What, specifically, is your role at Norstella?
I lead the Medical Science function and oversee a team of highly skilled medical analysts with backgrounds in clinical practice, data science, and real-world evidence. My role is to ensure that our clinical and analytical strategy aligns with client needs, guiding the transformation of complex healthcare data into actionable insights. I work cross-functionally to support data curation, clinical normalization, and entity extraction efforts across multiple therapeutic areas.
Tell us about your real-world data expertise.
My expertise centers on bridging clinical context with real-world data, especially in mining and normalizing unstructured EMR data. I’ve led initiatives involving the development of entity frameworks for oncology, dermatology, and hematologic malignancies—translating nuanced clinical language into structured formats that power advanced analytics. I also specialize in designing scalable approaches to clinical data standardization, including comprehensive codebooks and data spec alignment.
What’s been one of the most rewarding or exciting projects that you’ve been a part of and why?
One of the most exciting projects has been leading an natural language processing effort to extract and structure detailed clinical entities in plaque psoriasis. It brought together deep clinical knowledge, technical innovation, and real impact—allowing our clients to better understand disease severity and treatment pathways. It was also a standout collaboration across our medical, data, and product teams.
What does a day in the life of a real-world data analyst look like at Norstella?
Our medical analysts balance clinical rigor with data interpretation. A typical day may involve reviewing unstructured EMR notes, refining clinical concepts for extraction, or validating mapping logic for molecular markers or treatment regimens. Analysts often work on building and refining market baskets that define disease cohorts or treatment categories, and help construct lines of therapy to map treatment journeys over time. They also collaborate closely with data science and client-facing teams to ensure the clinical integrity of our insights and to support evolving client needs across different therapeutic areas.
What types of problems does real-world data help pharma solve?
We help pharma answer questions that are difficult to address through traditional trials: What are real-world treatment patterns? How does disease severity manifest outside of controlled settings? What biomarkers correlate with treatment response or resistance? Our work helps shape more effective clinical development plans and supports market access and HEOR strategies grounded in real-world data.
When you’re not analyzing data, what do you like to do?
Outside of work, I love exploring new places through travel—whether it’s a weekend getaway or an international trip, I enjoy discovering different cultures and cuisines. Cooking is another passion of mine; I find it both creative and relaxing, and I especially enjoy experimenting with dishes inspired by our travels. Most importantly, I cherish the time I spend with my five-year-old, whether we’re baking together, playing outside, or just curled up with a good story. Family time is always a priority.
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