Tuberculosis (TB) one of the world’s deadliest diseases: one third of the world’s population, mostly in developing countries, is infected with TB. But 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). There is now a growing awareness that TB can be effectively fought only working globally, starting from countries like India, where the infection is endemic. Once a person present the active disease, the most critical issue is the current duration of the therapy, because of the high costs it involved, the increased chances of non-compliance (which increase the probability of developing an MDR strain), and the time the patient is still infectious to others. One exciting possibility to shorten the duration of the therapy are new host-reaction therapies (HRT) as a coadjuvant of the antibiotic therapy. The endpoints in the clinical trials for HRTs are time to sputum culture conversion, and incidence of recurrence. While for the first it is in some cases possible to have a statistically powered evidence for efficacy in a phase II clinical trial, recurrence almost always require a phase III clinical trial with thousands of patients involved, and huge costs.
In the STriTuVaD multidisciplinary consortium we will test, through phase IIb clinical trials, one of the most advanced therapeutic vaccines against DS-TB and MDR-TB i.e. RUTI vaccine, provided by Archivel Farma S.L (Spain).
In parallel we will extend the Universal Immune System Simulator to include all relevant determinants of such clinical trial, establish its predictive accuracy against the individual patients recruited in the trial, use it to generate virtual patients and predict their response to the HRT being tested, and combine them to the observations made on physical patients using a new in silico-augmented clinical trial approach that uses a Bayesian adaptive design. This approach, where found effective could drastically reduce the cost of innovation in this critical sector of public healthcare.
To achieve such important goal, we intend to reach the following objectives:
• Assessment of the computational modelling framework to simulate the human immune system complex dynamics at large scale;
• Development and integration into the general modelling framework of the module featuring the simulation of the TB – immune system interaction;
• Development and integration into the general modelling framework of the module featuring the simulation of the effects of antibiotics therapy in TB patients;
• Development and integration into the general modelling framework of the module featuring the simulation of the immunity induced by the TB vaccines;
• Set-up the library of virtual patients using data of real patients enrolled for the clinical trial and run an empowered in silico-augmented adaptive Bayesian clinical trial.
• In silico trial framework release by means of the validation of the real phase IIb clinical trial.
