Using R in Regulatory Review

Tae Hyun (Ryan) Jung, Ph.D., is a Senior Statistical Reviewer in FDA/CDER/OTS/OB/DBVII. He has comprehensive NDA/BLA/PMR review experience from phase III/phase IV safety-focused reviews and phase III efficacy reviews including RWE efficacy. He is also leading multiple RWE/RWD research projects using machine learning/artificial intelligence in causal inference, data quality, and synthetic patient data. Tae Hyun completed his Ph.D. degree in Biostatistics at Yale University.
Presentation title: Achieving Regulatory Approval using R – Lessons learned from a recent RWE sNDA approval

Hye Soo Cho is a statistical analyst in the Office of Biostatistics at CDER/FDA. She has regularly been involved in the review of NDA/BLA applications and provides assistance on pre-market IND reviews for senior statisticians at the agency. In addition, to reviewing work, she has also been involved with the standardization of programs for data analysis, a digital health technology working group, and the R based research projects.

Hye Soo originally graduated from UC Berkeley with a bachelor’s degree in Statistics and obtained her MS degree in Biostatistics from Northwestern University.

Presentation title: Review experience of the R consortium R submission pilot 1

Ning Leng, Director, Product Development Data Sciences, Roche – Genentech. Ning Leng is a People and Product Lead in Product Development Data Sciences in Roche-Genentech. Ning joined Roche-Genentech in 2016 as a statistician in the oncology early development and personalized healthcare group. Ning has worked on both early and late phase oncology development, with a special interest in utilizing diverse data sources and advanced methodologies to generate insights for personalized healthcare. Ning is an advocate of automation, open sourcing, and open collaboration in pharma. She is also passionate about connecting and helping people find new interests and opportunities. She serves as Roche representative on the R consortium board, co-leads the R consortium R submission working group, and co-leads the Meetup series of the Bay-area Biotech-pharma Statistics Workshop (BBSW). Ning holds a B.S. in Information and Computing Science from Beijing Institute of Technology and a Ph.D. in Statistics from the University of Wisconsin-Madison.

Paul Schuette is the Scientific Computing Coordinator for the Office of Biostatistics in the Center for Drug Evaluation and Research at the FDA and is a member of OB’s Division of Analytics and Informatics. Paul joined the FDA in 2008 after previously working in academia and as a government contractor.  He is the PI for a Cooperative Research and Development Agreement (CRADA) for detecting data anomalies in clinical trial data and is a member of FDA’s Scientific Computing Board, the High-Performance Computing Governing Advisory Board, FDA’s Modeling and Simulation working group, and CDER’s AI working group.  Paul received his Ph.D. and master’s degrees from the University of Wisconsin-Madison, with a specialization in probability theory, and his undergraduate degree in Mathematics from Kansas State University.

Coline Zeballos, R Strategy Lead at Roche Informatics. 

Coline is R Strategy Lead at Roche Informatics and as part of this role drives strategic topics around the use of open source programming languages such as important enablers like R Package Validation.

Coline is Swiss and French, based in Switzerland. After obtaining her MSc in Business Management from the University of Lausanne, she quickly oriented herself toward Data Science using Python. After several years in the finance sector, she became an entrepreneur where she was leading a team of data scientists and data architects in developing analytical solutions for SME during a couple of years before joining Roche.