Forecasting by biomarker, not tumour type
If you are forecasting for an asset across multiple tumour types, forecasting using biomarkers may be a favourable approach for you.
If you are forecasting for an asset across multiple tumour types, forecasting using biomarkers may be a favourable approach for you. Especially if you are factoring in multiple countries and scenarios.
How does this work? Kris Barker, senior consultant at J+D Forecasting explains:
Historically, oncology forecasts have often focussed on a specific tumour type as the basis for how the model is structured and populated. If you have an asset that spans across multiple tumour types, this can make forecasting more challenging (especially if you are also factoring in multiple countries and scenarios).
In more recent times, the focus has become more on the opportunity for the asset rather than the tumour types for which the asset may get a final indication. It may well be the case that an asset in development targets a specific biomarker across a number of tumour types.
BRCA1, as an example, is closely associated with ovarian cancer and to a lesser extent prostate and pancreatic cancer. If you are forecasting an asset that is likely to be closely linked to the BRCA1 biomarker, then it may make more sense to approach your forecast from a biomarker perspective (and to size your potential patient population on those who exhibit this biomarker), than to take an approach based on tumour type.
Download this free example model that demonstrates the above principle.