Biostatistics Podcast

What are some important skills that are helpful while doing post-graduate training? What is the trend in academia as Biostatistics gets more and more competitive? How to navigate career choice between industry and academia?
Dr. Jin Jin will answer all these questions for you. Jin Jin received her phd in Biostatistics from the University of Minnesota and now works as an Assistant Professor of Biostatistics at the University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics. With a research focus on integrating large-scale datasets to address cutting-edge problems in public health and medicine, she deals with complex issues such as health equity in disease risk prediction, statistical genetics, and Bayesian hierarchical models for high-dimensional data. Let's dive into this episode and see what Jin Jin has shared with us.
Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes.
If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast

What's the difference between epidemiology and biostatistics? What do epidemiologists support in a consulting company? How to build a start-up with your statistical knowledge?
Dr. Paul Arora will answer all these questions for you! Paul holds the position of Vice President, Advanced Epidemiology at Cytel, where his primary areas of focus encompass real-world evidence, epidemiological methods, and the application of machine learning to health outcome issues. Additionally, he played a significant role in establishing Lighthouse Outcomes, a specialized consulting firm dedicated to advanced analytics in clinical epidemiology research. Moreover, Paul is an Assistant Professor within the Division of Epidemiology at the Dalla Lana School of Public Health, University of Toronto. His professional background is rooted in epidemiology, with over fifteen years of experience leading assessments in both public health and clinical epidemiology. He possesses extensive expertise in evidence synthesis methodologies and has held influential consulting positions, collaborating with domestic and international public and private institutions. Let's dive into this episode and see what Paul shared with us!
Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes.
If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast

What are the differences between early phase trial design and late phase trial design? What are some common assumptions for early trial designs? What are some challenges for statistics nowadays?
Dr. Brian Smith will answer all these questions for you. Brian got his Phd in statistics from the University of Kentucky and has been actively involved in promoting quantitative sciences in drug development. He has a diverse background in biostatistics and has held numerous positions in the pharmaceutical industry and academia. He currently holds the position of executive director of Biostatistics at Novartis.
Throughout his career, Brian has focused on early clinical development in the pharmaceutical industry. He has played an active role in the development and implementation of statistical methods to improve the efficiency and quality of drug development. With his vast experience and expertise in biostatistics, Brian has become a respected leader in the field and continues to contribute to the advancement of quantitative sciences in drug development. Let’s dive into this episode and see what Brian shared with us.
Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes.
If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast

How will the biostatistics industry evolve in the coming years? Is SAS still an important skill recruiters look at when hiring for a biostatistics related job?
In this episode, you will hear Doctor Xiaoling Wu answering these questions after being in the field for over 15 years. Xiaoling holds a PhD degree in statistics from the Johns Hopkins University. She has contributed to over 10 successful global submission of drugs treating cancer and CNS disorder. She was the director and head of biostatistics in Legend Biotech in New Jersey. And led the successful BLA submission of a breakthrough cell therapy treating multiple myeloma during her 3 year tenure. Currently, Xiaoling is the statistics technical lead of a game changing ADC at a leading global oncology company.
Xiaoling was lead statistician of five successful IND clearance and 1 BLA/MAA/PMDA approval valued at $5B. She addressed statistics query from FDA, SEC and institution investors and co-authored over 150 abstracts published at ASCO, ASH and other international medical congress. Let's dive in this episode to see what Xiaoling shared with us
Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes.
If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast

Can you do research while being in a industry setting? How do people do science in real world ? What are some technical and cultural difference between statistics and machine learning?
Jonathan O'Brien will answer all these questions for you! Jonathan obtained his PhD degree in biostatistics from University of North Carolina and currently works as a principle data scientist in Calico life science which is a health care biotech company that focuses on combating aging and aging related diseases. His main research interest has been focused on improving the mathematical modeling and downstream analysis of mass spectrometry proteomics experiments which involves missing data techniques, Bayesian hierarchical modeling, clustering and compositional data analysis.
It was great talking to Jonathan since he gave me a lot of new perspectives, and I learned a lot more about proteomics studies and what he is working on. Let's dive into this episode to see what Jonathan shared with us!
The paper mentioned in this episode can be found here: The effects of nonignorable missing data on label-free mass spectrometry proteomics experiments.
Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes.
If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast