Description du projet
Un algorithme de médecine stratifiée pour prédire la réponse au traitement de la tuberculose
La tuberculose est une maladie infectieuse qui affecte les poumons; si elle n’est pas traitée, elle s’avère mortelle pour environ la moitié des personnes touchées. Actuellement, un quart de la population mondiale est infectée par la tuberculose, la région européenne présentant la prévalence la plus élevée de tuberculose résistante aux médicaments. Le traitement dirigé vers l’hôte à effet anti-inflammatoire a été proposé en plus du traitement actuel, afin d’obtenir une solution plus rapide ayant un impact moins permanent sur les poumons. Le projet SMA-TB, financé par l’UE, mettra au point une approche de médecine personnalisée, comportant une stratification des patients et une intégration des facteurs de l’hôte et de l’agent pathogène. Parmi les objectifs principaux de SMA-TB se trouvent l’évaluation de l’action anti-inflammatoire de l’aspirine et du traitement dans les cas résistants aux médicaments, l’identification et la validation clinique des biomarqueurs de l’agent pathogène et de l’hôte, et la génération d’un algorithme pour stratifier les patients afin de prédire l’évolution de la maladie et sa réponse à l’intervention.
Objectif
Tuberculosis (TB) is a chronic, life-threatening infectious disease which poses a tremendous challenge for physicians, researchers and Health Systems, which treatment is long, based only on the drug susceptibility of the responsible infective strain and very costly in drug-resistant cases (MDR-TB). The European Region still has the highest prevalence of MDR-TB in the world. Host-Directed Therapies (HDT) have been recently proposed to shorten treatment length and by to improve the patients’ outcomes while not increasing the risk of generating drug resistance.
As hyperinflammation is responsible of the lung damage associated to patients’ worse outcomes and sequelae, one of the approaches is to add an HDT with anti-inflammatory effect to the current drug regimen to cure the patients faster while having less permanent lung damage. Because TB has a wide range of clinical forms and severity stages, any therapeutic regimen needs to be studied in clinical trials (CT) as its benefit might differ among patients. No individualized personalized medicine is possible without stratifying the patients by integrating pathogen and host factors that will predict the course of the disease and the response to the intervention.
SMA-TB objectives are:
• To evaluate in a CT the potential impact of acetylsalicylic acid (ASA) and Ibuprofen (Ibu) (anti-inflammatoriesy HDT) as adjuncts to standard therapy for drug sensitive (DS-) and MDR-TB. This potentially will reduce tissue damage, decrease the length of the treatment and the risk of bad outcomes.
• To identify and clinically validate host and pathogen biomarkers for further selection according to their relevance in terms of their ability to predict TB course and outcomes and response to treatment thanks to data science protocol.
• To generate a medical algorithm to stratify patients using network-based mathematical modelling for predicting the course of the disease and its response to the intervention, to be applied during clinical management to improve and personalize TB.
Champ scientifique
- natural sciencescomputer and information sciencesdata science
- medical and health scienceshealth sciencesinfectious diseases
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistance
- medical and health sciencesclinical medicinepneumologytuberculosis
- medical and health scienceshealth sciencespersonalized medicine
Mots‑clés
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
08916 Badalona Barcelona
Espagne