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Monday, June 20 • 4:00pm - 5:00pm
#143: A Targeted Learning Framework for Causal Effect Estimation Using Real-World Data

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Component Type: Session
Level: Basic
CE: ACPE 1.00 Knowledge UAN: 0286-0000-22-537-L04-P ; CME 1.00; RN 1.00

This session will discuss how to maximize potential for informing regulatory decision making from real-world data by following the Targeted Learning Roadmap. Compare findings using TMLE+Super Learning with propensity score-based estimators. Develop a TL-based SAP.

Learning Objectives

Describe how to follow steps in the Targeted Learning (TL) Estimation Roadmap to extract reliable evidence from real-world data (RWD); Assess level of support for substantive conclusion; Recognize challenges of analyzing RWD, and how they can be mitigated by using data adaptive machine learning and TMLE; Access resources for developing a TL-based, completely pre-specified, statistical analysis plan.


Susan Gruber, PhD, MPH, MS


Targeted Learning for Real World Evidence
Mark van der Laan, PhD

Regulatory Perspective
Hana Lee, PhD

Industry Perspective
Yixin Fang, PhD


Yixin Fang

Medical Affairs and Health Technology Assessment, AbbVie, United States
Yixin Fang is a Director of Medical Affairs & Health Technology Assessment Statistics (MA&HTA Statistics) at AbbVie. He received his PhD degree in statistics from Columbia University and holds experiences combined in academia and pharmaceutical industry. His research interests include... Read More →
avatar for Susan Gruber

Susan Gruber

Principal, Putnam Data Sciences, LLC, United States
Dr. Susan Gruber is a biostatistician and computer scientist whose expertise is in the development and application of data adaptive methodologies to improve the quality of evidence generated by studies of observational health care data. She is a leading expert in Targeted Learning... Read More →
avatar for Mark van der Laan

Mark van der Laan

Professor in Biostatistics and Statistics, University of California, Berkeley, United States
Mark van der Laan is the Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at the University of California, Berkeley. He has made contributions to survival analysis, semiparametric statistics, multiple testing, and causal inference. He also developed the targeted... Read More →

Hana Lee

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... Read More →

Monday June 20, 2022 4:00pm - 5:00pm CDT
Room 183 B McCormick Place 2301 South Indiana Avenue Gate 40 Chicago, IL 60616
  11: Statistics, Session
  • Level Basic
  • Featured Topics RWD-RWE
  • Level Basic
  • Feature Topics RWD-RWE
  • Credit Type ACPE, CME, RN
  • Tags Session