Descrizione del progetto
Algoritmo di medicina stratificata per prevedere la risposta al trattamento della tubercolosi
La tubercolosi (TBC) è una malattia infettiva che colpisce i polmoni: se non trattata, è fatale per circa la metà delle persone colpite. Attualmente, un quarto della popolazione mondiale è infetto da TBC, con la regione europea che mostra la più alta prevalenza di TBC resistente ai farmaci. Oltre all’attuale regime farmacologico è stata proposta una terapia «host-directed» con effetto antinfiammatorio, per una cura più rapida con un danno polmonare meno permanente. Il progetto SMA-TB, finanziato dall’UE, svilupperà un approccio di medicina personalizzata, caratterizzato da stratificazione dei pazienti e integrazione di fattori patogeni e ospiti. Gli obiettivi principali di SMA-TB includono la valutazione dell’azione antinfiammatoria dell’aspirina oltre alla terapia in casi di farmacoresistenza, l’identificazione e la convalida clinica di biomarcatori ospiti e patogeni e la generazione di un algoritmo per stratificare i pazienti al fine di prevedere il decorso della malattia e la sua risposta all’intervento.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SC1-2019-Two-Stage-RTD
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
08916 Badalona Barcelona
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