Indegene Supports Global Pharma with Cost-Effectiveness Analysis of Oncology Drug vs. Biosimilars

The Customer

A leading global biopharmaceutical company sought to evaluate the cost-effectiveness of a drug compared to Biosimilar 1 and Biosimilar 2 in adult patients receiving myelosuppressive chemotherapy for early-stage breast cancer and non-Hodgkin’s lymphoma. The company required a solution that could seamlessly bridge data gaps—integrating extrapolated data and robust sensitivity testing—to deliver accurate, reliable inputs for building a strong and defensible cost-effectiveness model. However, the lack of comprehensive real-world data posed a significant challenge. To overcome this, the team needed to employ advanced data extrapolation methods, carefully calibrated assumptions, and rigorous sensitivity analyses to develop a credible economic model that reflected clinical realities and supported informed decision-making.

The Solution

With a triangulated approach, we implemented a structured methodology to enhance the accuracy and credibility of the cost-effectiveness model:

Comprehensive Literature Review – Indegene conducted an extensive review of relevant publications and data sources from healthcare systems comparable to the client's geography. This established a robust foundation for the analysis and helped identify key parameters for advanced data extrapolation methods in the cost-effectiveness model.

Expert Insights via KOL Survey – A survey of 20 oncologists was conducted to gather real-world data on critical cost and healthcare utilization metrics. This included injection costs, CBC and ANC assessments, length of administration, hospitalization, post-hospitalization, and outpatient expenses, providing valuable insights that couldn't be obtained from literature alone.

Draft Model Development – Indegene built a cost-effectiveness model referencing an established framework from a similar healthcare setting. This model integrated clinical and economic assumptions derived from both the literature review and KOL survey data.

Model Validation & Refinement – The model's credibility was strengthened through a rigorous validation process that aligned insights from the literature review and KOL survey. This ensured the model's reliability and relevance to real-world clinical scenarios in the target geography.

Outcomes

Implemented a multi-approach strategy that effectively addressed data gaps in the cost-effectiveness evaluation of the product.

Designed a cost-effectiveness model tailored to the geographical context that generated insights on the product's value to support informed decisions on the drug launch