Augmentes clinical trials in Tuberculosis therapeutic vaccination

Within the STriTuVaD project, the consortium is developing a methodology to generate in silico patients to enhance the data from the Phase II clinical trial that started in September with the first patients’ enrollment.


But how exactly is the information from computer simulations combined with data from the clinical trial?


The approach is detailed in a paper authored by Dr Kiagias et al., recently published on Frontiers in Medical Technology, where the authors propose a Bayesian hierarchical method for combining in silico and in vivo data into an augmented clinical trial using the UISS-TB simulator developed in the project.


The simulation platform

The Universal Immune System Simulator (UISS) previously described here, is an agent-based model (ABM) able to simulate the evolution of tuberculosis in the lung after RUTI vaccination.

This ABM produces in silico data from a number of biological entities and chemical species (e.g., cytokines) for an individual virtual patient, identified and characterised through an initial vector of 22 features (e.g. lymphocytes subpopulation levels, bacterial load, BMI).


From the virtual patient to the virtual cohort