Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB
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RESEARCH
Moving forward through the in silico modeling of tuberculosis: a further step with UISS‑TB Giulia Russo1†, Giuseppe Sgroi2†, Giuseppe Alessandro Parasiliti Palumbo2, Marzio Pennisi3, Miguel A. Juarez4, Pere‑Joan Cardona5,6,7, Santo Motta8, Kenneth B. Walker9, Epifanio Fichera10, Marco Viceconti11 and Francesco Pappalardo1*
From 3rd International Workshop on Computational Methods for the Immune System Function (CM‑ ISF 2019) San Diego, CA, USA. 18-21 November 2019 *Correspondence: francesco.pappalardo@unict. it † Giulia Russo and Giuseppe Sgroi wish it to be known that, in their opinion, the first two authors should be regarded as joint first authors 1 Department of Drug Sciences, University of Catania, 95125 Catania, Italy Full list of author information is available at the end of the article
Abstract Background: 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 deadli‑ est 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. Results: 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 suggest‑ ing that RUTI vaccine may favor a partial recover of infected lung tissue. Conclusions: In silico trials innovations represent a powerful pipeline for the predic‑ tion 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.
© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and
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