Descripción del proyecto
Algoritmos de medicina estratificada para predecir la respuesta al tratamiento de la tuberculosis
La tuberculosis es una enfermedad infecciosa que afecta a los pulmones y, si no se trata, es mortal para aproximadamente la mitad de las personas que la padecen. Hoy día, una cuarta parte de la población mundial padece tuberculosis y la región europea es la que presenta la mayor prevalencia de tuberculosis farmacorresistente. Junto con el régimen farmacológico actual, se ha desarrollado una terapia dirigida al hospedador con efecto antiinflamatorio para lograr una cura más rápida con un menor daño pulmonar permanente. El proyecto financiado con fondos europeos SMA-TB desarrollará un método de medicina personalizada que incluirá la estratificación de pacientes y la integración de los factores del patógeno y del hospedador. Los principales objetivos de SMA-TB incluyen la evaluación de la acción antiinflamatoria de la aspirina, además del tratamiento en casos farmacorresistentes, la identificación y validación clínica de los biomarcadores del hospedador y del patógeno, y la generación de un algoritmo para estratificar a los pacientes a fin de predecir el curso de la enfermedad y su respuesta a la intervención.
Objetivo
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.
Ámbito científico
- 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
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SC1-2019-Two-Stage-RTD
Régimen de financiación
RIA - Research and Innovation actionCoordinador
08916 Badalona Barcelona
España