- I’m a Statistician in the pharmaceutical industry, passionate about science, drug development, and health & medicine research.
- I find my roots in math.
- You will find me always on my way to get a cup of coffee.
- My husband thinks I complain about life too much, but honestly, I feel I’m doing just fine as a mid-aged woman.
As a statistician, I am interested in Bayesian modeling, dynamic borrowing, risk-benefit assessment, and innovative clinical trial designs to make drug development research smarter, faster, and more informative.
As a drug developer, I am interested in tracking the landscape and chasing new findings in the field.
- Goal: Bridge rigorous statistical methods and practical decision-making in drug development
It’s been bothering me how resource-consuming the whole process of drug development is. I love the evidence-based way things are done — and as a statistician, that’s basically why I have such a good job — but it still feels crazy that it takes 10–12 years on average for a drug to go from discovery to approval (American Pharmaceutical Review).
I grew up in China, where herbal medicine has a long history and a lot of treatments are passed down through generations. Sometimes it’s literally, “your grandma heard from another grandma that this herb works.” I respect that kind of shared experience — it’s part of our culture — but at the same time, it always made me wondering how to valid evidence without a rigrous science.
So I keep asking myself: how can we make the whole process better?
No matter the starting point — traditional or modern — the goal is the same:
get effective treatments to people faster, and make information sharing and tracking more open and complete.
Maybe the answer lies in using real-world data, data borrowing from existing knowledge, or seamless trial designs.
I’ve been thinking and working a lot about seamless design and data borrowing lately, and it’s becoming a big focus for me.
📚 See my research work on Google Scholar.