2024 - Moneyball for Drug Development: How Causal Inference can Increase the Probability of Success in Clinical Trials

Discover an informative webinar that focuses on how studying oncological trial data and patient selection biomarkers can increase the probability of success (PoS).
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. But what if there was a proven process to identify trade-offs that could save precious resources when designing trials with the greatest probability of success?
The expert speakers will present results from studying patient selection biomarkers, which focus a trial on a subset of patients, possibly increasing the trial’s PoS. Conversely, this focus can reduce the patient population for which regulators approve a drug. To help companies consider this trade-off, the analysis provides unbiased, precise estimates of how much the focus increases a trial’s PoS. This analysis can help identify opportunities for underutilized biomarkers that can significantly impact PoS or where they are overutilized and their use offers little benefit in terms of PoS, unnecessarily reducing the target population.
The findings shared will empower sponsors to understand the impact of their choices better, de-risk pipelines and make more informed decisions regarding their clinical development strategies.
Register for this webinar today to learn how causal inference can revolutionize clinical trial design decision-making.
Keywords: Drug Development, Patient Data, Clinical Research, CRO, Oncology, Biomarkers, Data Analytics, Clinical Data, Data Management, Clinical Data Management, Data Science, Therapeutic Aras