TESTWEB - METHODS FOR PREDICTION OF PROGRESSION IN MULTIPLE SCLEROSIS

TestWeb - Methods for Prediction of Progression in Multiple Sclerosis is a technology aimed at improving the prediction of clinical disease progression in patients with multiple sclerosis (MS). The technology integrates clinical information and, potentially, biomarkers and imaging data to identify patterns associated with an increased likelihood of disease progression. The approach combines variables collected during routine patient follow-up, including demographic and clinical characteristics, disability evolution, medical history and treatments, with parameters derived from diagnostic assessments, particularly neuroimaging techniques. Statistical methods and/or machine learning algorithms can then be used to generate predictive models capable of estimating an individual patient's risk of progression and anticipating their future clinical trajectory. A key advantage of this approach is its ability to move beyond the assessment of isolated clinical indicators towards a multidimensional and personalised evaluation of disease risk. This may enable the earlier identification of patients with a higher probability of developing disability, even when their current clinical status does not clearly indicate their future disease course. The technology could support both clinical research and healthcare applications, including patient stratification, clinical trial design and participant selection, and treatment decision-making. Predictive models could also help identify patient subgroups with distinct disease trajectories and support the development of more tailored monitoring strategies. Overall, the technology aims to advance predictive and personalised medicine in multiple sclerosis by enabling a more accurate assessment of disease progression and supporting improved patient monitoring and management. TESTWEB - METHODS FOR PREDICTION OF PROGRESSION IN MULTIPLE SCLEROSIS

Autors: CRISTINA GONZALEZ MINGOT, LUIS BRIEVA RUIZ, PASCUAL TORRES CABESTANY, Hugo Gonzalo Benito, ANNA GIL SANCHEZ
Protecció: PCTEPXXXXXX1
Titulars: IRBLLEIDA INSTITUT RECERCA BIOMEDICA DE LLEIDA, INSTITUTO DE ESTUDIOS DE CIENCIAS DE LA SALUD DE CASTILLA Y LEÓN, UNIVERSITAT DE LLEIDA