A one-stop-shop for forecasting assumptions and building market landscape overviews

We leveraged real-world data and secondary research information to develop a self-servicing tool for building forecasting assumptions and market landscape overviews for multiple oncology indications

Oncology indications supported

Project cost savings

Actively using stakeholders

“With the tool in place, we are now able to cut down on a significant amount of time invested in data exploration, ADS buildings, and KPI development.

Now our team is spending more time on generating more meaningful insights and not worry about data preparation anymore.”


The customer has multiple assets across different therapeutic areas including Oncology. Given the complex nature of Oncology, the customer wanted to build a dynamic tool that will give a detailed view into dynamics of the market and also be able to provide ready-to-use KPIs for their forecasting needs.


D Cube Analytics proposed building a tool that will leverage both real world data and secondary research data. By doing so, it will not only address the ask from the client, but also serve as a educational platform for anyone from the client side who wants to get up to speed on the market in terms of understanding the details around the products and their performance.


As the first step, we developed advanced algorithms to clean the unstructured data to define regimens and LoTs as performing these mappings is critical to building an appropriate market overview for any oncology indication.

Given that we are combining both drug information from secondary research and real-world data, it gives us abundant number of metrics that we could leverage. Hence, it becomes important to identify the relevant KPIs from this ocean of metrics.

The KPIs that we identified includes regimen share, peak patient share, time to peak, and other compliance-related metrics like adherence and duration of treatment. These metrics are not only critical for drawing insights into the market evolution but also are provided to the forecasting team as ready-to-use KPIs for their modelling needs.


  1. Helps gain a robust understanding of the changing market dynamics due to various events such as new launches, patent expiry, label expansion, etc
  2. To understand trends in real-world product usage and align their marketing, market access, medical affairs, and commercial operations to maximize patient benefits and revenues
  3. Build robust forecasting assumptions in terms of patient share, peak patient share, time to peak, analog analysis, adherence, persistence, and median duration of treatment


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