%0 Conference Paper %F Oral %T Prediction of biomarkers' trajectory in Huntington's disease: application to precise clinical trial design %+ Algorithms, models and methods for images and signals of the human brain (ARAMIS) %+ Institut du Cerveau = Paris Brain Institute (ICM) %+ UCL, Institute of Neurology [London] %A Koval, Igor %A Dighiero, Thomas %A Scahill, Rachael, I %A Durr, Alexandra %A Durrleman​, Stanley %< avec comité de lecture %B CompAge 2020 - Computational approaches for ageing and age-related diseases %C Paris, France %8 2020-09-01 %D 2020 %K Huntington's disease %K Longitudinal progression %K Design of Clinical trials %Z Mathematics [math]/Statistics [math.ST]Conference papers %X Patient inclusion is a crucial step in the setting of clinical trials, especially in rare diseases like Huntington's disease. The current selection process relies mostly on baseline measurements and cofactor values. This coarse estimate of the patient’s profile leads to heterogeneous cohortsin clinical trials, which leads to uncertain therapeutic approaches. To this end, we developed a method that can position any patient on a common reference timeline of HD progression. From it, patients can be selected based on their future temporal profile. %G English %2 https://inria.hal.science/hal-03137994/document %2 https://inria.hal.science/hal-03137994/file/abstract.pdf %L hal-03137994 %U https://inria.hal.science/hal-03137994 %~ INSERM %~ CNRS %~ INRIA %~ INRIA-ROCQ %~ APHP %~ INSMI %~ TESTALAIN1 %~ ICM %~ INRIA2 %~ ARAMISLAB %~ SORBONNE-UNIVERSITE %~ SORBONNE-UNIV %~ SU-MEDECINE %~ SU-MED %~ SU-TI %~ ALLIANCE-SU %~ INRIA-ROYAUMEUNI