Innovating Works

SMA-TB

Financiado
A novel Stratified Medicine Algorithm to predict treatment responses to host dir...
A novel Stratified Medicine Algorithm to predict treatment responses to host directed therapy in TB patients. 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 responsib... 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. ver más
31/12/2024
6M€
Duración del proyecto: 60 meses Fecha Inicio: 2019-12-06
Fecha Fin: 2024-12-31

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2019-12-06
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
Presupuesto El presupuesto total del proyecto asciende a 6M€
Líder del proyecto
FUNDACIO INSTITUT D'INVESTIGACIO EN CIENCIES... No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5 12M