User Personas
Based on extensive user research across pharmaceutical, clinical, and commercial teams, we identified three primary personas representing diverse user needs and technical comfort levels.
Dr. Sarah Chen
Senior Data Scientist
Global Pharma Inc.
DEMOGRAPHICS
• Age: 32
• Location: San Francisco, CA
• Experience: 6 years
• Education: PhD in Biostatistics
Goals & Motivations
• Extract patient journey insights quickly from complex healthcare datasets
• Generate reliable SQL queries that accurately capture clinical criteria
• Validate data before analysis to ensure research integrity
• Accelerate drug development through efficient data processing
Pain Points & Frustrations
• Weeks spent writing custom queries for each new patient cohort
• Manual data validation processes that are time-intensive and error-prone
• Inconsistent data formats across systems requiring constant transformation
• Limited reusability of existing work for similar projects
Lisa Thompson
Marketing Manager
Biotech Solutions
DEMOGRAPHICS
• Age: 29
• Location: Austin, TX
• Experience: 5 years
• Education: MBA Marketing
Goals & Motivations
• Understand market opportunities for new therapeutic areas
• Develop targeted campaigns based on patient population insights
• Measure market impact of product launches and campaigns
• Support business decisions with data-driven market intelligence
Pain Points & Frustrations
• Clinical data too complex to interpret without technical background
• No business context for insights making data difficult to actionable
• Slow turnaround for market analysis missing competitive opportunities
• Language barrier between clinical teams and business needs
Dr. Michael Rodriguez
Clinical Research Director
Rare Disease Institute
DEMOGRAPHICS
• Age: 45
• Location: Boston, MA
• Experience: 15 years
• Education: MD, Clinical Research
Goals & Motivations
• Understand patient treatment pathways to optimize care protocols
• Identify outcome predictors for improved patient stratification
• Support regulatory submissions with robust data evidence
• Advance rare disease research to bring new treatments to patients
Pain Points & Frustrations
• Data scattered across multiple systems making analysis fragmented
• Long delays for basic analysis that slow research progress
• Difficulty translating data to insights without technical expertise
• Limited visibility into data quality and methodology