Chronic obstructive pulmonary disease (COPD) is the third most common cause of death worldwide. It is predicted to increase due to the aging population, thus posing a huge socio-economic burden. Existing treatment and prevention strategies do not adequately take into account the complex, multifaceted and heterogeneous pathophysiology as well as the diverse, sometimes very stressful comorbidities (cardiovascular, metabolic, etc.). Therefore, there is an urgent need to implement recent research results into improved COPD diagnosis and classification in clinical practice.

The goal of the PerMed-COPD integrated research platform is to implement a novel personalized strategy for the treatment and prevention of COPD. A prospective, randomized, controlled trial will evaluate the additional benefit of a clinical decision support system based on imaging biomarkers and clinical parameters in COPD compared to usual care. Novel pathophysiologically relevant biomarkers (polygenic risk scores, exosomes, microbiome) will be identified from existing biosamples and validated using machine learning techniques. Furthermore, an implementation analysis will be carried out that includes accompanying health economic research including a cost-benefit analysis of the new personalized strategy. The comparison of the personalized strategy with the standard treatment should allow an assessment of the short and medium-term cost-effectiveness.

The project consists of several collaborative partners. The Institute of Medical Informatics at the University of Münster handles the integration and ML-supported analysis of multi-omics data to identify new geno-phenotype associations.

Contact: Dr. rer. nat. Roman Martin  Leon Fehse

Information about the project

Funding reference number: 01EK2203F