Recently, the project named STriTuVaD (i.e., In Silico Trial for Tuberculosis Vaccine Development) was funded by the European Commission towards the Call Horizon 2020 - H2020-SC1-2016-2017 (Personalised Medicine), topic: SC1-PM-16-2017, type of action: RIA - (Research and Innovation action). The project started last February 2018 and Prof. Francesco Pappalardo is the Scientific Coordinator of the project. Tuberculosis is one of the world’s deadliest diseases: one third of the world’s population, mostly in developing countries, is infected with TB. TB is becoming again very dangerous also for developed countries, due to the increased mobility of the world population, and the appearance of several new bacterial strains that are multi-drug resistant (MDR). COMBINE Group Unit will develop an in silico trial platform that simulate the relevant individual human physiology and physiopathology in patients affected by Mycobacterium tuberculosis; furthermore, the platform will makes use of a level 3 simulation modelling framework able to represent each individual of the reference population. STriTuVaD will use this approach to predict the outcome of the efficacy of two different therapeutic vaccination strategies administered to M. tuberculosis patients. Another possible benefit of the StriTuVaD platform will be the reduction of human testing, by providing a reliable prediction of the phase III outcomes on the basis of the data collected in the phase II clinical trial. StriTuVaD will increase the confidence in investing in a phase III trial to demonstrate the efficacy in term of reduced recurrence and to drastically reduce the numerosity of the enrolled patients to obtain enough statistical power. STriTuVaD project is going to lay one of the fundamental stones in the context envisaged by Faris: “In the future, computer-based modeling may change the way we think about device validation in other ways, allowing for much smaller clinical trials, or may change the way we think about running trials, in that some “clinical” information may be derived from simulations.” Recently, also regulatory agencies i.e., EMA and FDA, see the value of computational modeling in supporting regulatory decision and considering as top science priority the development of a standard for the in silico approaches in clinical trials. This is based on a reverse engineering methodology combining mathematical models of diseases, drugs and virtual patients in offering a transformative approach to drug R&D.