STriTuVaD simulation platform now able to reproduce the immune system response induced by vaccines

Another important milestone has been reached by the STriTuVaD project in these days.

The team of the University of Catania (Italy) successfully extended their modeling framework in order to include dynamics and specific features of the Mycobacterium Tuberculosis infection and to simulate the artificial immunity induced by candidate vaccines.

UISS, acronym for Universal Immune System Simulator, is a multi-scale, multi-organ agent based simulator of the immune system, with an attached module able to simulate the dynamics of specific biological pathways at the molecular level. The simulator has been developed through several years by the research group composed by Prof Francesco Pappalardo, Dr Giulia Russo and Dr Marzio Pennisi, and in the STriTuVaD project it has the fundamental role of performing large scale agent based modelling simulations of the immune response induced by candidate vaccine against tuberculosis.

The two vaccines being tested in STriTuVaD project are Ruti by Archivel Farma and ID93 by IDRI, and their features have been implemented into the platform to simulate the mechanisms that induce an immune response. Moreover, since real patients involved in the clinical trials will be treated with a conventional antibiotic strategy, it was crucial for the modelling platform to take into account the interaction between Mycobacterium tuberculosis and antibiotics, so that in silico clinical trials could be correctly validated.

In this way, the computational modeling platform will be able to simulate and predict the outcomes of treatments in virtual patients.

In particular, three possible scenarios are being simulated and evaluated in order to validate the extended framework: MTB latent chronic infection with some typical granuloma formation; a reactivation phase during latent chronic infection, and a latent chronic disease infection scenario during RUTI or ID93 vaccine administration.

Next step will consist on the creation of virtual patients libraries that will be used to implement the in silico clinical trials.

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