The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA—disseminated and implemented in over 70 countries globally—is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA (Contre les Maladies Chroniques pour un Vieillissement Actif)-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease.

Sublingual immunotherapy has been proven as a well-tolerated and effective treatment for allergic rhinitis. Within this type of treatment, GRAZAX® is the most documented product in terms of safety and efficacy. The objective of this study was to identify the patients’ expectations and level of treatment satisfaction, as well as the clinical management of patients with moderate/severe allergic rhinoconjunctivitis treated with GRAZAX®. This was a non-interventional, observational, multi-centre, open-label study involving a total of 131 adult patients aged 18–66 years with confirmed diagnosis of grass-allergy and initiated treatment with GRAZAX® between June 2010 and April 2011. In the pollen season after starting treatment, 56.6% of patients stated that their symptoms were much less/less intense, 86% needed less symptomatic medication for control of their symptoms, and 74.4% manifested to have improved (quite/a lot) as regards their allergic disease since treatment was initiated as compared with previous grass pollen season. The patient satisfaction with GRAZAX® was measured using a visual analogue scale (VAS) between 0 (minimum satisfaction) and 100 (maximum satisfaction) comprising five different items: effectiveness, tolerability, cost, convenience and overall satisfaction. The results obtained for each item were [mean (SD)]: 74.7 (18.1), 70.3 (36.1), 39.3 (25.8), 86.2 (12.6), 78.4 (15.8) respectively. The patient’s level of satisfaction is highly influenced, especially in terms of assessment of effectiveness, tolerability and convenience, by the information provided by the specialist. In summary, it can be concluded that improved communication leads to increased patient knowledge, greater patient compliance, and increased patient satisfaction.

Chronic respiratory diseases (CRDs), including asthma and chronic obstructive pulmonary disease (COPD), represent significant global health challenges, contributing to substantial morbidity and mortality. As the prevalence of CRDs continues to rise, particularly in low-income countries, there is a pressing need for more efficient and personalized approaches to diagnosis and treatment. This article explores the impact of emerging technologies, particularly artificial intelligence (AI), on the management of CRDs. AI applications, including machine learning (ML), deep learning (DL), and large language models (LLMs), are transforming the landscape of CRD care, enabling earlier diagnosis, personalized treatment, and enhanced remote patient monitoring. The integration of AI with telehealth and wearable technologies further supports proactive interventions and improved patient outcomes. However, challenges remain, including issues related to data quality, algorithmic bias, and ethical concerns such as patient privacy and AI transparency. This paper evaluates the effectiveness, accessibility, and ethical implications of AI-driven tools in CRD management, offering insights into their potential to shape the future of respiratory healthcare. The integration of AI and advanced technologies in managing CRDs like COPD and asthma holds substantial potential for enhancing early diagnosis, personalized treatment, and remote monitoring, though challenges remain regarding data quality, ethical considerations, and regulatory oversight.