Instructors
![Hana Lee, PhD](/_Images/member/Generic_Image_Missing-Profile.jpg)
Hana Lee, PhD
Senior Statistical Reviewer, OB/OTS/CDER, FDA, United States
Hana Lee, PhD, is a Senior Statistical Reviewer of the Office of Biostatistics in the CDER, FDA. She leads and oversees various FDA-funded projects intended to support development of the agency’s RWE program including multiple Sentinel projects to develop causal inference framework for conducting non-randomized studies, to enhance analytic capacity using machine learning-based methods, and to implement sensitivity analysis for RWE studies at the study design stage, and the BAA project on Targeted Learning. She is currently a co-lead of RWE scientific working group of the American Statistical Association (ASA) Biopharmaceutical Section.
Joo-Yeon Lee
Master Mathematical Statistician, FDA, United States
Joo-Yeon Lee is a senior mathematical statistician in Division of Biometrics VII at FDA/CDER. Since she joined FDA in 2007, she developed an expertise on pharmacometrics and design and analysis of post-market drug safety studies. She has reviewed sponsor led studies as well as collaborated with other investigators in FDA-led studies in Sentinel Distributed System and federal data partners. She has played a leading role in causal inference method working group in Division of Biometrics VII. Prior to joining FDA, she earned Ph.D in Biostatistics from Brown University.
![Laine Thomas](/_Images/member/Generic_Image_Missing-Profile.jpg)
Laine Thomas
Assistant Professor of Biostatistics and Bioinformatics , Duke University, Department of Biostatistics and Bioinformatics , United States
Dr. Thomas’ primary interest is causal inference methods, particularly using large data sets such as registries, Medicare claims and electronic health records. She is a co-investigator on the NIH-supported Statistical Methods for Complex Data in Cardiovascular Disease and primary investigator on the AHRQ-supported Matching Methods for Comparative Effectiveness Studies of Longitudinal Treatments. She uses causal inference methods in collaborations in cardiovascular disease (CHAMP-HF, ORBIT-AF registries; ACTION-NCDR and CRUSADE registries linked to Medicare; ARISTOTLE and NAVIGATOR clinical trials) and uterine fibroids (COMPARE-UF). She teaches the causal inference course in the Biostatistics and Bioinformatics Masters and PhD programs.
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