化为新的或改进的治疗方法仍然是非常困难的。要从大量医学测试结果中获得有用的信息，需要在功能强大的计算机上运行复杂的基于物理学的数学和统计模型-这是一种称为数据驱动的生物物理多尺度建模的技术组合。开发此类模型的能力将使我们能够更好地了解疾病是如何开始和发展的。我们的BIOREME网络将支持使用这些技术来模拟整个肺部发生的生物和机械过程的新研究。利用数千次肺部测试的信息，我们的想法是让这些模型模拟真实的病变肺。为了改善和建立对这些模型的信任，我们的一些项目将专注于将它们的结果与其他肺部测试的结果进行比较。然后，医学科学家可以使用这种模型来测试特定类型的肺部疾病可能发生的情况，并在对患者进行测试之前调查对新疗法的可能反应。最重要的是，这将导致新药的设计和新疗法的改进试验。第一步将是让医务人员、成像专家和数学家以及行业和患者团体代表一起决定优先考虑哪些特定研究领域，这种形式的建模将在哪些领域发挥最大作用。然后，这个NetworkPlus奖项将允许我们以不同的形式组织多个活动，旨在帮助研究人员合作，并提出最佳的初始项目来帮助实现我们的目标。然后，我们将帮助研究人员将这些发展成更大的项目，这些项目将吸引其他来源的资金，并在未来继续研究。即使在这笔资金耗尽后，BIOREME仍将为肺部研究人员提供一个活跃的论坛，让他们继续使用这些先进的计算工具解决问题。最后，BIOREME将支持外联活动，让社区和年轻人了解和教育数学在医学和医疗保健中可以发挥的作用，并激励来自不同背景的新一代呼吸系统科学家。