Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)
Pennisi, Marzio (University of Catania. Department of Mathematics and Computer Science)
Russo, Giulia (Department of Drug Sciences. University of Catania)
Sgroi, Giuseppe (Department of Mathematics and Computer Science. University of Catania)
Bonaccorso, Angela (Department of Drug Sciences. University of Catania)
Parasiliti Palumbo, Giuseppe Alessandro (Department of Mathematics and Computer Science. University of Catania)
Fichera, Epifanio (Etna Biotech S.r.l.)
Kumar Mitra, Dipendra (All India Institute of Medical Sciences (Nova Delhi, Índia))
Walker, Kenneth B. (TuBerculosis Vaccine Initiative (TBVI))
Cardona, Pere-Joan (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Amat, Mercè (Archivel Farma S.L)
Viceconti, Marco (Department of Industrial Engineering. Alma Mater Studiorum. University of Bologna)
Pappalardo, Francesco (Department of Drug Sciences. University of Catania)

Data:	2019
Resum:	Background: Tuberculosis (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. Results: We 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. Conclusions: The 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.
Ajuts:	European Commission 777123
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Computational modeling framework ; In silico clinical trials ; Tuberculosis ; Vaccine ; Immunity ; Therapeutic strategies
Publicat a:	BMC bioinformatics, Vol. 20 (December 2019) , p. 504, ISSN 1471-2105

DOI: 10.1186/s12859-019-3045-5
PMID: 31822272

10 p, 1.3 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
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