It is critical that models mirror true disease progression and treatment effects as accurately as possible. Even after creating the appropriate patient pathways, it can be challenging to derive appropriate Markov transition probabilities to accurately represent clinical outcomes.
Calibration allows you to automatically adjust model input values to match against targets based on observed clinical data. The calibration process then adjusts the input values iteratively until the model generates outputs that best match your targets.
Choose the input parameters that the calibration process can modify.
Setup the targets for model outputs to match.
Run the calibration to identify the input values that generate model results that best match your targets.
The demo below introduces this feature.
* Model Calibration will be made available to current annual license holders and standard license holders that have an active Support Contract.