More than half of new drug launches are first-in-class, and many of these are breakthrough therapies without precedent. How can forecasters develop demand models that accurately predict a new drug’s impact on the treatment landscape with sparse data available?

In this analogue forecasting article, we look at how forecasters can use the past to better predict the future. We discuss:

• How to account for narrow product labels and complex patient segmentation
• The importance of building a “basket” of analogues to inform patient-based forecasting
• How to expand the horizon with future-looking analogues