ArticleBMC bioinformatics2020
Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- The eight pillars of within-host tuberculosis modelling.Frontiers in immunology · 2026Review
- Drug resistance mechanisms inFrontiers in pharmacology · 2026Review
- An overview of immunotoxicity in drug discovery and development.Toxicology letters · 2025Review
- Immune digital twins for complex human pathologies: applications, limitations, and challenges.NPJ systems biology and applications · 2024Review
- In Silico Studies to Support Vaccine Development.Pharmaceutics · 2023Review
- Computational modelling and simulation for immunotoxicity prediction induced by skin sensitisers.Computational and structural biotechnology journal · 2022Article
- Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system.Computational and structural biotechnology journal · 2022Article
- Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility.CPT: pharmacometrics & systems pharmacology · 2021Article
- Bayesian Augmented Clinical Trials in TB Therapeutic Vaccination.Frontiers in medical technology · 2021Article
- TowardsFrontiers in bioengineering and biotechnology · 2021Review
- Toward computational modelling on immune system function.BMC bioinformatics · 2020Article
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Authors and funding
11 authors at 8 institutions in 4 countries.
Funding
Abstract
backgroundIn 2018, about 10 million people were found infected by tuberculosis, with approximately 1.2 million deaths worldwide. Despite these numbers have been relatively stable in recent years, tuberculosis is still considered one of the top 10 deadliest diseases worldwide. Over the years, Mycobacterium tuberculosis has developed a form of resistance to first-line tuberculosis treatments, specifically to isoniazid, leading to multi-drug-resistant tuberculosis. In this context, the EU and Indian DBT funded project STriTuVaD-In Silico Trial for Tuberculosis Vaccine Development-is supporting the identification of new interventional strategies against tuberculosis thanks to the use of Universal Immune System Simulator (UISS), a computational framework capable of predicting the immunity induced by specific drugs such as therapeutic vaccines and antibiotics.
resultsHere, we present how UISS accurately simulates tuberculosis dynamics and its interaction within the immune system, and how it predicts the efficacy of the combined action of isoniazid and RUTI vaccine in a specific digital population cohort. Specifically, we simulated two groups of 100 digital patients. The first group was treated with isoniazid only, while the second one was treated with the combination of RUTI vaccine and isoniazid, according to the dosage strategy described in the clinical trial design. UISS-TB shows to be in good agreement with clinical trial results suggesting that RUTI vaccine may favor a partial recover of infected lung tissue.
conclusionsIn silico trials innovations represent a powerful pipeline for the prediction of the effects of specific therapeutic strategies and related clinical outcomes. Here, we present a further step in UISS framework implementation. Specifically, we found that the simulated mechanism of action of RUTI and INH are in good alignment with the results coming from past clinical phase IIa trials.
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