29.10.2024 Reports online 2023

Online Conference of the Clinical Platform PerMed-COPD

Investigators from all projects within the PerMed-COPD platform, joined by external researchers, e. g. from the Deutsches Krebsforschungsinstitut (DKFZ; German Institute for Cancer Research; Heidelberg), came together on December, 3rd 2023 to present and discuss recent development in the fields of expertise that are to be considered in modern personalized medicine. 

The first part of the interesting program  focused on clinical studies. C. Vogelmeier, Philipps-Universität Marburg, presented a detailed and interesting overview of recent and currently ongoing international clinical studies on COPD, which, due to the complexity of the disease, point out the importance of looking into the individual characteristics of every patient. He addressed the challenges of diagnosing COPD, especially in early stages, its co-morbidities, details on the disease course and on exacerbations. S. Dias Almeida, DKFZ, presented recent findings that anomaly-based assessment of chest CTs is a very promising approach for the diagnosis of COPD.

The second part dealt with clinical decision support systems (CDSS). T. Schleicher, Labvantage Biomax GmbH, gave an introduction to goals, features, and challenges of clinical decision support systems (CDSS). CDSSs can be used to support the diagnosis, therapy decisions, monitoring, and management of chronic diseases. A key criterion in their success is user acceptance. R. Holle and T. Niedermaier, Ludwig-Maximilians-Universität München, shed light on economic aspects of CDSSs, which can only gain widespread acceptance if cost implications as well as cost effectiveness are within an acceptable range. 

In the final part of the meeting, investigators from Philipps-Universität Marburg concentrated on biomolecular aspects in the diagnosis and prediction of COPD. J. Schumacher gave interesting insights into genome-wide association studies, which use polygenic risk scores (PRS) for genetic prediction and risk stratification mainly on the basis of inherited genetic predisposion. K. Laakmann emphasized the role of extracellular vesicles (EVs), isolated from the patients’ blood, as biomarkers in precision medicine. R. Martin presented machine learning-based data analysis as a key factor in using biomolecular data as a tool towards their application in disease diagnosis and in predicting the disease course.