Predicted Demand
Influence of region features
Demand by geographic region
Accelerating Innovation in Vaginal Formulations in Support of Women's Health
Grand Challenges Intitiative (Vaginal Products)
Objective 2: Define characteristics of an ideal vaginal product
We propose that user demand for novel vaginally administered products (VAP) can be predicted based on (a) geospatial information, and (b) the features of the product.
To demonstrate this, we propose a method of describing and predicting the system that generates user demand for particular product features using a Geospatial Bayesian Network.
Our approach to building and quantifying Bayesian Network models based on research synthesis methods allows us to make full use of available data before gathering more. We have used this approach in a range of industries where data are sparse such as conservation and food safety with great success.
While we expect most users will explore the model outputs using a live version of this demonstration, the model is also able to be queried via API, allowing other researchers and developers to build their own products using the model.
The major stages of the proposed project are outlined in the graphic below.
Source data filtered to your inputs
In this screen users will be able to see and download the source data filtered to their inputs, to allow for use in their own workflows.
The data in the current demonstration is based on a simple piecewise function to allow reviewers to test the dashboard and get a feel for its potential use cases.
