AutoBuSTeD



Automated Bubble Sweat Test Diagnostics

Insights into the project documentation

Aims of this collaborative project

This project aims to automate and standardize the analysis required for a diagnostic test for cystic fibrosis.

Our partner Teresinha Leal from the UCLouvain in Brussels has established and improved a non-invasive version of the imaging based sweattest with a linear charateristic identifying heterozygous as half responders useful to study genotype-phenotype correlation of rare CFTR mutations.

Another advantage of the new image-based test is that it has proven to be able to detect improved levels of CFTR function in patients treated with CFTR modulators. However, a severe practical limitation of the test is the manual image analysis (80 images/test), which is labour-intensive and can take 6 hours per test.

The Automated Bubble Sweat Test Diagnostics – AutoBuSTeD aims at overcoming the practical limitation of the new sweat test due to the labour cost of its data analysis.

Funding

Our project is funded by the Christiane-Herzog-Stiftung via the "Forschungsförderpreis für wissenschaftliche Nachwuchsförderung 2018" for our project proposal "Verbesserung der individuellen Bestimmung der CFTR-Restfunktion durch automatisierte Bildanalyse von beta-adrenerg-abhängiger Schweisssekretion"

Project partners

The software is being developed transnationally and tested by our project partner with a cohort from Brussels (ClinicalTrials.gov Identifier NCT03584841).

Department of Medical Bioinformatics (UMG)
Dr. Manuel Nietert

Institut de Recherche Expérimentale et Clinique (IREC)
Louvain centre for Toxicology and Applied Pharmacology (LTAP)
Université catholique de Louvain (UCLouvain), Brussels, Belgium

Prof. Dr. Teresinha Leal

Press releases

Press release from the Mukoviszidose Institut – gemeinnützige Gesellschaft für Forschung und Therapieentwicklung mbH:

https://idw-online.de/de/news707760

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