The Challenge
Turning fragmented market data into a clear view of competitive position
You cannot defend a position you cannot see.
A first-in-class oral therapy for a mutation-defined patient population was expanding into later lines of treatment, where the convenience of an oral option could become increasingly relevant. At the same time, emerging oral competitors were entering the same treatment space.
The brand needed to understand where it stood, which patients were most exposed to competitive switching, and where the greatest opportunities for differentiation existed.
However, three gaps made this difficult.
The market denominator was unclear. Mutation status was not consistently visible in claims data, making it difficult to reliably size the eligible population. Without linking patient-level lab and EHR information, share and opportunity estimates were based on assumptions rather than a common denominator.
The timing of competition was difficult to predict. Patient progression patterns varied considerably, meaning that eligibility for subsequent lines did not follow a consistent timeline. As a result, opportunities for treatment switching could emerge at different points in the patient journey.
The competitive picture was fragmented. Claims, laboratory, EHR, and specialty pharmacy data each provided a different part of the story, but there was no integrated view of the patient journey or where competitors were gaining traction.
Our Solution
Chryselys integrated claims, EHR, laboratory, and specialty pharmacy data to create a patient-level view of the treatment journey. This foundation was then used to build a continuous competitive intelligence and benchmarking framework.
1. Market Quantification
Linked data was used to identify and size the mutation-positive and post-progression populations, establishing a consistent denominator for downstream analysis.
2. Competitive Benchmarking
Competitors were assessed across the attributes most relevant to treatment choice, including efficacy, safety and tolerability, convenience, and access to testing.
3. Adoption Hurdles Assessment
The analysis identified where testing gaps could limit patient identification and quantified the untested population by oncologist and site.
4. Switching Analytics
Patient treatment sequences were tracked to understand testing adoption, treatment progression, sequencing patterns, and competitive switching over time.
5. Scenario Modelling
Potential competitive developments – including new entrants, combination strategies, and label expansions – were modelled to assess how changes in the landscape could affect future competitive positioning.
Business Impact
From hindsight to earlier visibility
Continuous tracking of testing and switching patterns provided earlier visibility into changes in the competitive landscape, supporting preparation for future market developments.
From estimates to a defensible denominator
A patient-level data foundation gave teams a more consistent basis for market sizing, forecasting, and share assessment.
From product attributes to meaningful differentiation
Benchmarking connected product characteristics with factors influencing treatment choice, helping sharpen the areas where differentiation could matter most.
From broad targeting to focused engagement
Oncologists could be prioritized based on a combination of untested patient volume and competitive exposure, creating a more focused basis for engagement.
From reactive defense to scenario-based planning
Potential competitor moves could be evaluated in advance, allowing the team to consider response options under different market scenarios.
