Meet Our
Real-World Data Experts
Madhav KC, PhD, MPH
What is your role at Norstella?
Tell us about your real-world data expertise.
What’s been one of the most rewarding or exciting projects that you’ve been a part of and why?
All of the projects I’ve worked on have been quite rewarding and interesting in their own ways, but one of the most rewarding recently involved a collaborative discussion around advanced epidemiologic methods. It was exciting because the team brought diverse perspectives, and together we arrived at a creative and rigorous solution to a complex methodological challenge. Our newer studies using NorstellaLinQ data are particularly engaging, and exploring the depth and flexibility of this dataset has opened up new possibilities for real-world evidence generation.
What does a day in the life of a RWD analyst look like at Norstella?
A typical day involves a mix of strategic collaboration and technical execution. I often start the day by meeting with clients to understand their research objectives, discuss study designs, and provide input on epidemiological and biostatistical considerations. Throughout the day, I collaborate with internal teams to review data products, align on study implementation plans, and troubleshoot any challenges that arise. I also spend time preparing and presenting study results, ensuring they are both scientifically rigorous and aligned with client expectations. The role requires balancing analytical work with cross-functional communication to drive meaningful, data-driven insights.
What types of problems are our RWD helping pharma solve?
Through real-world data analysis, Norstella helps pharmaceutical companies address key questions related to patient journeys, treatment patterns, and healthcare utilization. We support clients in identifying target patient populations, tracking how patients move through the healthcare system, and understanding variations in care across providers, geographies, and time. Our RWD studies help quantify disease burden, assess real-world effectiveness, and evaluate market performance of therapies. This evidence supports decision-making around clinical development, health economics and outcomes research (HEOR), market access, and post-market surveillance.