Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)

Abstract

BackgroundTuberculosis (TB) represents a worldwide cause of mortality (it infects one third of the world’s population) affecting mostly developing countries, including India, and recently also developed ones due to the increased mobility of the world population and the evolution of different new bacterial strains capable to provoke multi-drug resistance phenomena. Currently, antitubercular drugs are unable to eradicate subpopulations of Mycobacterium tuberculosis (MTB) bacilli and therapeutic vaccinations have been postulated to overcome some of the critical issues related to the increase of drug-resistant forms and the difficult clinical and public health management of tuberculosis patients. The Horizon 2020 EC funded project “In Silico Trial for Tuberculosis Vaccine Development” (STriTuVaD) to support the identification of new therapeutic interventions against tuberculosis through novel in silico modelling of human immune responses to disease and vaccines, thereby drastically reduce the cost of clinical trials in this critical sector of public healthcare.ResultsWe present the application of the Universal Immune System Simulator (UISS) computational modeling infrastructure as a disease model for TB. The model is capable to simulate the main features and dynamics of the immune system activities i.e., the artificial immunity induced by RUTI® vaccine, a polyantigenic liposomal therapeutic vaccine made of fragments of Mycobacterium tuberculosis cells (FCMtb). Based on the available data coming from phase II Clinical Trial in subjects with latent tuberculosis infection treated with RUTI® and isoniazid, we generated simulation scenarios through validated data in order to tune UISS accordingly to STriTuVaD objectives. The first case simulates the establishment of MTB latent chronic infection with some typical granuloma formation; the second scenario deals with a reactivation phase during latent chronic infection; the third represents the latent chronic disease infection scenario during RUTI® vaccine administration.ConclusionsThe application of this computational modeling strategy helpfully contributes to simulate those mechanisms involved in the early stages and in the progression of tuberculosis infection and to predict how specific therapeutical strategies will act in this scenario. In view of these results, UISS owns the capacity to open the door for a prompt integration of in silico methods within the pipeline of clinical trials, supporting and guiding the testing of treatments in patients affected by tuberculosis.

In Silico Trial to test COVID-19 candidate vaccines: a case study with UISS platform

“…More recently, UISS has been used as the centerpiece of the StriTuVaD H2020 project with the aim to create an in silico trial for tuberculosis. In this context, observations from virtual patients will be coupled with results from a real clinical trial to obtain an in silico augmented clinical trial, with greater accuracy and more statistical power [30].…”

Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB

“…2 and 3 , the mean behavior (green line) and standard deviation (orange shaded region) of the biological entities taken into consideration are depicted. Untreated TB digital patients have been widely discussed in [ 13 , 24 ]. Figure 2 shows the cellular dynamics where an initial challenge with a virulent strain of MTB is supposed to happen on day 15.…”

“…UISS computational framework, widely discussed in [ 13 ], was successfully applied to a large number of disease modelling scenarios [ 15 – 17 ], including COVID-19 [ 18 ]. UISS is based on Agent-Based Model (ABM) methodology [ 19 , 20 ] that predicts the efficacy of vaccines and/or antibiotics treatments targeting MTB in a specific digital patients cohort.…”

“…Among these, the HORIZON 2020 In Silico Trial for Tuberculosis Vaccine Development (STriTuVaD) project aims to evaluate a specific therapeutic vaccine against tuberculosis through an innovative computational modelling infrastructure named Universal Immune System Simulator (UISS). In this context, UISS for Tuberculosis (UISS-TB) is capable to reproduce the dynamics of the immune system affected by TB and predict the outcome of a real clinical trial under the administration of specific interventions such as the RUTI vaccine [ 13 ].…”

Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator

“…To analyze the behavior of possible therapeutic interventions, we implemented mechanisms of action (MoA) of ID93+GLA-SE vaccine in our pre-existing version of UISS-TB computational platform, in which RUTI vaccine was previously implemented [10], along with the entire dynamics of MTB and interactions with the immune system machinery. We analysed the associated immune response induced by both vaccines and we applied UISS-TB computational model to set up a library of digital TB patients, through the identification of a "vector of features" that combines biological and pathophysiological parameters of tuberculosis patients.…”