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.
- 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