Research project
The high prevalence of documented allergic diseases underscores the pressing need for enhanced understanding of prevention strategies to reduce the burden on children, their families, and society at large. This need is strongly emphasized by patient organisations, providing the foundation for the current project application.
The rational for this project stem from the successful intervention of early food introduction, starting at 3 months of age, which effectively prevented food allergies at age 3, particularly peanut allergies, within a normal-risk, healthy population. The proposed investigations aim to contribute novel evidence concerning the impact of early food allergy prevention on the occurrence of food allergies, dietary intake, and the development of tolerance to birch allergens up to school age. Additionally, we seek to explore whether impaired skin barrier function during early infancy modifies the risk of allergic sensitization to airborne and food allergens, along with eosinophilic allergic inflammation by the time children reach school age.
To accomplish these objectives, we use data from the large-scale multicentre PreventADALL birth cohort study. This study comprises 2x2 factorial randomized controlled interventions, encompassing skin care and early food introduction, and involves 2395 children drawn from the general population in Norway and Sweden. PreventADALL has already conducted extensive biosampling and data collection, spanning from birth to school age.
We are in an era of "big data," where the analysis of large datasets target to revolutionize healthcare by uncovering patterns and insights that enable a shift from disease-centred to patient-centred care of asthma and Chronic Obstructive Pulmonary Disease (COPD). In respiratory care, integrating big data and artificial intelligence (AI) through novel digital tools like home spirometry systems, offers transformative interdisciplinary healthcare opportunities that are significant. By initially aligning comprehensive temporal home spirometry data from more than 15000 real-world asthma patients from year 2019, including COPD patients, encompassing symptoms, spirometry measurements, individual triggers, medication adherence, and environmental triggers, machine learning will facilitate the development of personalized, precise, and proactive care strategies.
The overall aim of PRISAAD is to develop and evaluate AI-assisted clinical prediction models integrated with remote home spirometry system for healthcare support, target to substantially improve the accuracy of asthma and COPD diagnosis and leverage self-management and prevention of exacerbation. In addition, patients will benefit from timely "what-if" scenarios generated by counterfactual explanations using personal temporal input data from home spirometry system.
This approach target to enhance patient engagement, improve health outcomes, and optimize healthcare resources. The accuracy and effect of proposed interventions will be validated by healthcare providers and patient involvement. The PANDA group aree co-founder behind a pioneering home spirometry system AsthmaTuner in 2014, owned by the big data provider MediTuner, and ranked as the best digital technology for asthma in Europe 2023 by Federation of Allergy and Airway diseases patient organisations (EFA), has uniquely positioned PRISAAD project to scientific contributions by generating new knowledge and opening innovative pathways for AI-research.
APPETITE study is a randomised controlled trial over 6-12 weeks. The inhalation flow app is an automated objective tool to measure the inhalation technique to customised treatment with metered dose inhaler (MDI) or dry powder inhaler (DPI). The app- and spirometry module consists of wireless hand-held spirometer measure the peak inspiratory flow rate, inspiration time and inspiratory volume and hardware that provides inspiratory resistance that is concordant with a specific inhaler. The research purpose is to evaluate the effect of the inhalation app- and spirometry module on patient’s inhalation technique.
A diagnostic study for asthma using a home spirometry system in primary care.
An observational study evaluating a home spirometry module for COPD over a 6-month period.