The Opportunity
In mid-2021, a brand team at a mid-sized Life Sciences organization had a desire to understand the future market landscape and most probable forecast given brand investments and external market headwinds.
Our Solution
Propensity4 conducted a market mapping exercise focused on:
- Patient Profile
- Source of Business
- Sizing of Priority Patient Cohorts
Propensity4 built a most probable forecast focused on new writing and re-writing tempered by external headwinds.
Most Probably Forecast = Statistical Baseline + Commercial Operations Assumptions – Exogenous Headwinds
The Results
Team identified drivers of performance challenges, specifically reimbursement action and challenges in the long term care (LTC) channel, and identified targeting activities to address controllable challenges.
Team documented areas to ramp in retail and LTC through increase in new writers and driving additional re-writing from existing prescribers.
Identified nearly 10,000 additional annual TRxs to be gained because of recommended changes; stemming a persistent decline in the LTC channel.
Learn more about our work.
Jump to a slide with the slide dots.
Welcome to the Team: Isabelle Amick, Senior Director of Data Science
We’re thrilled to announce that Isabelle Amick has joined Propensity4 as our new Senior Director of Data Science!
Read more
Powering a U.S. Launch: Building a Commercial Infrastructure from the Ground Up
End-to-end US launch support for EU client’s dry eye device—from KAM team and CRM setup to data analytics, targeting, and incentive strategy.
Read more
Chris Savage
Improve your forecast with “bottom-up” methodologies
This blog explores how “bottom-up” forecasting, particularly Most Probable Forecasting (MPF), enhances pharmaceutical brand planning.
Read more
Predictive Patient Engagement Program
Personalized patient engagement boosted therapy adherence with AI-driven insights, risk scoring, and tailored support recommendations.
Read more
Isabelle Amick
Rare-disease patient finding: Identifying the “right” patients at the “right” time.
Accelerating rare disease diagnosis through data-driven patient finding and predictive modeling to connect patients with the right HCPs faster.
Read more