Experimental Features
Experimental Features
Section titled “Experimental Features”KerusCloud® Experimental Features enable expediency in getting new functionality to users in the production environment. Experimental features are those that are undergoing statistical validation, as a result, they may be modified with future updates where data relevant to the feature may change or be lost.
Active experimental features are listed below -
| Feature: | Description: | Active since: |
|---|---|---|
| Bayesian Dynamic Borrowing (BDB) | Added support for BDB, enabling integration of multiple prior components (informative or uninformative) with configurable weighting. | 19/03/2026 |
| Bayesian Dynamic Borrowing (BDB) | Update: The following BDB metrics have passed statistical validation and are now stable in KerusCloud® - P(Difference in Means), P(Difference in Proportions), P(Mean), and P(Proportion). The following metrics remain as experimental features - P(Coefficient), P(Event Proportion at given Time), and P(Risk Difference) | 18/06/2026 |