Project title: 3TR (Identification of the Molecular Mechanisms of non-response to Treatments, Relapses and Remission in Autoimmune, Inflammatory, and Allergic Conditions)
Starting date: September, 1st 2019.
Ending date: August, 31st 2026.
3TR is a transdisciplinary consortium made of experts in all areas of medicine, basic sciences and bioinformatics from academic institutions, SMEs, and 8 major pharmaceutical companies, teamed to study a fundamental issue in medicine: the mechanisms of response and non-response to therapies, the major aim of 3TR, both within single disease entities and across diseases, where molecular stratification may identify shared disease taxonomies. The molecular identification of groups of patients to whom a drug will benefit, will allow focusing on those who are drug orphan. Harmonization of data from existing academy or industry-sponsored studies will identify biomarkers to inform a new collection. Specimens of diseased tissues, blood, stools, and other fluids will be obtained in a de novo observational prospective trial with standard of care medication prior, during and after first or second line of treatment. Because the studies will be at different phases of progression, a carrousel model of work was designed for input and output of data to be continuously analysed, and interpreted, to inform those measurements to be undertaken and allow cross-validation of results. The 3TR team will elucidate the role of the microbiome, genetics and regulatory genomic features in disease progression. The working aims of 3TR are: 1) establish a centralized data management platform; 2) perform comprehensive molecular and clinical characterisation of a prospective patient cohort; 3) establish integrated analysis of all data using advanced bioinformatics/statistical and modelling methods; 4) identify sets of predictive biomarkers of response/non-response to therapies; 5) improve the competitiveness of European industry and support development of novel solutions. 3TR will sustain beyond the project end the samples and its knowledge base. 3TR will challenge and revolutionize the conventional single-disease based approach with important implications in future disease treatment.
Project title: STriTuVaD (In Silico Trial for Tuberculosis Vaccine Development)
Starting date: February, 1st 2018.
Ending date: July, 31st 2022.
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 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 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.
Project title: ImmunoGrid
Starting date: February, 1st 2006.
Ending date: January, 31st 2009.
The ImmunoGrid is an implementation of virtual human immune system using grid technologies. It can simulate immune processes at natural scale and provides tools for applications in clinical immunology and the design of vaccines and immunotherapies. The developed set of tools will be validated with experimental data and used in clinical applications for development of immunotherapies in cancer and chronic infections. Computational models are highly relevant because immune system is complex and has a combinatorial nature, experimental approaches are expensive, and there are restrictions on the experimentation that can be performed in humans.
The ImmunoGrid project is highly relevant to the IST Call 4, its objectives, focus, and roadmaps. The target user groups are clinicians and developers of vaccines and immunotherapies. The ImmunoGrid applications will provide tools for clinicians and vaccine/immunotherapy developers for identification of optimal immunisation protocols. The unique component of this proposal is that it aims at connecting molecular level interactions (which regulate immune responses) with system level models (which study behaviour of the immune system as a whole). This is a novel approach to disease prevention and treatment which will help improve human health. Applications of the ImmunoGrid include modelling of the natural-size complex system on a large scale. Another important contribution of the ImmunoGrid will be the implementation of individual immune system models across the grid nodes. This fits well into the roadmaps for research and developments in ICT for health focusing on the development of an in silico model of a human being (virtual human).
ImmunoGrid will be developed by an European consortium with members from Italy, France, UK, Denmark, and France and also from Australia. The members of the consortium are leading experts in computational immunology whose developments already have been experimentally validated.