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RCT Simulations for Enhanced TB Treatment Outcomes

This project is a FastAPI-based application designed to simulate datasets based on various population parameters. It offers endpoints for dataset simulation, statistical power calculation, optimization of sample sizes, and generation of clinical datasets.

Clinical Trial Context

This simulation study is tied to the clinical trial work on identifying biomarkers that can predict progression from latent tuberculosis infection to active tuberculosis disease.

The referenced clinical trial builds on the C-TRIUMPH household contacts cohort, including household contacts who progressed from latent TB infection to active TB. Its purpose is to compare immune and biomarker profiles between progressors and non-progressors, including plasma biomarkers, microRNAs, TB-antigen and mitogen stimulated cytokine and chemokine responses, growth factors, and other immune factors.

Study aims include:

  • Identify biomarkers that can accurately predict progression from latent TB infection to active TB disease.
  • Measure baseline plasma biomarker profiles in household contacts who progress versus those who do not.
  • Profile baseline microRNAs in household contacts who progress versus those who do not.
  • Measure baseline unstimulated, TB-antigen stimulated, and mitogen stimulated cytokine and chemokine responses.
  • Measure baseline unstimulated, TB-antigen stimulated, and mitogen stimulated growth factors and other immune factors.

Features

  • Simulate Dataset: Generate datasets based on user-defined population parameters.
  • Calculate Statistical Power: Compute the statistical power for different treatment groups.
  • Optimize Sample Size: Adjust sample size to achieve desired statistical power.
  • Generate Clinical Dataset: Create a clinical dataset with an equal number of samples from each population group.

App Links