Structured Exploration of Clinical Trial Data

In this webinar...

As clinical trialists begin to collect an increasing amount of biomarker and genomic data with the intent of relating these data to clinical outcomes, there is a need to help interpret these high-dimensional data. Advanced statistical learning methods provide a powerful approach to these questions, but need careful thought in how they are used and integrated into the process of interpretation of clinical data and building the evidence around a new medicine.

This webinar will provide an overview of a structured approach for safely applying these more advanced methods, discuss their application in practice, and explore how they can be used to guide scientific research.

Learning Objectives

  • Recognize opportunities to use advanced statistical methodology to generate hypotheses about clinical trial data
  • Outline the scope and limitations of statistical learning methods in the interpretation of clinical trial data
  • Evaluate the output of statistical learning methodologies


  • Paul Metcalfe, MMath, MA, PhD, Senior Director and Head, Data Science Solutions, AstraZeneca