Drivers of prescriptions

Objective

Understand the most important factors driving drug choices at different stages of a patient journey, basing which create favorable patient profiles for New to Market and Switch targeting.

Approach

  • Data sources: Integrated Claims and EMR data
  • Overview of approach:

  • For Model Building, D cube employed a combination of:

    Strong Predictive Techniques, that leverages machine learning concepts (Random Forest) to get best-in-class models

    Descriptive Techniques, like decision trees to enable attributes classification enabling business deriving robust marketing strategies.

Life Sciences Strategy Consulting

Results

New to Market Patients

Model Statistics – 83% Accuracy
Key Insights
Key Decision factors for New to market Prescription
  • Prescriber Specialty
  • Disease Severity
  • Biomarker results
  • Comorbidities
  • Concomitant drugs
Impact
7% lift in New to market patient share

Switch Patients

Model Statistics – 75% Accuracy
Key Insights
Key Decision factors for Drug choice while switching
  • Patient choice
  • Market Access
  • Exposure to Injectables
Impact
13% lift in 2nd line Patient Share