Switch Prediction Boosts Rare Disease Patient Starts by Targeting Key HCPs

THE CHALLENGE

A mid-sized pharmaceutical company with a portfolio of drugs in rare disease, faced severe challenges in trial and adoption of its ITP (Immune thrombocytopenia) drug.

Lack of HCP awareness and a small sales force challenged the manufacturer, despite the drug’s strong clinical value proposition against competitive drugs. While evidence suggested that HCPs who tried the drug consistently became adopters, getting information into the hands of the right HCPs remained a struggle.

This client sought to increase their market share by identifying patient personas that had a high potential for trial of their therapy based on key identifying factors. Due to the size of their sales force, it was critical that they optimize their HCP targeting efforts. Through this potential patient identification process, they hoped to link patients to their corresponding HCPs in order to maximize their sales force impact.

THE SOLUTION

• EVERSANA partnered with this client to deploy its switch prediction solution to determine, with high accuracy and precision, the highest potential patients, and subsequently HCPs who are the best targets for the brand.
• We worked with the client’s brand, marketing and medical team to understand the patient journey, and utilized machine learning to identify factors (e.g. demographics, Rx volumes, side effects, comorbidities, etc.) likely to be predictive of trial.
• We built a number of ML based prediction models to determine high potential patients for the brand.

THE RESULTS

The predictive model proved positive outcomes: