Asthma is a devastating disease affecting more than 334M people in the world. 40-60% of them suffer from moderate to severe asthma of which 30% would benefit from additional remote monitoring and/or digital health tools. Digital tools often focus on measuring clinical parameters and do not translate the findings into self-management advise or risk prediction. Nor is the potential of education fully leveraged. The use of artificial intelligence is not yet entering the domain of respiratory diseases as it is the case in cardiology or diabetes. 

However, it has been shown in literature that easy algorithms can improve asthma control by 30% by increasing therapy adherence. As artificial intelligence opens up the door towards risk predictions and self-learning medication and therapy adaptations, this session will specifically zoom in on the potential of AI in predicting risks for exacerbations and loss of asthma control. 

We will also focus on the potential of digital biomarkers in monitoring asthma patients. How can these parameters drive AI-based predictive models? What makes sense and what not?

Lastly this session will focus on how digital tools can increase patient engagement. How can we ensure that patients stay onboarded, as well as medical staff? Can we calculate the impact from the tools to what it means in terms of savings for healthcare systems? And how this is affected by patient engagement? Can we formulate some guidelines towards future developers and policy? Treatment is good but prevention is better, and for that we need the tools, the engaged patients and a favorable environment. 

The session will share insights of recently published data, next to the announcement of a promising clinical trial that will start in Belgium and the Netherlands in Q2 2025.