Clinical Trials associated with LungenClinic Grosshansdorf GmbH
NCT06752122
/ RecruitingPhase 1
Safety, Tolerability and Pharmacokinetics of Single-ascending and Multiple-ascending Doses of RCS-21 in Healthy Volunteers. a Double Blind, Randomized, Placebo Controlled Phase I Study.
The goal of this clinical trial is to evaluate the safety and tolerability of RCS-21 in healthy volunteers. Participants will be asked to inhale a single or multiple doses of RCS-21 for a maximum of 7 days and their health status will be constantly monitored.
COPD Exacerbation Modelling Study Using Daily-life Data From Unobtrusive Sensors - the TOLIFE Clinical Study A
This work is a multicentric prospective cohort study designed to improve chronic obstructive pulmonary disease (COPD) treatment and management. The study involves 150 patients diagnosed with COPD who are at risk of exacerbations. These patients are recruited from three tertiary hospitals in Spain, Germany, and Italy. The study will last 18 months, with a 12-month follow-up duration for each patient. The primary objective of this study is to develop and test Artificial Intelligence (AI)-based models that can predict moderate-to-severe COPD exacerbations early on. This will be done by analyzing daily-life data collected from unobtrusive sensors that monitor patients' psycho-physiological and environmental signals. By accurately predicting exacerbations, the study aims to support clinicians in providing more precise, optimized, and personalized treatment to COPD patients. A secondary objective is to train and test AI-based models to estimate the 12-month dynamics of health-related quality of life (HRQoL) in COPD patients. This will involve analyzing data related to the patients' functional exercise capacity, dyspnea (difficulty breathing), and health-related quality of life, as measured by the Clinical COPD Questionnaire (CCQ) score and the COPD Assessment Test (CAT) score.
GUIding Multi-moDal ThErapies Against MRD by LiquidBiopsies in Non Small Cell Lung Cancer- GUIDE.MRD-03-NSCLC
Improving personalized cancer treatments and finding the best strategies to treat each patient relies on using new diagnostic technologies. Currently, for non small cell lung cancer (NSCLC), the methods used to decide who gets additional post radical (surgery or definite chemo-radiotherapy) treatment are suboptimal. Some patients get too much treatment, while others do not get enough. There is a new way to explore if there is any cancer left in a patient's body using circulating tumor DNA (ctDNA) detected in blood samples. This can help decide who needs more treatment. Even though many tests have been developed, it has yet to be determined which test performs best at relevant time points. The GUIDE.MRD consortium is a group of experts, including scientists, technology, and pharmaceutical companies. The consortium is working on creating a reliable standard for the ctDNA tests, validating their clinical utility, and collecting data to help decide on the best treatment for each patient. GUIDE.MRD-03-NSCLC is a part of the GUIDE.MRD project.
Author: Steuer, S ; Elmas, H ; Claussen, M ; Rabe, K ; Önal, B ; Mehdi, E ; Hantzsch-Kuhn, B ; Ince, Ü ; Welker, L
01 Mar 2025·Pneumologie
Results from a Phase II trial (AIRLEAF) of a cathepsin C (dipeptidyl peptidase 1) inhibitor, BI 1291583, in adults with non-cystic fibrosis bronchiectasis*
Author: Rauch, J ; Eickholz, P ; Chotirmall, S ; Armstrong, A ; Frahm, E ; Gupta, A ; McShane, P ; Shteinberg, M ; O'Donnell, A ; Eleftheraki, A ; Mall, M ; Sauter, W ; Hasegawa, N ; Watz, H ; Chalmers, J
100 Deals associated with LungenClinic Grosshansdorf GmbH
Login to view more data
100 Translational Medicine associated with LungenClinic Grosshansdorf GmbH
Login to view more data
Corporation Tree
Boost your research with our corporation tree data.
Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.
Start your data trial now!
Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.