The F101G benefited from the help of three computer scientists to develop three new Apps designed to facilitate research into rare diseases(GEMS pilot project) and to make the results of a bioinformatics tool using artificial intelligence accessible to the general public(GEMVAP). This fruitful collaboration was organized by mic.brussels (Microsoft/Brussels Capital Region), which each year selects the best profiles from Brussels’ IT schools to take part in its innovation program. Thibault You-Hout, Dylan Bricar and Geoffrey Dielman explain their work with the F101G.

Thibault You-Hout: Consent App

“I worked on the development of a web-based informed consent application designed to facilitate participation in scientific research into rare diseases. The GEMS study on Marfan syndrome served as a pilot project. This ‘Consent App’ enables patients/participants to ensure that they have fully understood the objectives of the studies they are invited to join, and thus to formulate a genuine informed consent. This App also saves rare disease researchers precious time, which they can devote to research rather than administrative tasks”.

Dylan Bricar: “Pheno App

“In order to feed the F101G’s ‘Genomic Cloud‘, I took part in the design of a conditional questionnaire web App in which participants in a scientific study can fill in their phenotypic information (all the apparent characteristics of an individual). The participant’s answers dynamically redirect him/her to other questions until the end of the question tree. Another aspect of my work involved the creation of a portal via which users can view and modify their personal information and that from the conditional questionnaire at any time, manage their consents and also have access to scientific publications linked to the research in which they are taking part”.

Geoffrey Dielman: “GEMVAP Live

“In collaboration with the F101G, I developed an application for consulting the results of the artificial intelligence tool named GEMVAP created as part of Genome4Brussels. GEMVAP is an essential tool for bioinformatics and algorithmic research on the FBN1 gene (the gene on which the mutations that cause Marfan syndrome are located), and aims to compare different predictions of the deleterious effects of FBN1 gene variants. Once these predictions have been compared, App refines them by cross-checking results from different sources, and classifies them as “pathogenic, non-pathogenic or unknown” mutations. The aim of the ‘GEMVAP Live’ App is to build and maintain a database containing all GEMVAP predictions and their displays within a user-friendly and educational interface aimed at a non-scientific public with an awareness of Marfan syndrome”.