A novel Stratified Medicine Algorithm to predict treatment responses to host-directed therapy in TB patients.

Informazioni relative al progetto

SMA-TB

ID dell’accordo di sovvenzione: 847762

DOI

10.3030/847762

Progetto chiuso

Data della firma CE 6 Dicembre 2019

Data di avvio 1 Gennaio 2020

Data di completamento 31 Dicembre 2024

Finanziato da

SOCIETAL CHALLENGES - Health, demographic change and well-being

Costo totale

€ 6 388 104,00

Contributo UE

€ 6 388 104,00

6 388 104,00

Coordinato da

INSTITUT DE INVESTIGACIO EN CIENCIES DE LA SALUT GERMANS TRIAS I PUJOL
Spain

Periodic Reporting for period 4 - SMA-TB (A novel Stratified Medicine Algorithm to predict treatment responses to host-directed therapy in TB patients.)

Periodo di rendicontazione: 2024-07-01 al 2024-12-31

Tuberculosis (TB), is a disease caused by bacteria that attack the lungs and it can persist throughout a person’s life or even kill them. The treatment is very long and its success depends on the particular strain of bacteria in that patient being treatable by the available drugs. Resistant strains (MDR-TB), not killed by the common drugs, are much more difficult to treat, which makes the treatment much longer and costly, more unpleasant for patients and a burden for health systems. Moreover, up to 50 % of TB patients can suffer of permanent lung damage which can impair their quality of life. Host-directed treatments (HDTs) are a new type of treatment that boost the patient’s defences and ability to fight off the disease rather than just killing the bacteria. Using HDT treatments together with the antibiotics might mean a shorter time taking medicine and better results for patients.Our hypothesis is that to include an HDT that reduces inflammation in the medicines the patients are already taking can help to reduce permanent lung damage and even the lenght of treatment.

Taking into account all these, the SMA-TB Project aims to do three things:

1-To run a high-quality clinical trial (RCT) in which patients being treated for TB are also given common anti-inflammatories, aspirin or ibuprofen, which reduce inflammation. It is hoped that this will show that the use of anti-inflammatory means a better health-related quality of life for TB patients and better management of their disease.

2-To identify biomarkers to reliably predict how each patient’s disease will progress, who can be treated successfully by the standard treatment and who can benefit of completing the drug treatment with HDT. To do this the researchers will collect information from a large group of patients and analyse it using computers and mathematical models that are able to pick out patterns from huge amounts of information.

3-To make a mathematical tool (algorithm) that doctors can use to identify which patients will have worse outcomes or can benefit of adding an HDT, and to adjust their treatment accordingly (personalized treatment).

SMA-TB Achievements

Despite the challenges encountered, particularly those related to the COVID-19 pandemic, the SMA-TB Clinical Trial (CT) had to prematurely stop, even if we successfully completed the 62% of the estimated sample size across all three sites (two in South Africa and one in Georgia). A significant achievement of the consortium has been the successful collection, management, shipment, and distribution of a substantial number of samples (n = 18,263 from 221 patients). Although the RCT did not meet its primary endpoints, its implementation, protocol, and results are highly valuable. They contribute significantly to the fight against tuberculosis, support the potential of HDT, and offer important insights for the broader field of infectious diseases.

We have studied most pathogen and host factors (through WP2) and linked them to the outcomes thanks to the mathematical modelling (WP3), identifying and validating relevant biomarkers in predicting health outcomes and treatment response. Finally, we have developed an stratification algorithm with the potential for rapid uptake into clinical practice

All consortium partners have actively engaged in communication and dissemination activities, producing many outputs available through open access or publicly accessible from the EU Open Free Repository Zenodo, creating the SMA-TB Zenodo community https://zenodo.org/communities/sma-tb/records?q=&l=list&p=1&s=10

Some examples are:
-Produced video stories highlighting the project's impact.
-Issued and distributed three newsletters across various platforms.
-Engaged with local communities and stakeholders to explain the SMA-TB project and organize joint public activities.
-Established connections with other EC-funded projects to conduct joint activities, including DRTB-HDT (GA Nº 847465), MISTRAL (GA Nº 847943), STATIN-TB (GA Nº RIA2017T-2004), Innova4TB (GA Nº 823854), and ADVANCE-TB (CA21164).
-Published 15 open-access articles.
-SMA-TB Capacity-Building Toolkit, including SMA-TB outputs generated up to now that might be exploited by others: e-consent video, toolkit related to the CT, laboratory technical capacity of staff, templates to be used for Project Management and Clinical Trial Monitoring

The project’s scientific, technical management, and administrative coordination remained strong all along the project. The Project Management Team provided targeted support and advice to partners with limited experience in H2020 projects. The consortium conducted five annual meetings (including one online due to the pandemic), three General Assemblies, and numerous management and scientific meetings. The consortium and the European Commission have collaborated on various measures to mitigate the impact of the COVID-19 pandemic on the progress of the SMA-TB project.

All SMA-TB deliverables were submitted successfully.

The impacts of SMA-TB are:

-The SMA-TB initiative has bolstered internal market integration and productivity by creating jobs, fostering further collaborations, and expanding services. SMA-TB partners have enhanced their international competitiveness through expertise in RCTs and multi-country, multi-partner projects, as well as by establishing a large biobank and database. This advancement is expected to attract new public and private investments, opening up additional funding opportunities and driving R&D investment.

-The SMA-TB RCT was the first to systematically investigate the use of NSAIDs for TB. Our findings highlight the importance of this approach, demonstrating that ASA and IBU are safe and may have a positive impact on pulmonary TB. Additionally, our results underscore the need for further research into alternative doses, dosing regimens, and other investigational anti-inflammatory drugs as potential HDT options, reinforcing their relevance to the field. Thanks to the SMA-TB, a new ICT test has been developed by LIONEX with enhanced performance, increasing competitiveness of this SME.

-We have generated and integrated data on the most pathogen and host factors (through WP2) and linked them to the outcomes thanks to the mathematical modelling (WP3). We have identified and validated biomarkers relevant in predicting health outcomes and treatment response. We also have defined the outcomes to be used in the algorithm and that can be used in other clinical trials and studies. Finally, we have developed an stratification algorithm with the potential for rapid uptake into clinical practice.

-We have developed very valuable data on MDR-TB. Moreover, our RCT results show that patients suffering of MDR-TB are the ones that might benefit more of the addition of the NSAIDS to the standard treatment.

-We have strengthened resilient health systems in South Africa and Georgia and generated valuable insights into the socioeconomic status of TB patients, promoting greater equity. Our commitment to open access - through publications and a capacity-building kit – ensures that our methods.

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Periodic Reporting for period 4 - SMA-TB (A novel Stratified Medicine Algorithm to predict treatment responses to host-directed therapy in TB patients.)

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