Paper Info
Title
Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB
Abstract
In 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. Here, 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. In 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.
Year
DOI
Venue
2020
10.1186/s12859-020-03762-5
BMC Bioinformatics
Keywords
DocType
Volume
Tuberculosis, Computational modeling, In silico trials, RUTI, Isoniazid, Immunity, Therapeutic strategies
Journal
21
Issue
ISSN
Citations 
17
1471-2105
1
PageRank 
References 
Authors
0.39
7
11
Name
Order
Citations
PageRank
Giulia Russo11510.89
Giuseppe Sgroi213.09
Giuseppe Alessandro Parasiliti Palumbo333.91
Marzio Pennisi410923.03
Miguel Juarez531.16
Pere-Joan Cardona610.39
Santo Motta720229.74
Kenneth B. Walker810.39
Epifanio Fichera961.69
Marco Viceconti10227.23
F. Pappalardo117620.14