KMK Leverages Anonymized Patient-Level Data (APLD) to Identify Market Opportunities
How can you use patient-level data to help rebound from a sluggish product launch?
One of our clients, a growing specialty pharmaceutical company, had just received approval on a new product that could treat two different diseases. However, after one year on the market the new drug’s uptake was not increasing as fast as expected, resulting in underwhelming sales volume.
This client wanted to understand the cause of such a stagnant product launch by analyzing physicians’ prescribing behavior to restructure their business and commercial strategies but were struggling to find answers due to two key challenges:
- For this particular product, traditional physician-prescribed data lacks good coverage and granularity in physician prescribing behavior required to drive solid business decisions
- Since the product has multiple indications, distinguishing the sales by indication through traditional physician prescription data is nearly impossible
This client also suspected that the prescribing behavior for the two different indications could provide some important clues into why their sales were underperforming. After careful evaluation, they partnered with KMK to verify their assumptions and determine the best marketing strategy moving forward.
Our team at KMK used Anonymized Patient-Level Data (APLD) to group patients by diseases that the new product was indicated to treat. We then conducted an in-depth analysis to evaluate the treatment patterns and assessed the physicians’ prescribing behaviors based on their specialties, followed by a thorough investigation of the patient journey to evaluate timing from diagnosis to treatment and then assessed by the product and specific indication.
Here are the steps we took to come up with a plan to help our client rebound after their less-than-stellar launch performance:
- We leveraged APLD data to separate patients by diseases that the product was indicated to treat
- We took a deep dive into treatment patterns
- We assessed prescribing behavior by physician specialty
- We Investigated the patient journey to evaluate the timing from diagnosis to treatment
After careful analysis, our team discovered:
- The newly launched product had a much higher market share for one indication (to treat a more severe disease) over the other.
- Specialists tended to write more prescriptions of our client’s new product compared to generalists.
- It took a longer time for generalists to begin to prescribe the new product than specialists
These results improved forecasting by providing more accurate current market share estimations using these indicators. It also presented our client with valuable business insights for determining the next phase of their marketing strategies and tactics, such as planning a comprehensive physicians’ education program for the generalist & patient segmentation.
Moving forward, our clients would have the tools to maximize their impact at product launch by focusing more on maintaining APLD and conducting patient-level data analytics to deal with missing data issues and get better insights. They learned that improved study design can help in minimizing the bias caused by missing data, and a single analysis design will not always be appropriate for all business questions.
Each unique business question must be answered with a unique and appropriate analysis design – which is different for every organization and every situation. Only then can the answers be integrated in a scientific way to provide synthesis evidence.
Looking for advice on your next product launch, or answers as to why your product is performing a certain way? Contact us today for a no-hassle free consultation.