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In Silico Trial for Tuberculosis Vaccine Development

Deliverables

Second dissemination report

Second dissemination report

Report on the modeling simulation framework able to simulate human immune system dynamics

The UNICT partner has developed through years a computational modeling infrastructure able to simulate the main features and dynamics of the immune system, named UISS (Universal Immune System Simulator). UISS is a multi-scale, multi-organ, three-dimensional agent based simulator of the immune system with an attached module able to simulate the dynamics of specific biological pathways at the molecular level. In this report we describe the extension and the enhancing of the UISS platform to take care of the human immune system at large scale, in order and include the organs that play important role in TB i.e., lungs and the lymph nodes around them.

Governance and meetings: the governance bodies are set. SC meetings organised: logistic, preparation of programme, invitation of experts

Governance and meetings: the governance bodies are set. Kick off meeting organised: logistic, preparation of programme, invitation of experts.

Report on the data collection and selection on TB disease and candidate vaccines/treatments

The purpose of this deliverable is to collect all publicly available data on the host-pathogen interaction for TB infection and disease as well as data from preclinical and clinical studies conducted with TB vaccine candidates in the pipeline.

First dissemination report

First dissemination report

Report on the creation of the subjects-specific and virtual patients libraries that will be used in the implementation of the in silico clinical trial

The purpose of this deliverable is to create a set of subjects-specific models with the aim to reproduce biological diversity of the subjects. Hence, the library of subjects created will be personalized with a “vector of features” that identifies a specific real patient with the final goal to to obtain a library of virtual M. tuberculosis infected patients that will be vaccinated and treated accordingly.

A coherent hierarchical Bayesian model encompassing the virtual and real data sources.

This deliverable brings real and virtual patients models together to relate in a coherent manner the outcome from the in silico and in vivo experiments in the (WP2).

Dissemination plan

Dissemination plan

An efficient computational implementation of the model, yielding information and measures of variability on the evaluation of the vaccines

In this deliverable we will present an efficient computational implementation of the model, yielding information and measures of variability on the evaluation of the vaccines

Report on the extensions implemented into the modeling simulation platform to reproduce the immune system – TBC – vaccines interactions and dynamics

The goal of this deliverable is to integrate into UISS modeling framework the capability to simulate the dynamics and the specific features of the tuberculosis mycobacterium infection. Moreover the UISS modeling framework will be enabled to simulate the artificial immunity induced by two vaccines i.e., Ruti vaccine and ID93 vaccine.

Public web site

Creation of a public web site (strituvad-isct.eu) .

Establishment of a web based information portal

A web site will be created that will contain links to all the significant Tuberculosis research sites, but more importantly, enabling the presentation of progress reports of the project to be seen publicly. At the same time, in a private channel each partner enabled with proper login and password could exchange confidential information in form of documents or data including reports, charts, updated financial plans, contact information; information about activities conducted by each group, protocols, Standard Operating Procedures (SOPs) IP-related documents etc.

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Publications

An agent based modeling approach for the analysis of tuberculosis – immune system dynamics

Author(s): Francesco Pappalardo, Giulia Russo, Marzio Pennisi, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Santo Motta, Epifanio Fichera
Published in: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018, Page(s) 1386-1392
DOI: 10.1109/bibm.2018.8621355