Built to make evidence more reliable, not just more available.
Four ways PurpleLab CARES puts better evidence into practice:
Reproducible Research
Research we conduct, publish, and put through peer review.
- Conduct original research on the questions that matter most, using transparent, well-documented methods
- Replicate published studies to verify and extend what other researchers have found
- Perform sponsored research that produces rigorous, defensible evidence
- Publish thought leadership that puts findings in front of the people who need them
Rigorous Methods
Methods and tools that raise the reliability of research industry-wide.
- Build transparent, operational definitions into study design from the start, not audited after the fact
- Validate and advance research methods through education in shared best practices
- Contribute to the tools that put those practices to work
- Curate, standardize, and evaluate real-world data to ensure fitness for purpose
Academic Partnerships
Mentorship and study design help, alongside the data.
- Co-design studies directly with faculty and students
- Mentor academic researchers in best practices through hands-on training
- Provide opportunities to collaboratively publish studies that use PurpleLab’s representative real-world data
- Support grant- and industry-sponsored projects with data access and linkage
Patient Communities
Answering questions for communities that don’t have a research team.
- Welcome patient voices from foundations, rare-disease groups, and patient advocacy organizations into our research
- Surface patient perspectives and prioritize unanswered questions
- Support underserved patient populations through projects such as investigating new uses for existing therapies
The research depth behind CARES.
CARES brings together researchers, analysts, data scientists, biostatisticians, epidemiologists, and clinical health informaticists across therapeutic areas including oncology, cardiology, mental health, and rare disease.
That multidisciplinary depth lets us move from research question to study design, analysis, and evidence, with the rigor needed for findings to withstand scrutiny and the transparency needed for others to build on them.
We map treatment flows and disease progression using claims linked with social determinants of health data, and measure outcomes and cost of care using standardized, CMS-based pricing models.
Natural Language Processing
Statistical Analysis
Custom Reports & Dashboards
Artificial Intelligence
Data Science
Privacy & Data Governance
Advanced Methodology