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The Idealised Lung Clearance Index: tuning in to the silent years of cystic fibrosis

理想的肺清除指数：适应囊性纤维化的沉默岁月

基本信息

批准号：
EP/T001186/1
负责人：
Grant Ritchie
金额：
$ 58.78万
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FT001186%2F1
关键词：
Idealised Lung Clearance Index tuning

项目摘要

This proposal deals with an emerging and disruptive technology known as molecular flow sensing (MFS) of human breath. MFS allows highly precise and accurate measures of gas flows and concentrations such that a simple non-invasive breath test can be used to detect the onset of early stage airways disease, potentially of great strategic significance as the societal and financial costs of chronic airways disease are huge. The difficulty in identifying the presence of early airways disease and tracking change in disease state (progression or regression) with precision remains a serious problem for both medicine and industry. The standard approach of spirometry (for example, measuring how much air you can breathe out in a given time) does not identify the presence of disease in the lung until the pathology is well established, and this limits the opportunity for early intervention before there is significant irreversible structural damage within the lung. However, it is very difficult to justify starting expensive therapies without clear evidence from a marker showing the early presence of disease. In industry, an ability to track changes in lung function with precision would reduce greatly the number of patients that need to be recruited for a clinical trial. In turn, this would significantly reduce costs and addresses a major bottleneck in the whole drug development pipeline. Finally, the cost of new drugs is such that it will be impossible to use them without first determining which patients will benefit most. The unprecedented precision and accuracy of MFS technology has the potential to provide an early marker of pathology through the measurement of the inhomogeneity of the lung and thereby address many of the issues highlighted above. This proposal specifically relates to the development of MFS technology for use with pre-school children with cystic fibrosis where a "window of opportunity" exists for early diagnosis of lung disease and intervention. Here, there are two technical requirements: (i) to reduce the timescale for the breath test, and (ii) to reduce the size of the instrument. Requirement (i) will be addressed by incorporating trace amounts of an inert gas into the inspired air to allow the time taken for it to sample the lungs to be obtained contemporaneously with "air" breathing data. Requirement (ii) will be achieved by miniaturizing the MFS device while retaining sufficiently high enough precision and accuracy to realise measures of lung inhomogeneity. The MFS method is the first that seeks to separate inhomogeneity in alveolar ventilation into a component that arises because of inhomogeneity in the way the lung inflates and another that represents the inhomogeneity in the amount of deadspace; as such, it has the potential to separate reversible from irreversible abnormalities in CF lung disease. The normally used Lung Clearance Index (LCI) cannot differentiate between irreversible structural damage and airway narrowing due to mucus secretion. This fact further highlights the disruptive nature of MFS technology.MFS technology directly addresses the core need for better ways of measuring lung disease, both for the development of novel therapeutics and for better management of patients with existing therapeutic options. As more novel therapeutic interventions become available that directly target the dysfunctional CF transmembrane conductance regulator, the quantitative data using the MFS may prove suitable to establish whether novel CF drug treatments will impact lung function measurements over time in young children where early intervention with effective treatments could have the most pronounced long-term effect.

本提案涉及一项新兴的颠覆性技术，即人类呼吸的分子流传感（MFS）。MFS允许高度精确和准确地测量气体流量和浓度，从而可以使用简单的无创呼吸测试来检测早期气道疾病的发作，这可能具有重要的战略意义，因为慢性气道疾病的社会和经济成本巨大。在识别早期气道疾病的存在和精确跟踪疾病状态变化（进展或消退）方面的困难仍然是医学界和工业界面临的一个严重问题。肺活量测定法的标准方法（例如，测量你在给定时间内可以呼出多少空气）在病理完全确定之前不能识别肺部疾病的存在，这限制了在肺部出现重大的不可逆转的结构损伤之前进行早期干预的机会。然而，如果没有明确的证据表明疾病的早期存在，就很难证明开始昂贵的治疗是合理的。在工业界，精确追踪肺功能变化的能力将大大减少临床试验所需招募的患者数量。反过来，这将显著降低成本，并解决整个药物开发管道中的一个主要瓶颈。最后，新药的成本如此之高，以至于如果不首先确定哪些病人将受益最大，就不可能使用它们。MFS技术前所未有的精确性和准确性有可能通过测量肺的不均匀性提供病理的早期标记，从而解决上述强调的许多问题。该建议特别涉及MFS技术的发展，用于患有囊性纤维化的学龄前儿童，其中存在早期诊断肺部疾病和干预的“机会之窗”。在这里，有两个技术要求：(i)减少呼吸测试的时间尺度，（ii）减少仪器的尺寸。要求(i)将通过在吸入空气中加入微量惰性气体来解决，以使其采样肺部所需的时间与“空气”呼吸数据同时获得。要求（ii）将通过MFS设备的小型化来实现，同时保持足够高的精度和准确度来实现肺不均匀性的测量。MFS方法是第一个试图将肺泡通气的不均匀性分离为肺膨胀方式的不均匀性和另一个代表死空间数量的不均匀性的组件；因此，它有可能区分CF肺部疾病的可逆性和不可逆性异常。通常使用的肺清除率指数（LCI）不能区分不可逆性结构损伤和由粘液分泌引起的气道狭窄。这一事实进一步凸显了MFS技术的颠覆性。MFS技术直接解决了更好地测量肺部疾病的核心需求，既可以开发新的治疗方法，也可以更好地管理现有治疗方案的患者。随着更多新的治疗干预措施的出现，直接针对功能失调的CF跨膜电导调节因子，使用MFS的定量数据可能适合于确定新的CF药物治疗是否会随着时间的推移影响幼儿的肺功能测量，其中早期干预有效的治疗可能具有最明显的长期效果。