Clinical Trial Details
— Status: Not yet recruiting
Administrative data
NCT number |
NCT06235684 |
Other study ID # |
LUX-CLIN-002 |
Secondary ID |
|
Status |
Not yet recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 1, 2024 |
Est. completion date |
May 1, 2032 |
Study information
Verified date |
January 2024 |
Source |
Luxembourg Institute of Health |
Contact |
Jasmin Schulz, PhD |
Phone |
+35226970265 |
Email |
Jasmin.Schulz[@]lih.lu |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
This study is part of the Clinnova program. This is a prospective cohort study including
patients with RD recruited at the time of a treatment change. At least 800 participants
(recruited in France, Germany and Luxembourg) will be enrolled, of which 100 participants are
expected to be recruited in Luxembourg with the present study protocol. The mission of
Clinnova is to support the digitalization of healthcare and precision medicine by creating a
data-enabling environment for accessing, sharing and analyzing interoperable, high-quality
health data. The main hypothesis is that treatment change decided by clinicians is
predictable using objective surrogate markers derived from clinical, epidemiological, and
omics data. Identifying these objective markers may facilitate future treatment decisions,
provide new insights on the molecular causes for differential treatment response,
pathogenesis and progression, and potential pointers for improved personalized therapeutic
interventions.
Description:
Major unmet clinical needs in RD are participant stratification by the predicted response to
different drugs and the stratification of participants by predicted disease course, which
might result in more or less aggressive treatment approaches. In this context, key unmet
needs that can be addressed by data science and artificial intelligence include:
- Identification of predictive biomarkers for drug response estimation and identification
of prognostic biomarkers to estimate the future course of the disease, focusing on
participants in whom treatment needs to be changed.
- Improved monitoring of participant well-being. During the first year, data related to
demographics, lifestyle, laboratory and physical examinations will be collected at
baseline, at month 3, at month 12 and in case of unscheduled visit. Questionnaires and
standardised voice collection will be collected (optionally) at different time points
using the Colive web app. Physical activity and sleep quality will be optionally
monitored via a smartwatch that will be provided to interested participants. Biological
sample(s) and imaging data will be collected at different time points (baseline; 3
months; 12 months; unscheduled visit). A long-term follow-up (starting from month 12 and
up to 4 years after month 12) is foreseen in this study. During the long-term follow-up
medical data are collected on a yearly basis, and questionnaires are collected every 6
months.