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

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.

CF lung disease begins early in life (pre-school age) and often progresses in the absence of clinical signs and symptoms. Consequently, there has been an increasing emphasis on early intervention strategies to prevent lung damage during this critical period of disease progression, for which objective outcome measures that capture and track lung disease are needed. One measure of disease progression is the lung clearance index (LCI), obtained by multi-breath washout (MBW). In March 2018 the American Thoracic Society published its first technical statement on MBW technology for pre-school children. In that document the authors highlight the importance of future technical advances that may allow optimisation of MBW device design; they specifically state that "an example of one such area is advances in mainstream O2 analysis, which may one day negate the need for sidestream O2 analysis and adjustments for associated sample flow rate.... This is important given the increased susceptibility of pre-school MBW to sources of technical error." The applicants have developed the mainstream O2 analysis technology referred to in this statement. Crucially, this molecular flow sensing (MFS) technology is practical in a clinical setting: it is simple to undertake, it is non-invasive, it does not require ionising radiation, it does not require expensive scanners and reagents and it is sufficiently simple to conduct that it could be used in any standard lung-function testing laboratory. These attributes give MFS the potential to be a world-leading disruptive technology. Finally, we note that in comparison to current MBW equipment, it has clear technical superiority.

The proposed research will advance the capability of MFS technology by making it suitable for studies of children with CF. In particular, the highly accurate time-resolved measurements will allow calculation of an idealised lung clearance index. The LCI is recognised as an attractive clinical endpoint for studies of CF as the LCI is a summary statistic combining a number of different factors, and the development of an idealised-LCI (i-LCI) will address many of its remaining shortcomings. In addition, however, our structural model of the lung makes possible the identification of a number of different causes of inhomogeneity (currently all combined within the LCI). These different factors are likely to reflect different aspects of pathology in CF (e.g., irreversible bronchiectasis versus reversible inflammation and mucus plugging), and so eventually may prove to be of more clinical value than the i-LCI itself. As more novel therapeutic interventions become available that directly target the dysfunctional CF transmembrane conductance regulator, i-LCI may be a functional parameter suitable to establish whether CF drugs such as transmembrane conductance regulator modulators will impact lung function trajectories over time in young children where early intervention with effective treatments could have the most pronounced long-term effect.

MFS technology will contribute in establishing the UK as a global leader in respiratory monitoring, particularly for stratification of airways disease. 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. One requirement is to be able to detect and track progression of lung damage much earlier in the overall disease process. A second requirement is for measurements that are better for stratifying patients and predicting their individual responses to a particular treatment. A third requirement is for measurements that can track response to therapy. Finally, there is a need for measurements that can help us to understand better the onset and development of exacerbations, as these are sentinel events in CF and other airways diseases, and are associated with major healthcare expenditure.