Dave:
Welcome back to the podcast. Today I’m joined by Dr. Lixia Yao, the founder and CEO of Polygon Health Analytics. She has a PhD in biomedical informatics and is doing fascinating work at the intersection of health data, machine learning, and real-world evidence. Lixia, thanks for being here.
Dr. Lixia Yao:
Thanks for having me, Dave. I’m excited to chat.
Dave:
To kick things off, can you tell us what Polygon Health Analytics does in a nutshell?
Dr. Lixia Yao:
Absolutely. Polygon Health Analytics helps organizations make sense of real world data—things like electronic health records, insurance claims, and patient registries—to generate real world evidence. That evidence can support everything from clinical decision-making to regulatory submissions and drug development.
We use machine learning, statistical modeling, and domain expertise to turn messy, fragmented data into actionable insights. Our clients include pharmaceutical companies, healthcare providers, and health tech startups.
Dave:
That’s super cool. For those who might not be familiar with the term—what exactly is “real world data,” and how does it differ from clinical trial data?
Dr. Lixia Yao:
Great question. Real world data is collected from everyday healthcare settings. It’s different from the data collected during a controlled clinical trial. Real world data comes from electronic health records, insurance claims, patient registries, or even wearables and digital health apps. So it reflects what actually happens in real clinical environments and patient lives.
At Polygon Health Analytics, we specialize in transforming this messy, heterogeneous, and often incomplete data into structured, usable information. We apply advanced data science, machine learning, and AI techniques to make sense of it. This helps our clients—whether they are pharmaceutical companies, healthcare providers, or health tech startups—make better decisions in drug development, care delivery, and business strategies.
Dave:
That’s really interesting, and I think it’s something most people probably don’t think about when they hear “health data.” It sounds like there’s a lot of complexity involved. What are some of the challenges you face working with real world data?
Dr. Lixia Yao:
Yeah, great question. The biggest challenge is data quality. Real world data wasn’t collected for research purposes, so it tends to be noisy, inconsistent, and missing important information. For example, if you look at an electronic health record, there might be different formats across systems, human errors, or missing fields.
So a lot of our work starts with cleaning and harmonizing the data before we can even analyze it. Another challenge is data privacy. We need to follow strict regulations like HIPAA to ensure that patient identities are protected. But at the same time, we want to maximize the value of the data to improve health outcomes. So there’s a balance we have to strike.
Dave:
That makes sense. And I imagine working with clients across the healthcare ecosystem adds another layer of complexity. How do you tailor your solutions depending on the client?
Dr. Lixia Yao:
Yes, exactly. Each client has different needs. A pharmaceutical company might be focused on understanding treatment patterns or patient adherence, while a health system might be more interested in operational efficiency or identifying high-risk patients.So we work very closely with our clients to define the research questions, select the right datasets, and choose the right analytical approach. Sometimes it’s traditional statistical modeling, other times it’s deep learning or NLP, depending on the problem. We really try to be flexible and outcome-focused.
Dave:
Very cool. I’d love to switch gears a bit and talk about your experience as a founder. What has it been like building Polygon Health Analytics from the ground up?
Dr. Lixia Yao:
It’s been both challenging and rewarding. Coming from a technical and academic background, I had to learn a lot about business, marketing, operations—all the things you need to run a company that aren’t necessarily taught in a PhD program. But I’ve also found it to be incredibly fulfilling. I get to build something from scratch, hire a team, set the culture, and directly shape the vision.
And I think being a founder in the health tech space comes with an extra sense of purpose. We’re not just building a product; we’re contributing to improving people’s lives through better data and insights.
Dave:
That’s powerful. Do you have any advice for aspiring founders—especially those coming from research or academic backgrounds—who want to start a company?
Dr. Lixia Yao:
Absolutely. I’d say: don’t wait until you feel “ready.” There’s never a perfect moment. Starting something new is inherently uncertain. What helps is staying curious, asking lots of questions, and surrounding yourself with people who are smarter than you in different areas. Also, be okay with iterating. The first version of your product or service will probably be wrong in some ways, and that’s fine. The key is to listen to your customers and learn quickly. And lastly, lean into your unique strengths. For me, that was deep technical knowledge and domain expertise—and that gave me an edge in building a product that truly works for our users.
Dave:
Great advice. What’s next for you and Polygon Health Analytics?
Dr. Lixia Yao:
We’re focused on expanding our capabilities in AI-driven analytics and making our platform more scalable so we can serve a wider range of clients. We’re also exploring partnerships with health systems to apply our models more directly in clinical settings. It’s an exciting time—there’s so much potential to improve healthcare with better data.
Dave:
Amazing. Lixia, thank you so much for being here and sharing your insights. I learned a lot and I’m sure our listeners did too.
Dr. Lixia Yao:
Thanks so much, Dave. This was a lot of fun.