LungCHEM-Py: A Computational Model for Predicting Asthma Exacerbation-Risk from Exposure to Indoor Air Pollutants

Asthma affects over 260 million people globally, placing a heavy burden on sufferers and costing the NHS approximately £1.1billion a year. Therefore, methods to reduce asthma exacerbations (AE) are sought. In recent years, indoor air pollutants, known as volatile organic compounds (VOCs) have been linked with AE, though definitive links between specific VOCs and health effects remain elusive. This project will characterise these links for target VOCs, and data will be incorporated into a model that predicts AE risk, based on indoor VOC concentrations. A new open-source Lung CHEMistry model in Python (LungCHEM-Py) will be developed, that calculates time-evolved lung VOC concentrations and produces corresponding numerical AE hazard indices. LungCHEM-Py will incorporate experimental data that will be obtained to characterise a) the chemical kinetics of target VOCs in contact with respiratory lining fluids and b) asthma responses of lung epithelial cells, following VOC exposure. Model evaluation will be performed, where simulated hazard indices for common household products (e.g., domestic cleaning products and fragrances) will be compared to that of a reference AE-linked compound. A workshop will be hosted for clinicians, researchers and policymakers to discuss the recommended changes in human behaviour and consumer choices for improving asthma symptoms, informed by LungCHEM-Py.