The mantra “Correlation does not equal causation” is well known. However, causal inference, a new set of statistical techniques, can identify causal relationships and even derive experimental results and counterfactuals from historical data. In this webinar, the expert speakers will introduce causal inference and apply it to ten years of oncological clinical trial data, seeking opportunities to optimize trial design decision-making.

• How to use causal inference to understand the impact of clinical design decisions, specifically focusing on biomarkers inclusion criterion and clinical trial success
• The importance of combining quality data with the proper methodologies for more informed decisions
• How to apply state-of-the-art methodologies to clinical trials to uncover underlying causal relationships that can optimize decision-making
• The correlation between biomarkers and the probability of technical and regulatory success