ArticleBMC bioinformatics2020
Generation of digital patients for the simulation of tuberculosis with UISS-TB.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Integrative agent-based modeling of cutaneous lupus: single-cell benchmarking and in silico evaluation of B-cell therapies.Briefings in bioinformatics · 2026Article
- Therapeutic targeting of oligodendrocytes in an agent-based model of multiple sclerosis.PLoS computational biology · 2026Article
- The eight pillars of within-host tuberculosis modelling.Frontiers in immunology · 2026Review
- In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024Article
- Beyond the state of the art of reverse vaccinology: predicting vaccine efficacy with the universal immune system simulator for influenza.BMC bioinformatics · 2023Article
- Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system.Computational and structural biotechnology journal · 2022Article
- Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility.CPT: pharmacometrics & systems pharmacology · 2021Article
- Bayesian Augmented Clinical Trials in TB Therapeutic Vaccination.Frontiers in medical technology · 2021Article
- Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB.BMC bioinformatics · 2020Article
- Toward computational modelling on immune system function.BMC bioinformatics · 2020Article
- Generation of digital patients for the simulation of tuberculosis with UISS-TB.BMC bioinformatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe STriTuVaD project, funded by Horizon 2020, aims to test through a Phase IIb clinical trial one of the most advanced therapeutic vaccines against tuberculosis. As part of this initiative, we have developed a strategy for generating in silico patients consistent with target population characteristics, which can then be used in combination with in vivo data on an augmented clinical trial.
resultsOne of the most challenging tasks for using virtual patients is developing a methodology to reproduce biological diversity of the target population, ie, providing an appropriate strategy for generating libraries of digital patients. This has been achieved through the creation of the initial immune system repertoire in a stochastic way, and through the identification of a vector of features that combines both biological and pathophysiological parameters that personalise the digital patient to reproduce the physiology and the pathophysiology of the subject.
conclusionsWe propose a sequential approach to sampling from the joint features population distribution in order to create a cohort of virtual patients with some specific characteristics, resembling the recruitment process for the target clinical trial, which then can be used for augmenting the information from the physical the trial to help reduce its size and duration.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.