This comprehensive workshop, hosted by TU Dortmund University and presented by experts Thomas Debray and Long Nguyen, offers participants a deep dive into the rapidly evolving field of personalized medicine. Tailored for researchers, statisticians, and healthcare professionals, this workshop explores the intricacies of treatment effect estimation—a cornerstone of personalized medicine that enables tailoring treatments to individual patients based on their unique characteristics.

What Participants Will Learn:

• Fundamentals of Treatment Effect Estimation: Understand the concepts and differences between Population Average Treatment Effects (ATE) and Conditional Average Treatment Effects (CATE). Explore the rationale behind estimating population-level effects and their implications for individual patients.
• Developing and Assessing Prediction Models: Gain hands-on experience in developing risk prediction models that identify patients' baseline risks. Learn to assess these models using key metrics like discrimination and calibration.
• Advanced CATE Prediction: Dive into the creation and evaluation of models that predict CATE to identify patient subgroups most likely to benefit from specific treatments. Discover how these models are evaluated to ensure accurate and reliable predictions.
• Application of R Packages: Familiarize yourself with the R packages “metamisc” and “precmed,” which are essential tools for implementing the discussed methodologies in real-world research.
• Synthesizing RCTs and Real-World Data: Learn strategies for combining data from randomized controlled trials with real-world evidence to enhance the applicability of research findings in clinical practice.

Benefits for Participants:

By attending this workshop, participants will not only gain foundational knowledge in personalized medicine research but also acquire practical skills in the development and evaluation of predictive models. These skills are essential for advancing personalized treatment strategies, improving patient outcomes, and staying at the forefront of healthcare innovation. This workshop is an excellent opportunity to network with experts in the field and to apply cutting-edge statistical methods in your research or clinical practice.

Whether you're new to personalized medicine or looking to deepen your expertise, this workshop promises to provide valuable insights and practical tools that can be directly applied to your work.

About the Presenters:

Thomas Debray, PhD: Thomas Debray is the founder of Smart Data Analysis and Statistics B.V., a consulting firm that specializes in the development and practical application of innovative statistical methods. With extensive experience as a scientist, he has led the development of advanced statistical methods, particularly in risk prediction and meta-analysis.

Long Nguyen, PhD: Long Nguyen is a tenure-track assistant professor at the University of Copenhagen. His research focuses on epidemiological and statistical methodologies at the intersection of causal inference and prediction modeling, with applications in medicine and public health. He is also an editor of the forthcoming book ‘Comparative Effectiveness and Personalized Medicine Research Using Real-World Data.’