Meet our expert

mike-munsell-headshot

Real-World Data Expert

Mike Munsell, PhD

Director, Real-World Data, HEOR
As Director, RWD HEOR, Mike works with clients to design studies that use real-world data to evaluate the clinical effectiveness and economic impact of treatments. He advises on methodological considerations and leads the publication of these findings in peer-reviewed journals and conference presentations.

What is your role at Norstella?

As Director, RWD HEOR, I work with clients to design studies that use real-world data to evaluate the clinical effectiveness and economic impact of treatments. I advise on methodological considerations and lead the publication of these findings in peer-reviewed journals or through conference presentations.

Tell us about your real-world data expertise.
I specialize in applying statistical and econometric methods to administrative claims and electronic medical records data, including predictive modeling and machine learning.

What’s been one of the most rewarding or exciting projects that you’ve been a part of and why?
I looked at the early real-world impact of a rare disease treatment that has only been on the market for a couple of years. The sample size was small, so we had to be very thoughtful of how we designed the study, including linking multiple data sources together. We saw both evidence of clinical effectiveness and cost offsets in the early view data, which was exciting!

What does a day in the life of a RWD analyst look like at Norstella?
I spend a lot of time meeting with clients to understand their research objectives, and then writing study protocols to ensure we’ve designed something that is scientifically sound. For projects that are currently in the analysis phase, I review output and think through how to best translate the findings to real world policy makers, who will eventually be looking at the data we produce.

What types of problems are our RWD helping pharma solve?

Generating value and evidence for rare conditions. With how much data we have and the availability to link at the patient level across data assets, we are able to identify patients that are typically hard to find in real-world sources.

When you’re not analyzing data, what do you like to do?
I spend time with my family (I have two young kids) and play music in a few bands (I play bass guitar).

Published insights

Article

In an Uncertain Policy Environment, Pharma Needs Timely Real-World Data More Than Ever

Timely access to RWD doesn’t just inform policy responses, it empowers life sciences organizations to track, anticipate, and shape patient outcomes in real time.
Article

How machine learning strengthens real-world data and disease identification: 5 use cases in 5 minutes

Machine learning is a powerful tool in the life sciences industry, making evidence generation more efficient and precise and bolstering real-world data (RWD) to identify diseases earlier, trigger timely interventions, and recommend screenings and physician referrals. Our blog series, How Life Sciences is Leveraging Machine Learning: 5 Use Cases in 5 Minutes, explores five recent studies that used machine learning to analyze RWD or improve clinical practice.
Article

Data-driven development: How real-world data and AI are transforming clinical trials

Earlier this month, Dandelion Health announced the launch of the first artificial intelligence (AI) database specifically aimed at bolstering research for GLP-1 drugs, giving trial sponsors unprecedented insights into which indications to investigate next.
On-Demand Webinar

The scientific and operational elegance of study replication with real-world EHR data: A vitiligo and alopecia example

This webinar, hosted by experts from Panalgo and OM1, looks at the scientific and operational details behind study replication, using vitiligo and alopecia areata as an example.
Article

Q&A: How AI and ML are reshaping the research landscape

In a rapidly evolving landscape where artificial intelligence (AI) and machine learning (ML) have become household terms, their impact on biopharmaceutical research and epidemiology is profound. I caught up with Mike Munsell, PhD, Director of Research at Panalgo, to discuss how these technologies are transforming the healthcare research landscape and their real-world applications in biopharmaceutical R&D.
Article

What’s next for the life sciences industry? Four trends to watch in 2024

2023 was an eventful year for the life sciences industry, with the Inflation Reduction Act (IRA) and game-changing technology like ChatGPT dominating the headlines. Will biopharma’s constrained budgets, reorganizations, and reductions in force continue in 2024, or will there be a healthy rebound from these prunings?
Article

Leaning into RWE: The IRA is here, so now’s the time

Manufacturers are continuing to wrestle with the effects of the Inflation Reduction Act (IRA) on their business plans and revenue streams. Although some of the IRA’s impacts are still uncertain, real-world evidence (RWE) is an important tool for manufacturers in navigating the road ahead, as it will help them demonstrate the value and comparative effectiveness of their treatments, and help patients get access to the treatments they need.
Article

How life sciences is leveraging machine learning: 5 use cases in 5 minutes

It’s no secret that machine learning is establishing itself as a powerful tool in the healthcare analytics industry. However, there is still some uncertainty around how to employ it. In our editions of Insights & Innovators: 5 Machine Learning Use Cases in 5 Minutes, we will take a look at five recent studies that used machine learning (ML) to analyze real-world data.
Article

How machine learning can advance disease predictability

In this article with AiThority, Chao Li (AbbVie) and Mike Munsell (Panalgo) discuss how machine learning models and AI technology can enhance our ability to predict disease.

Our AI capabilities are built to evolve—transforming data into insight, insight into action, and action into impact.