Tuberculosis (TB) is one of the world’s deadliest diseases. One third of the world’s population, mostly in developing countries, is infected with TB, but the disease 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 presents 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 an adjuvant of the antibiotic therapy. The endpoints in the clinical trials for HRTs are time to inactivation, 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 project we will extend our Universal Immune System Simulator to:
include all relevant determinants of the 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;
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.
ETNA BIOTECH SRL - Italy
UNIVERSITA' DEGLI STUDI DI CATANIA - Italy
ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - Italy
THE UNIVERSITY OF SHEFFIELD - United Kingdom
ARCHIVEL FARMA, SL - Spain
STICHTING TUBERCULOSIS VACCINE INITIATIVE - Netherlands
INFECTIOUS DISEASE RESEARCH INSTITUTE - United States
THE ALL-INDIA INSTITUTE OF MEDICAL SCIENCES - India
Grant agreement ID: 777123
Total cost: EUR 5.050.656,25
EU contribution: EUR 4.549.527,50
Department of BioTechnology, Government of India contribution: EUR 501.128,75
Coordinated in: Italy
Topic: SC1-PM-16-2017 - In-silico trials for developing and assessing biomedical products
Call for proposal: H2020-SC1-2017-CNECT-2
Funding scheme: RIA - Research and Innovation action
Public deliverables and reports
D1.1 Governance and meetings: the governance bodies are set. SC meetings organised: logistic, preparation of programme, invitation of experts
D1.2 Establishment of a web-based information portal
D2.4 Report on the creation of the subjects- specific and virtual patient libraries that will be used in the implementation of the in silico clinical trial
D3.1 A coherent hierarchical Bayesian model encompassing the virtual and real data sources.
D3.2 An efficient computational implementation of the model, yielding information and measures of variability on the evaluation of the vaccines
D4.3 First patient recruitment
D4.4 Last patient recruitment
D5.1 Report on the set of generated in silico models
D5.2 Report on the tuning and refinement of the in silico models at time 12 and the creation of virtual patients for predictions
D5.3 Final report on the validated computational modelling framework and final release of the in silico clinical trial model
D6.1 Dissemination plan
D6.2 Public web site
D6.3 First dissemination report
D6.4 Second dissemination report
D6.5 Third dissemination report