geraschenko / metis

Metis implements simulation tools for clinical trial enrollment.

Baseline Site Selection Tool

The Baseline Site Selection Tool (BSST) implements simulation tools for clinical trial enrollment. BSST is being developed for the public good with the initial goal of expediting clinical validation of vaccine candidates for COVID-19, with a focus on targeted site selection to support enhanced recruitment for vaccine research.

BSST allows the user to input model forecasts for regional disease prevalence, as well as historical disease incidence data. One potential source of US-only model forecasts is the CDC ensemble. A potential source of historical data is Google Cloud’s open repository.

How to use the Baseline Site Selection Tool

This repository includes Jupyter notebooks, a Python package, and Dockerfiles for the simulation tools.

By default the notebooks run with a small amount of demo data, so you can run them anywhere that you can run Jupyter notebooks.

For use of the notebooks to run simulations on your own, larger scale data, you will need to run them on a machine with more CPUs and memory, such as those available via Terra. Please see the computational requirements listed at the top of each notebook.

Different trial designs will have different additional requirements for the simulations. You can reach the Baseline Site Selection Tool team at [email protected] to discuss how those changes can be added to this tool.

How to contribute to the Baseline Site Selection Tool

First please see the contribution guidelines. Then refer to the development instructions for further detail.